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The New Quantum Era – innovation in quantum computing, science and technology
PodcastTechnologiePhysikEnglisch

The New Quantum Era – innovation in quantum computing, science and technology

von Sebastian Hassinger

NeuQuantum Error Correction and the Road to Fault Tolerance with Benjamin Bloom09.11.2026 · 40 Min.
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118
Erscheint
wöchentlich
Letzte Folge
9. Nov. 2026
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Über den Podcast

Your host, Sebastian Hassinger, interviews brilliant research scientists, software developers, engineers and others actively exploring the possibilities of our new quantum era. We will cover topics in quantum computing, networking and sensing, focusing on hardware, algorithms and general theory. The show aims for accessibility - Sebastian is not a physicist - and we'll try to provide context for the terminology and glimpses at the fascinating history of this new field as it evolves in real time.

Mitwirkende

Folgen 118

  1. Quantum Error Correction and the Road to Fault Tolerance with Benjamin Bloom

    40 Min.Folge 118

    Mit Benjamin Bloom

    Ben Bloom has an unusual vantage point on quantum computing: he built one of the world's most precise atomic clocks at JILA, learned semiconductor manufacturing discipline at Intel, watched a superconducting …

    Shownotes

    Ben Bloom has an unusual vantage point on quantum computing: he built one of the world's most precise atomic clocks at JILA, learned semiconductor manufacturing discipline at Intel, watched a superconducting startup scale from the inside at Rigetti, and then founded Atom Computing in 2018 to apply alkaline-earth atomic physics to quantum computation. He returned as CEO in 2024 to push the company through what he describes as the transition from binary technical challenges to engineering execution.

    The conversation lands at a pivotal moment. In June 2026, Atom published a paper demonstrating sustained, many-round toric-code quantum error correction on neutral atoms — including mid-circuit measurement and mid-computation atom replacement from a reservoir — the first time this has been done on this platform. The same month, the company closed a $100M Series C, signed a $100M Letter of Intent with the Department of Commerce, and announced a photonic networking partnership with Nu Quantum. The Magne system, built jointly with Microsoft for Denmark's QuNorth, is due around the turn of the year. If you want to understand what "fault-tolerant quantum computing" looks like when it stops being a research milestone and starts being an engineering program, this is the episode.

    What We Get Into

    • Why the toric-code QEC result is different from prior milestones — Bloom explains that the June paper was designed to demonstrate every component exactly as it would be used in a utility-scale system: mid-circuit measurement, atom loss, and live atom replacement from a reservoir, all running for ~90 error-correction cycles.
    • How atom loss goes from fatal flaw to managed engineering problem — Neutral atoms can literally escape the trap mid-computation. Bloom describes how Atom now cycles atoms between data-qubit and ancilla roles and reloads from a reservoir, removing what he calls the last "binary challenge" for the platform.
    • Why the number of qubits in a neutral atom system is a software question as much as a hardware one — Because the array is fully reconfigurable, the same physical system can run a shallow circuit with many logical qubits or a deep circuit with fewer, higher-distance logical qubits. Bloom explains why Atom gives approximate qubit numbers on its roadmap.
    • What "Level 2" means for the Magne system — The ~50-logical-qubit machine being delivered to QuNorth in Denmark is described as the first commercially available system with enough logical qubits and error-correction distance to go meaningfully beyond what's possible with a handful of logical qubits today. Bloom explains how the spec was driven by use cases, not raw qubit counts.
    • How the Microsoft partnership actually works — Bloom describes the relationship as starting in R&D and expanding to go-to-market, with Microsoft contributing error-correction software and stack expertise above the hardware layer, while Atom owns the physical system.
    • Why Atom's real competitive differentiation is invisible — Bloom argues that while all neutral atom companies work with the same atoms, Atom's proprietary work on fast laser steering, pipelining around atom movement, and system integration is where the competitive moat actually lives — and none of it is in public papers.
    • The engineering ceiling on a single neutral atom module — Bloom estimates tens of thousands to hundreds of thousands of qubits may be achievable in a single chamber before networking becomes necessary, and explains why Atom has been building photonic interconnect capability for nearly two years.
    • What utility-scale looks like in 2030 and 2031-32 — Bloom sketches a near-term picture of single systems with tens of thousands of qubits serving national lab and government customers, followed by networked fleets with potentially millions of qubits serving pharmaceutical, materials, and chemical companies on a time-to-solution pricing model.
    • What DARPA's QBI Stage C forced Atom to confront — Bloom says the program required Atom to sharpen its pencil on runtime and cost, not just qubit count, and that the team had to return to the drawing board more than once to ensure their roadmap actually produces answers in reasonable wall-clock time.
    • The founder-physicist CEO perspective — Bloom reflects on stepping back to CTO, what Rob Hays's tenure accomplished in building hyperscaler relationships, and why returning as CEO made sense once the company's challenge shifted back toward deep technical execution.

    Resources & Links

    Guest & Company

    Papers & Technical Results

    Magne System & Partnerships

    Funding & Government Programs

  2. Quantum Policy, Topological Qubits, and the Maryland Research Center with Charles Tahan

    55 Min.Folge 117

    Mit Charles Tahan

    Charles Tahan has one of the most unique career arcs in quantum: PhD in silicon quantum computing, postdoc across three continents, fifteen years at the Lab for Physical Sciences running quantum programs and …

    Shownotes

    Charles Tahan has one of the most unique career arcs in quantum: PhD in silicon quantum computing, postdoc across three continents, fifteen years at the Lab for Physical Sciences running quantum programs and doing original research, then the first Director of the National Quantum Coordination Office at the White House OSTP, and now a Partner at Microsoft Quantum. He is one of the very few people who has both written U.S. quantum policy and is now executing on it from inside a major hardware program. That dual vantage point — policymaker turned builder — gives him a kind of credibility that is rare in a field full of either pure researchers or pure advocates.

    The timing of this conversation matters too. Microsoft just opened a 15,000-square-foot quantum research center at the University of Maryland's Discovery District, and DARPA has been given on-site access to the Majorana 2 system as part of its Quantum Benchmarking Initiative — the first opportunity for a technically capable independent party to evaluate Microsoft's topological qubit claims. Tahan is candid about the difficulty of what Microsoft is attempting, honest about the timelines, and enthusiastic about the parts of this problem that most people in his position would prefer to keep vague.

    Listeners who follow quantum hardware development, national science policy, or the workforce and ecosystem questions around quantum will find this episode unusually grounded.

    What We Get Into

    • How Tahan ended up in government in the first place — starting as a DARPA technical consultant in 2007, helping write the milestones for the first quantum computing programs, and eventually becoming the first Director of the National Quantum Coordination Office
    • What the NQI actually accomplished — and why Tahan argues its most important effect wasn't the money itself but the signal it sent globally, triggering coordinated national strategies across dozens of countries
    • Why topological qubits are worth the difficulty — Tahan's honest case for why a high-risk, high-reward approach makes sense even when the engineering challenges are severe, and what the broader field has already gained from Microsoft's pursuit of Majorana physics
    • The DARPA Quantum Benchmarking Initiative as an independent audit — why having DARPA's technical team on-site to evaluate Majorana 2 is meaningful, and how Tahan thinks about external validation as a feature rather than a threat
    • Why Tahan now believes the next five years may equal the last thirty — his specific reasoning about how AI-accelerated science, the scale of capital flowing into computing infrastructure, and demonstrated quantum error correction have changed his sense of what's possible
    • The "simplest quantum computer" argument — what Tahan was actually proposing in his 2024 arXiv preprint (written as a retrospective from 2040, presented at APS in a Doc Brown costume), and how the idea of using quantum computers to generate training data for classical models fits into a near-term business model
    • What a quantum hardware makerspace actually is — the specific vision for the Maryland center's hands-on space, including dilution refrigerators, hardware from AMD, IQM, Quantum Motion, Fermilab's QICK tools, and a model Tahan hopes can be replicated and scaled
    • Why the workforce gap is a hardware problem, not just a software one — and how Tahan's own path (his father was an HVAC technician at the Smithsonian who got him a high school internship in astrophysics) shapes his conviction that hands-on experience is how scientists and engineers are actually made
    • Microsoft as a platform company — why Tahan frames Microsoft's quantum strategy as wanting the best computers for customers, full stop, which means partnering with and supporting other modalities, not just betting everything on topological qubits

    Resources & Links

    Guest Links

    Papers & Articles

    Organizations & Programs

  3. Atomic-Precision Silicon Qubits and the Path to Fault Tolerance with Michelle Simmons

    38 Min.Folge 116

    Mit Michelle Simmons

    Michelle Simmons is the founder and CEO of Silicon Quantum Computing (SQC) and a Scientia Professor at UNSW Sydney. She is one of the few people in the field who has simultaneously run a 200-person academic …

    Shownotes

    Michelle Simmons is the founder and CEO of Silicon Quantum Computing (SQC) and a Scientia Professor at UNSW Sydney. She is one of the few people in the field who has simultaneously run a 200-person academic research centre, founded Australia's first vertically integrated quantum computing company, shaped how the community publishes its results (as inaugural editor-in-chief of npj Quantum Information), and influenced national quantum policy. That combination of roles gives her an unusually grounded view of what is actually hard — in the physics, in the manufacturing, and in the business.

    The conversation is happening at a specific inflection point. SQC published two landmark Nature papers within ten weeks of each other in late 2025 and early 2026 — an 11-qubit silicon processor with two-qubit gate fidelities reaching 99.99%, and a 15,000-site analogue simulator demonstrating a metal-insulator transition. The company has advanced to Stage B of DARPA's Quantum Benchmarking Initiative, a program whose stated opening position is skepticism that fault-tolerant quantum computing is achievable by 2033. And SQC is now shipping an analog quantum AI chip to commercial customers. This episode is for anyone who wants to understand what silicon spin qubits actually are, why the donor-qubit approach is architecturally distinct from the CMOS-foundry approaches most competitors use, and what a credible long-range quantum roadmap looks like when it is grounded in manufacturing reality rather than theoretical aspiration.

    What We Get Into

    • Why qubit quality improves with scale in SQC's system — the physical intuition behind using phosphorus donor atoms as "nature's perfect qubit," and why minimizing interfaces is the key insight that separates this approach from gate-defined quantum dots
    • The STM as a manufacturing tool, not just a microscope — how Simmons reframed the scanning tunneling microscope as the atomic-scale equivalent of an ASML stepper, and why 25 years of development now yields half a million registers in half a day at sub-nanometer precision
    • What the 15,000-site analogue simulator actually demonstrated — the distinction between analogue simulation and gate-model computation, what a metal-insulator transition tells you about correlated quantum matter, and why this device is also a tool for validating the gate-model processor as it scales
    • Six qubits per lead and all-to-all connectivity — how hyperfine frequency selection lets SQC address multiple nuclear spin qubits through a single electrical lead, and why that matters for error correction overhead
    • The eight-stage roadmap, set in 2014, and how it has held up — Simmons mapped her milestones onto the 1947–1981 arc of classical semiconductor development; two of the three near-term milestones came in ahead of schedule
    • DARPA QBI Stage B: what it validates and what it doesn't — why Simmons describes the program as "gold for a company" and how external scrutiny is forcing SQC to solve operating-environment questions earlier than planned
    • Quantum reservoir computing as a near-term product — how SQC's analog AI chip is already in customers' hands, cutting one communications company's training time from three weeks to two days, and why this is a bridge to the fault-tolerant era rather than a detour from it
    • Why you cannot outsource quantum manufacturing — Simmons's argument, drawn from decades of hands-on fabrication, that the teams who treated manufacturing as a commodity have paid a steep price
    • The hype question, answered by someone who has lived it — as a journal editor, APS division chair, and company CEO, Simmons has a rare vantage point on where the field's communication problems actually originate
    • What "fault tolerant" will need to mean in 2033 — and why the definition of that phrase is going to require as much parsing as the hardware milestone itself

    Resources & Links

    Guest & Company

    Papers & Results

    DARPA Program

    Context & Analysis

    Key Quotes & Insights

    "Nature's perfect qubit." Simmons's phrase for the phosphorus donor atom in silicon: the qubit state forms naturally when the atom is placed, without complex materials engineering, in an environment where the silicon matrix acts as the vacuum does for trapped ions.

    "Every atom counts." SQC's company motto, and a literal description of their manufacturing philosophy — because they know the position and behavior of every atom in every device, every chip is a learning opportunity.

    > "I've never really seen...

  4. Building a Regional Quantum Ecosystem with Corey Stambaugh

    30 Min.Folge 115

    Mit Corey Stambaugh

    Corey Stambaugh is one of the few people in the quantum world who has worked at the bench, inside federal policy, and now as the operational lead of a major public-private ecosystem initiative. He came up as a …

    Shownotes

    Corey Stambaugh is one of the few people in the quantum world who has worked at the bench, inside federal policy, and now as the operational lead of a major public-private ecosystem initiative. He came up as a precision measurement physicist at NIST, moved to the White House's National Quantum Coordination Office as a senior policy advisor, and now directs the Capital of Quantum — Maryland's statewide effort to translate decades of university research into a commercial quantum industry cluster anchored in the Discovery District at the University of Maryland.

    This conversation was recorded at the close of the 2026 Quantum World Congress, a week in which Maryland opened the Microsoft Quantum Research Center, announced Riverlane's U.S. headquarters in the Discovery District, welcomed QuEra Computing into the building, and unveiled a new partnership with Paladin Capital Group. If you follow quantum economic development, workforce policy, or the question of which regions are actually building durable quantum infrastructure versus generating press releases, this episode gives you a rare inside view from someone threading all of it together.

    What We Get Into

    • How the Capital of Quantum actually came together — the decades of university research that preceded the January 2025 launch, and what it took to stand up a formal initiative on top of that foundation
    • What "150,000 square feet and a fridge at 14 millikelvin" means in practice — the Discovery Center build-out, from Microsoft buying the building to pumping down their dilution refrigerator in under a year
    • Why the tenant list spans almost every major hardware modality — IQM (superconducting), Quantum Motion (silicon CMOS), Microsoft (topological), IonQ (trapped ion), QuEra (neutral atom), and Riverlane (error correction software) are all in or adjacent to the same building, and whether that's strategy or circumstance
    • The DARPA Capital Quantum Benchmarking Hub — Maryland is one of three states with a memorandum of agreement under DARPA's QBI program, and what that independent benchmarking infrastructure means for an ecosystem that also hosts the companies being evaluated
    • Quantum sensing as the near-term economic story — why Stambaugh, a metrologist by training, sees sensing startups like Euclid (NV diamond magnetometers for semiconductor inspection) as having clearer market paths than computing or networking right now
    • The Paladin Capital partnership and the DC venture gap — why the mid-Atlantic VC culture differs from the West Coast model and what the initiative is doing to change the capital formation picture
    • Workforce development from Q12 to the makerspace — a classroom next to a working dilution refrigerator, high school students from across the street getting their first look at a cryostat, and the lineage from early NSF quantum education workshops to the UN International Year of Quantum
    • How Stambaugh thinks about competing ecosystems — Colorado, Illinois, New Mexico — and why he frames them as complementary rather than adversarial, while still being clear about Maryland's competitive positioning

    Resources & Links

    Guest & Initiative

    Key Announcements Referenced in This Episode

    Background & Context

    Key Quotes & Insights

    "Tell me where a national lab is, I'll tell you where a physicist is, and I'll tell you where quantum is." — Stambaugh on why quantum clusters form where they do, and why the lineage from NIST, Sandia, and Argonne to today's startups is not accidental.

    "We ...

  5. Quantum Workforce, Sensing, and the Long Game of Operationalization with Isabella Martinez

    38 Min.Folge 114

    Mit Isabella Bello Martinez

    Isabella Martinez sits at an unusual intersection in the quantum ecosystem: she's not primarily a hardware researcher or an algorithm theorist, but a practitioner who has to make quantum work in operational …

    Shownotes

    Isabella Martinez sits at an unusual intersection in the quantum ecosystem: she's not primarily a hardware researcher or an algorithm theorist, but a practitioner who has to make quantum work in operational environments — for customers who have real missions, real constraints, and very little patience for technology that can't be deployed. Her team at Booz Allen spans quantum computing, quantum sensing, and post-quantum cryptography, which means she's watching all three of the field's major near-term vectors simultaneously.

    This conversation was recorded at Quantum World Congress 2026, and it reflects the mood of that moment: sensing is on the cusp of real deployment, PQC migration is being driven by policy urgency, and quantum computing is still asking the question of when — but the "when" is getting more specific. If you work in quantum and care about how the technology actually crosses the gap from lab to mission, this episode is for you. It's also a genuinely useful listen for anyone thinking about quantum careers, workforce development, or how to build teams that can navigate a technology that doesn't yet have a playbook.

    What We Get Into

    • Why Isabella's biomedical engineering capstone — not a physics class — shaped her entire approach to quantum: The lesson wasn't about building a better device; it was about why a life-saving tool sat unused because no one had time to get trained on it.
    • The four-stage commercialization arc she uses to frame quantum maturity: Solve for physics, then engineering, then business case, then operationalization — and why that last step is the one the field talks about least.
    • What quantum sensing deployment actually looks like right now: Including a vivid example of a quantum PNT sensor that "can't get wet" and what happens when you try to put it in a waterproof box without destroying its precision advantage.
    • Why quantum sensing and quantum computing will diverge in their adoption paths: A drone operator doesn't need to know their navigation data is quantum-derived. A quantum computing user, at least for now, probably does — and that changes everything about how you design for adoption.
    • How Booz Allen's team discovered the wrong part of a drug discovery workflow was being targeted for quantum speedup: A computational biologist and chemist sat down with the physics team and revealed that the step everyone assumed was the bottleneck wasn't the bottleneck at all.
    • Why Isabella actively recruits people with criminology degrees, economics backgrounds, and education startup experience onto a quantum team: And why she's more worried about the rise of pure quantum-only graduate programs than she is about the talent shortage.
    • The AI parallel that's shaping how enterprise customers think about quantum timing: Customers who watched AI capabilities leap unexpectedly are now asking "when" instead of "what" — but they're also more willing to wait for the right moment rather than jump in early.
    • Her honest read on NISQ-era value: Real scientific output is happening on today's devices, but the early 2030s are where she expects the first commercially meaningful fault-tolerant results to appear.
    • What the quantum community risks losing as the field matures: The collaborative, cross-disciplinary spirit that has defined the early era — and why she thinks that spirit is actually a competitive asset worth protecting.

    Resources & Links

    Guest & Organization

    Articles by Isabella Martinez

    Context & Policy

    Key Quotes & Insights

    > "The problem wasn't actually an engineering problem. An engineering tool existed for the problem they were having us solve. The problem was that getting certified to use that tool took so long that most nurses didn't have the time to get trained on it."

    — Isabella on the capstone project that shaped her entire career philosophy: adoption is often a harder problem than invention.

    > "First you have to solve for physics, then you have to solve for engineering, and then you have to solve for business case. But I would argue then you have to solve for operationalizing something — which is even beyond them."

    — On the four-stage arc that the quantum field's commercialization narrative tends to stop one step too early.

    Insight: When Booz Allen sat a computational biologist and chemist down with their quantum algorithm team to walk through an actual drug discovery workflow, the team discovered that the step they'd assumed was the computational bottleneck wasn't the bottleneck at all. The right use case only became visible when the domain experts were in the room.

    > "I need to do this purposefully. I have to purposefully open reqs where we are looking for people with more than just a physics degree."

    — On why interdisciplinary hiring is a deliberate strategy, not a nice-to-have.

    Insight: Isabella draws a direct parallel between the rise ...

  6. Superconducting Qubits, STAR Architecture, and Diamond-Spin Qubits with Dr. Shintaro Sato

    41 Min.Folge 113

    Mit Shintaro Sato

    Dr. Shintaro Sato is a Fellow and Head of the Quantum Laboratory at Fujitsu Research, and Deputy Director of the RIKEN RQC-Fujitsu Collaboration Centre. He oversees Fujitsu's entire quantum effort — from device …

    Shownotes

    Dr. Shintaro Sato is a Fellow and Head of the Quantum Laboratory at Fujitsu Research, and Deputy Director of the RIKEN RQC-Fujitsu Collaboration Centre. He oversees Fujitsu's entire quantum effort — from device fabrication through error correction architecture, software, and application research — and has been building toward commercial quantum systems since Fujitsu began its serious quantum R&D push around 2020. With over 164 publications spanning graphene nanoelectronics, superconducting qubit design, and fault-tolerant architectures, he brings both deep technical credibility and a rare full-stack perspective.

    This conversation is timely because two significant developments converged almost simultaneously just before recording: Fujitsu announced a tin-vacancy (SnV) diamond-spin prototype developed with TU Delft and QuTech, and began testing its STAR error-correction architecture on neutral-atom hardware with startup Yaqumo — an explicit signal that Fujitsu is betting on hardware-agnostic software layers even as it races to scale its own superconducting devices. Listeners who follow quantum hardware roadmaps, fault-tolerant computing, or Japan's national quantum strategy will find this episode unusually specific and candid.

    What We Get Into

    • How Fujitsu actually fabricates its superconducting chips — Sato explains how the team adapted Nakamura-sensei's original RIKEN designs, developed their own Josephson junction uniformity techniques, and built a research fab capability from scratch rather than licensing finished devices.
    • Why packaging is the hardest problem at 1,000+ qubits — not the qubits themselves, but the superconducting wiring, chip-to-chip interconnects, interposers, and the sheer number of control lines running from room temperature to millikelvin. Sato is candid that his engineers "don't want to do it anymore."
    • What STAR architecture actually does — it's not a new error-correction code; it operates at the logical gate layer above the surface code, replacing the notoriously expensive T gate with phase-rotation gates and selectively reintroducing T gates only when rotation angles would otherwise accumulate too much error. Version 3 achieves roughly a 10x accuracy improvement over version 2 for the same physical qubit count.
    • Why STAR is hardware-agnostic — because it operates at the logical operation layer rather than the physical error-correction layer, it can in principle run on any hardware modality. Fujitsu has now begun testing it on Yaqumo's neutral-atom platform, and Sato mentions QuEra has also demonstrated STAR independently.
    • What tin-vacancy (SnV) diamond-spin qubits are actually for — not a replacement for superconducting qubits, but a photonic interconnect technology. SnV centers emit photons that can carry quantum information between modules, potentially linking separate dilution refrigerators — a transduction approach that sidesteps one of the hardest problems in scaling superconducting systems.
    • The speed mismatch problem in hybrid architectures — superconducting qubits operate at gigahertz speeds; nuclear spins in diamond-spin systems operate at kilohertz. Sato acknowledges this directly and frames it as an architectural challenge analogous to CPU-memory hierarchies in classical computing.
    • What Fujitsu's open-source strategy looks like in practice — the collaboration with Osaka University on Project Octopus, which produced an open-source full-stack control and software platform, is now being adopted as part of Fujitsu's commercial offering.
    • What 2030 actually looks like — Sato is measured: a 10,000-qubit machine will still be a "very small scale logical quantum computer," most useful for quantum chemistry in hybrid HPC+quantum workflows. Revolutionary applications will come incrementally, not all at once.
    • The long-term vision — Sato's stated dream is a quantum computer small enough to fit in a smartphone, which he acknowledges requires entirely different physics than anything on today's roadmap.

    Resources & Links

    Guest & Organization

    Hardware Roadmap & STAR Architecture

    Diamond-Spin & SnV Prototype

    Neutral-Atom / Yaqumo Collaboration

  7. Quantum Venture Investing from the Lab to the Market with Marie Lepske

    41 Min.Folge 112

    Mit Marie Lepske

    Marie Lepske brings a combination that's genuinely rare in venture: a background in applied mathematics and physics, early experience covering quantum at Runa Capital before most generalist funds knew the field …

    Shownotes

    Marie Lepske brings a combination that's genuinely rare in venture: a background in applied mathematics and physics, early experience covering quantum at Runa Capital before most generalist funds knew the field existed, and now a GP seat at Constructor Capital, which closed a $110M Fund I in February 2026 with more than half its capital directed toward next-generation computing including quantum. She backed Qnami at Runa — a quantum sensing company acquired by Quantum Design in June 2026, one of the few clean sensing exits the field has produced — and Constructor's portfolio includes QuEra, which raised over $230M in a round led by Google Quantum AI and SoftBank.

    The conversation matters now because the quantum investment landscape is genuinely changing. SPAC activity, mega-rounds from hyperscalers, and rising valuations are pulling in non-specialist capital at the same time that the science is getting harder to evaluate from the outside. Lepske is one of the people who has to navigate that tension every day, and she's willing to name the failure modes.

    Founders building quantum or deep-tech companies, investors trying to understand where specialist and generalist capital intersect, and technically curious listeners who want to understand how the business side of quantum actually works will all find this episode useful.

    What We Get Into

    • Why technical training matters at the earliest stages — and what it actually buys you when a founding team's only asset is a laboratory and an optical table, before there's even a legal entity
    • How the specialist-versus-generalist divide is evolving — Lepske's 2022 argument that early-stage quantum would stay specialist territory, and how she reads the arrival of Google, SoftBank, and NVIDIA in QuEra's cap table
    • The due diligence framework for pre-product science startups — team provenance, patent landscape, IP legal review, and how Constructor uses its scientific advisory board to validate founders they can't fully assess internally
    • What a "no" looks like — the specific signals that make Constructor wait rather than invest, including teams with strong science but no credible path to market and IP positions that are already crowded
    • The Qnami exit and what it reveals about quantum sensing — why sensing applications are currently concentrated in R&D markets, which verticals Lepske thinks will break out first, and why sensing competes with computing for buyer attention
    • The SPAC problem — why the wave of quantum public listings concerns her, and why evaluating roadmap credibility requires the kind of deep familiarity that takes years to build
    • How Constructor supports portfolio companies beyond capital — executive hiring, software development guidance, co-investor introductions, and the limits of that hands-on model
    • AI and quantum as parallel tracks — why she doesn't see AI as cannibalizing quantum talent or capital, and where she thinks the two fields will eventually converge

    Resources & Links

    Guest & Fund

    Portfolio Companies Referenced

    Background Reading

    Recent Constructor News

    Key Quotes & Insights

    On what early-stage diligence actually looks like: > "They have only laboratory, and they have optical table which they want to show to you and you should understand if they have some interesting and useful patents or they can file them during the next one to two years."

    On where specialist and generalist capital divide: > "These bigger players, they're coming later. They're coming when we already investigated that this particular technology and this particular team actually could win."

    On the SPAC problem: > "It's very difficult for [non-specialist investors] to evaluate if they're doing proper investment or not, or if this valuation is good or not… You should be able to find out these roadmaps and to understand if this is a real roadmap or just written for the SPAC."

    Insight — sensing vs. computing for buyer attention: Lepske observes that quantum sensing is structurally underappreciated relative to computing, not because the products aren't real, but because governments and corporates perceive computing as the larger prize — which she suggests is not obviously correct.

    Insight — quantum talent scarcity as a leading indicator: She notes that quantum computing companies are now competing for talent the way AI companies did four or five years ago, with roughly 400–450 relevant laboratories globally — a number that puts the field's scale in sharp relief.

    Related Episodes

  8. Rational Quantum Mechanics and the Qubit Ceiling with Tim Palmer

    47 Min.Folge 111

    Mit Tim Palmer

    Tim Palmer is not a quantum computing skeptic from the outside. He is a Fellow of the Royal Society, a CBE, an IPCC lead author, and the inventor of probabilistic ensemble forecasting — techniques now used in …

    Shownotes

    Tim Palmer is not a quantum computing skeptic from the outside. He is a Fellow of the Royal Society, a CBE, an IPCC lead author, and the inventor of probabilistic ensemble forecasting — techniques now used in every major weather prediction center on Earth. He did his PhD in general relativity under Roger Penrose. When someone with that profile publishes a peer-reviewed paper in PNAS arguing that the entire fault-tolerant quantum computing roadmap may rest on a mathematical assumption that is subtly and profoundly wrong, it is worth paying close attention.

    The timing matters. The quantum computing industry is spending billions on the assumption that standard quantum mechanics scales indefinitely — that if you can build enough error-corrected qubits, Shor's algorithm will eventually factor RSA-2048. Palmer's RaQM framework, reviewed by leading quantum foundations researchers including Lucien Hardy and Nicolas Gisin, makes a concrete, falsifiable prediction that this assumption will fail somewhere between 200 and 1,000 error-corrected qubits. That falsification window is opening right now. This episode is for anyone who cares about the foundations of quantum mechanics, the long-term viability of fault-tolerant quantum computing, or the rare pleasure of watching a serious scientist put a real stake in the ground.

    What We Get Into

    • Why Palmer left general relativity and came back to quantum foundations decades later — the conceptual thread connecting chaos theory, climate forecasting, and the geometry of quantum state space
    • What Rational Quantum Mechanics actually proposes — specifically, why Palmer argues that Hilbert space should be defined over rational numbers rather than the full continuum of complex numbers, and what that means physically
    • The information-theoretic argument for a qubit ceiling — why, in RaQM, the information content of n entangled qubits grows linearly with n rather than exponentially, and why that creates a hard conflict with the quantum Fourier transform above a few hundred qubits
    • Why the 2022 Nobel Prize did not prove non-locality — Palmer's careful distinction between "Bell's inequality is violated" (experimentally established) and "the world is non-local" (an interpretation), and why that distinction matters enormously
    • How gravity enters the picture — Palmer's argument, drawing on Penrose-style thinking, that gravity is the physical mechanism responsible for discretizing Hilbert space, and how that determines the numerical qubit ceiling
    • Why the ceiling is technology-dependent but bounded absolutely — how Palmer estimates ~400 qubits for current photonic technology and argues that no technology, however exotic, can push the limit above ~1,000
    • What happens to Shor's algorithm specifically — why the quantum Fourier transform is the precise point of failure, and what that means for RSA encryption and the post-quantum cryptography transition
    • The optimistic read on a potentially negative result — Palmer's argument that a fundamental discovery about quantum mechanics, even one that limits quantum computing, could open doors we cannot yet imagine, in the same way general relativity eventually gave us GPS

    Resources & Links

    Guest

    Papers & Articles

    Further Reading

    • The Primacy of Doubt — Oxford University Press — Palmer's 2022 trade book synthesizing chaos, climate, and quantum uncertainty; accessible entry point to his broader thinking
    • 214 is a delightful bonus to the conversation, a short story by Noel Gorelick that imagines what might happen if RaQM turns out to be true.

    Key Quotes & Insights

    > "It's not that nature ...

  9. Classical Reversible Computing on Quantum Dots with Daniel Loss

    49 Min.Folge 110

    Mit Daniel Loss

    Daniel Loss is RDIA Chair Professor of Quantum Computing and Director of the Quantum Center at King Fahd University of Petroleum and Minerals in Saudi Arabia, where this work was done. He is also one of the …

    Shownotes

    Daniel Loss is RDIA Chair Professor of Quantum Computing and Director of the Quantum Center at King Fahd University of Petroleum and Minerals in Saudi Arabia, where this work was done. He is also one of the most influential theorists in quantum computing. The 1997 Loss-DiVincenzo proposal — that electron spins in quantum dots could serve as qubits — now has more than 9,000 citations and is the conceptual foundation for the semiconductor spin-qubit platforms that Intel, HRL, Diraq, and a wave of European startups are actively building toward. In 2025, Loss was named a Clarivate Citation Laureate in Physics, a designation with a strong historical track record as a Nobel Prize predictor.

    The reason to listen now is that Loss has turned his attention to a question that predates quantum computing itself: can reversible, energy-efficient classical logic be physically realized? His 2026 paper argues that the spin-qubit hardware the field has spent decades developing is, almost incidentally, the ideal platform to do exactly that — and that the energy advantage over room-temperature CMOS could be so large it would matter enormously for AI inference workloads and data-center power budgets. This episode is for anyone following the spin-qubit roadmap, the energy crisis in classical computing, or the deeper question of what semiconductor quantum hardware is ultimately good for.

    What We Get Into

    • Why reversible computing is having a moment now: The ideas of Landauer, Bennett, Fredkin, and Toffoli have been around since the early 1980s — Loss explains what changed experimentally that makes the proposal feel like engineering rather than philosophy.
    • The core energy claim, unpacked: Loss walks through why a spin-qubit Toffoli gate operating near 4 Kelvin could cost roughly 10⁵ times less energy than its CMOS equivalent, even after accounting for refrigeration overhead — and where the accounting is still incomplete.
    • What makes the computation classical and the hardware quantum: The gate uses coherent quantum dynamics internally, but inputs and outputs are classical spin states. No superposition is required between gate operations, which dramatically relaxes the error-correction burden.
    • The iToffoli gate and why it works for classical logic: Loss describes how a target spin hopping between quantum dots, controlled by two neighboring spins, implements a universal reversible gate using only DC voltage pulses — no radio-frequency drives required.
    • The Quantum Zeno trick for classical memory: Frequent projective measurement of a spin state can stabilize it against relaxation, turning one of quantum computing's central headaches into a feature for classical storage.
    • Why AI inference is the natural first application: Error tolerance, parallelizability, and the absence of a need for new algorithms make AI inference workloads a compelling early target — and Loss argues this de-risks the spin-qubit enterprise regardless of whether fault-tolerant quantum computing arrives on schedule.
    • The dual-use platform argument: The same germanium/silicon quantum-dot array could, in principle, run quantum algorithms when superposition is useful and classical reversible logic when it is not — a flexibility that changes the economic calculus for building the hardware.
    • What the experimental community needs to do next: Loss describes the first falsifiable tests — a three-spin iToffoli truth table, energy budget measurements, and a five-dot reversible adder — and names the groups best positioned to run them.
    • How the brain comparison reframes the stakes: Loss notes that his energy estimates put spin-qubit classical computing roughly four orders of magnitude below the energy cost of a biological synapse, which has implications for how we think about the physical limits of AI.

    Resources & Links

    Guest & Lab

    Papers & Articles

    Organizations

    Key Quotes & Insights

    > "If the physical platform is successful, we are guaranteed to have killer applications — because I don't need to find new algorithms for this." > — Loss on why classical reversible computing de-risks the spin-qubit investment, regardless of the timeline for fault-tolerant quantum algorithms.

    > "The energy difference is a factor of ten to the fifth. And this is mind-blowing." > — Loss summarizing the device-level energy advantage of a spin-qubit Toffoli gate over its CMOS equivalent, after accounting for refrigeration overhead.

    Insight: Loss argues that the Quantum Zeno effect — the tendency of frequent measurement to freeze a quantum state — can be used deliberately to stabilize classical spin states against relaxation, turning a well-known quantum-computing obstacle into a memory-stabilization tool for classical logic.

    Insight: The proposal requires superposition only inside a gate operation, not between operations. This means the error-correction burden is classical (majority voting) rather than quantum (surface codes or similar), which is a qualit...

  10. Quantum-Inspired AI and Tensor Network Compression with Román Orús

    41 Min.Folge 109

    Mit Román Orús

    Román Orús is one of the rare physicists who built a foundational mathematical tool — tensor networks — and then watched it become the engine of a unicorn. His 2013 introduction to tensor networks has been …

    Shownotes

    Román Orús is one of the rare physicists who built a foundational mathematical tool — tensor networks — and then watched it become the engine of a unicorn. His 2013 introduction to tensor networks has been cited over 2,000 times; his company, Multiverse Computing, just announced a $570 million Series C at a $1.7 billion pre-money valuation. That arc — from condensed matter theory to Europe's largest quantum software company — is worth understanding on its own terms. But what makes this conversation particularly timely is a May 2026 paper Orús co-authored demonstrating that individual layers of Meta's Llama 3.1 8B language model can be encoded as quantum circuits and executed on IBM's 156-qubit Quantum System Two while the model generates text. It's a proof of concept, not a product — but it's a real result, and Orús is honest about what it does and doesn't prove.

    This episode is for listeners who want a technically grounded, hype-free account of the quantum-AI intersection: what tensor networks actually are, why they keep getting rediscovered across different fields, where classical simulation of quantum systems genuinely competes with quantum hardware, and what it looks like to build a company at the boundary between those two worlds.

    Sponsor Message

    The Capital of Quantum is a people story. Built on a top-five quantum PhD program and 35-plus years of quantum research leadership. It's the billion-dollar initiative behind Discovery Center, launching this month with Microsoft, IQM, and Quantum Motion inside. That's why IonQ was born and is headquartered here, and why global companies keep choosing a spot minutes from Washington, D.C. This is where quantum is transforming the world. Come see it at the Quantum World Congress, September 23rd through 25th, College Park, Maryland. CapitalOfQuantum.com.

    What We Get Into

    • What tensor networks actually are — Orús explains the core idea without equations: tensors as the "DNA" of a quantum state, and how a network of them lets you see and quantify the internal correlations (entanglement) that matter versus the ones you can safely ignore.
    • Why the same math keeps appearing in different fields — from condensed matter simulation to quantum computing simulation to machine learning, and why Orús sees that recurrence as a sign of something deep rather than a coincidence.
    • How ChatGPT changed Multiverse's trajectory — the company was already applying tensor networks to machine learning before 2022; the emergence of large language models gave them a problem where the fit was obvious and the market was enormous.
    • What "90–95% compression with minimal accuracy loss" actually means — Orús explains the overparameterization problem in current AI models and why he believes tensor networks address a genuine structural inefficiency, not just a tuning opportunity.
    • The IBM kicked Ising model episode — Orús describes how his team rapidly produced a classical tensor network simulation of an experiment IBM had presented as evidence of quantum utility, and what that kind of competition between classical and quantum methods actually does for the field.
    • The Cayley Unitary Adapter experiment — how Multiverse sliced individual layers out of Llama 3.1 8B, encoded them as quantum circuits, ran them on a 156-qubit IBM processor, and achieved a 1.4% perplexity improvement — and why Orús argues the improvement-per-parameter ratio is the number that matters, not the headline percentage.
    • Why edge deployment is the real commercial driver — drones, satellites, vehicles, and industrial devices that cannot rely on cloud connectivity are the market pulling Multiverse toward smaller, more efficient models, not just benchmark competition with frontier labs.
    • How Orús thinks about Multiverse's identity — he calls it a "quantum AI company," not a quantum company or an AI company, and explains what that distinction means for how they allocate research effort and where they expect to be when fault-tolerant quantum hardware matures.
    • What he'd tell a PhD student today — a genuinely honest answer about the trade-offs between academic research and deep-tech industry, from someone who has lived both simultaneously.

    Resources & Links

    Guest & Company

    Papers & Articles Discussed in This Episode

    Models & Products

    Funding & Company Context

    Key Quotes & Insights

    > "We are using atomic bombs to kill a mosquito." Orús on the overparameterization of current large language models — and why he believes the transformer-attention paradigm, however successful, ...

  11. Quantum Workforce Intelligence from qubitsok.com with Piotr Lewandowski

    46 Min.Folge 108

    Mit Piotr Lewandowski

    Piotr Lewandowski is a software engineer based in Poland who, as a side project, has built something that no well-funded research institute has: a continuously updated, ontology-tagged intelligence platform …

    Shownotes

    Piotr Lewandowski is a software engineer based in Poland who, as a side project, has built something that no well-funded research institute has: a continuously updated, ontology-tagged intelligence platform that ingests the entire quant-ph archive, tracks thousands of open quantum roles across hundreds of companies, parses patents and grants and open-source repositories, and links all of it to individual researcher profiles. He is not a tenured academic or a hardware engineer. He is an independent data practitioner, and that outsider position gives him a vantage point on the quantum workforce that insiders rarely have — or rarely share.

    This conversation matters now because the quantum industry is simultaneously claiming a generational workforce opportunity and struggling to fill highly specialized roles. Lewandowski's data offers a rare ground-truth check on both claims. If you work in quantum hiring, research, policy, or investment — or if you're a student trying to understand what the field actually looks like from the outside — this episode will give you a more honest picture than almost anything else currently available.

    What We Get Into

    • How qubitsok's 500-tag ontology was built from scratch — why Lewandowski chose a tree-structured, parent-child tag system rather than relying on existing academic metadata infrastructure, and how it steers AI toward the most specific and useful classification rather than broad category labels.
    • What the full quant-ph corpus reveals about researcher mobility — which countries are gaining quantum talent (Germany and China are notable winners) and which are losing it (the US and Australia are among the top brain-drain sources), based on tracking affiliation changes over time in published papers.
    • The rising share of industry authorship in quantum research — industry-affiliated authors have grown from roughly 3.4% of quant-ph papers in 2005 to nearly 14% in 2026, and what that structural shift might mean for what gets published — and what doesn't.
    • Why the platform tracks open-source contributions alongside papers — when researchers join industry and their publication rate drops, their open-source activity becomes a meaningful proxy for continued technical engagement, and qubitsok indexes both.
    • The "qubie" talent-matching tool Lewandowski is building — rather than keyword overlap, qubie dispatches sub-agents to extract specific, claim-level evidence from a researcher's papers, dissertations, and other public writing, then returns a structured profile and interview guide for each candidate.
    • Why sourcing quantum talent is a fundamentally different problem than general tech recruiting — the evidence of what a quantum researcher can actually do is largely public and published, but no one has had the infrastructure to read it systematically at scale until now.
    • The two product directions Lewandowski is weighing — analytics and competitive intelligence for investors and companies versus talent matching for quantum hiring — and why he's currently prioritizing the latter.
    • What it means to build a field-level intelligence platform as an outsider — Lewandowski is neither employed by a quantum company nor affiliated with a university, and that independence shapes both what he can see and what he can say.

    Resources & Links

    Guest Links

    • qubitsok.com — The platform itself: quantum job board, daily arXiv paper digest with semantic tagging, and researcher collaboration search. All free for researchers and job seekers.
    • qubitsok.com/collaborate — Search for quantum researchers by expertise, ontology tag, and affiliation — useful for finding collaborators or co-authors.
    • Piotr Lewandowski on LinkedIn — The best place to reach him directly, especially if you're a company interested in early access to the qubie talent-matching product.
    • Piotr Lewandowski on YouTube — His channel covering quantum computing job market analysis and platform updates.

    Papers & Reports

    Tools & Platforms

    • qubitsok.com/jobs — Live quantum job listings, filtered by the platform's 500-tag ontology.
    • qubitsok.com/region/europe — Live European quantum jobs market data, useful context for the EU talent and salary discussion.
    • qubitsok.com/hire — Information for companies looking to use qubitsok's candidate database and, soon, the qubie matching tool.

    Recognition

    Key Quotes & Insights

    On why the published record is a better hiring signal than a LinkedIn profile: > "Research gives you this unique lens to see people's work before you talk to them. You can be really prepared, and this helps on two sides — you talk to people actually capable of filling the role, and you're not wasting their time asking questions they already answered via their published work."

    On what brain-drain data actually shows: > "The biggest country that gained quantum computing talent in the last twenty-four months is Germany — which is not something someone could expect. And the biggest countries getting brain-drained are, interestingly, the United States."

    Insight — on the soul-crushing reality of quantum sourcing: Lewandowski's first job in college was sourcing — going through profiles with pen and paper, making cold calls that nobody wanted to receive. His argument is that quantum hiring doesn't have to work that way, because the evidence of what a researcher can do is already public. The problem has never been a lack of signal; it's been a lack of infrastructure to read it.

    On the rising share of industry authorship: Industry-affiliated authors have grown from roughly 3.4% of quant-ph papers in 2005 to nearly 14% in 2026 — a structural shift in who is producing the science, with implications for what gets published and what gets quietly redirected into proprietary pipelines.

    Insight — on the limits of the data: Lewandowski is consistently careful about w...

  12. Quantum Risk, Readiness, and the Enterprise Boardroom with Richard Entrup

    36 Min.Folge 107

    Mit Richard Entrup

    Richard Entrup is unusual in quantum circles: he's not a physicist, and he doesn't pretend to be. He spent decades as a CIO, CTO, CDO, and CISO at organizations including Verizon, Christie's, Tiffany & Company …

    Shownotes

    Richard Entrup is unusual in quantum circles: he's not a physicist, and he doesn't pretend to be. He spent decades as a CIO, CTO, CDO, and CISO at organizations including Verizon, Christie's, Tiffany & Company, MoMA, Disney/ABC, and Time Warner before joining KPMG to lead its Emerging Solutions practice. That background — deep operational experience on the client side — shapes everything about how he thinks about quantum. He's not selling a hardware roadmap; he's thinking about what it actually takes to get a large, complex organization to change its cryptographic infrastructure before a threat materializes.

    The conversation matters now because the signals are accelerating. NIST has finalized its first post-quantum cryptography standards, executive orders in the US are pushing federal agencies toward PQC migration, and the algorithmic efficiency gains that reduce the qubit threshold for breaking RSA-2048 keep coming. Listeners who work in enterprise technology, cybersecurity, or quantum strategy — or who advise organizations that do — will find Entrup's practitioner perspective a useful counterweight to the more hardware-focused conversations that dominate the field.

    What We Get Into

    • Why Q-Day's exact date is the wrong question — and why the more important issue is how long it will take enterprises to even inventory their cryptographic exposure, let alone remediate it
    • The scale of the cryptographic migration problem, including why a single laptop may contain hundreds of individual cryptographic components and why upstream/downstream API dependencies make this a supply-chain-wide challenge, not just an internal IT project
    • Why "harvest now, decrypt later" creates urgency today, regardless of when fault-tolerant quantum computers arrive — and how compliance and regulatory timelines interact with that threat model
    • What crypto agility actually means in practice — moving from a "set it and forget it" cryptographic posture to a dynamic, continuously monitored framework, including the pressure SSL certificate renewal windows are already creating
    • How KPMG built its PQC practice, incubated it within the firm, and handed it off to the cybersecurity advisory team as a core service offering
    • The "good quantum" side of the ledger — how KPMG's emerging research function is approaching quantum computing as a source of competitive advantage, not just risk, and what sectors are furthest along in exploring it
    • The AI-quantum convergence, including Entrup's observation that AI is already being used to read and crack code — and what that means for the urgency of cryptographic modernization
    • Why the enterprise quantum opportunity still has a long tail, and how the current moment compares to the early infrastructure phase of the internet — when everyone was talking about TCP/IP and DNS, not Uber or Netflix

    Resources & Links

    Guest & Organization

    Reports & Research

    Ecosystem & Events

    Independent Coverage

    Key Quotes & Insights

    > "It's not if but when. And it could be five years, could be three years, could be ten years. The fact is organizations are not gonna be ready. And that's the scary part." — Richard Entrup on Q-Day

    > "This is not just the CISO. This is gonna be the software engineering app dev guys. This is gonna be all your partners, upstream and downstream, who have to also be compliant — because if you change your crypto and they don't, that stuff's gonna break." — On why PQC migration is an enterprise-wide, supply-chain-wide problem

    Insight: Entrup draws a sharp distinction between the "bad quantum" (cryptographic risk requiring urgent defensive action) and the "good quantum" (competitive opportunity with a longer tail) — and argues that most organizations aren't adequately addressing either.

    Insight: The analogy to the early internet is deliberate: just as the 1990s were consumed with TCP/IP and DNS rather than the applications those protocols would eventually enable, the current quantum moment is still largely an infrastructure conversation — and that's normal, not a sign of failure.

    > "AI is expediting all of this. If AI is doing one thing, the use case is reading code and cracking it. That's pretty scary." — On the intersection of AI capability and cryptographic vulnerability

    Related Episodes

  13. Silicon Spin Qubits and the IBM–HRL Acquisition with Thaddeus D. Ladd

    44 Min.Folge 106

    Mit Thaddeus D. Ladd

    Thaddeus Ladd has spent seventeen years at HRL as the theoretical anchor of its silicon spin qubit program — co-authoring the 2023 Nature paper that demonstrated universal logic with encoded spin qubits, and …

    Shownotes

    Thaddeus Ladd has spent seventeen years at HRL as the theoretical anchor of its silicon spin qubit program — co-authoring the 2023 Nature paper that demonstrated universal logic with encoded spin qubits, and contributing to the 2026 QPU paper that integrated qubits, a cryo-CMOS controller, and a new superconducting ribbon cable into a single digitally controlled system. He is not a commentator on this acquisition; he is one of the people whose work made it happen.

    The conversation is recorded eleven days after IBM announced a definitive agreement to acquire HRL from Boeing and General Motors — a deal that has not yet closed. That timing makes this one of the few technically grounded, insider-adjacent conversations available about what IBM is actually buying, why the exchange-only spin qubit architecture is strategically distinctive, and what the combination of HRL's research culture with IBM's fabrication ambitions could produce. Listeners who follow quantum hardware, quantum computing strategy, or the evolution of industrial research labs will find this episode unusually substantive.

    What We Get Into

    • Why the 2026 QPU paper is a systems story, not just a fidelity story — the qubit chip, the cryo-CMOS controller operating at four Kelvin, and the new superconducting ribbon cable are all part of one integrated QPU, and that framing is central to understanding what IBM acquired.
    • What "exchange-only" actually means — why using only voltage-controlled exchange interactions (no microwaves, no local oscillators, no phase tracking during idle) is both a technical constraint and a significant engineering advantage for scaling.
    • Why the jump from six dots to fifty-four dots happened so fast — and what was happening in HRL's fabrication program that wasn't being published.
    • What EUV lithography has to do with spin qubit scaling — and why the connection between HRL's process and IBM's Anderon 300 mm quantum foundry is one of the clearest pieces of strategic logic in the acquisition announcement.
    • How HRL's cryo-CMOS work could benefit IBM's superconducting program — and why the control-and-interconnect bottleneck is a shared problem across modalities, not a spin-qubit-specific one.
    • The "chandelier" reframe — Thaddeus's argument that the cables, filters, and control electronics surrounding a superconducting qubit chip are not overhead; they are part of the QPU, and understanding that changes how you read the HRL acquisition.
    • Which modality Thaddeus thinks will reach commercially useful scale first — and why he still believes spin qubits are the long-term answer, using an analogy to vacuum tubes and silicon microprocessors that is worth hearing in full.
    • What the acquisition means for HRL as an institution — the context of lost program funding, the December 2025 Q2B meeting, and what it means for a defense-oriented industrial research lab to find a commercial path through IBM.

    Resources & Links

    Guest

    Papers & Articles

    Acquisition & IBM Strategy

    Tools & Platforms

    Organizations

    • <...

  14. Quantum in the Big Four with Aaron Kemp

    44 Min.Folge 105

    Mit Aaron Kemp

    Aaron Kemp sits at an unusual intersection. He holds a doctorate in cybersecurity, spent years in DoD classified environments running SCI and SAP facilities, and now leads KPMG's quantum research practice — …

    Shownotes

    Aaron Kemp sits at an unusual intersection. He holds a doctorate in cybersecurity, spent years in DoD classified environments running SCI and SAP facilities, and now leads KPMG's quantum research practice — where he's a co-author on a recent hybrid QML paper with Kipu Quantum and IBM. He's also the lead author of KPMG's Q-PREP framework, which pushes enterprises to treat post-quantum cryptography migration as an operational risk problem right now.

    If you've wondered how quantum actually lands inside a Fortune 200 boardroom — not the hype cycle version, but the "what do you actually tell the CFO" version — this episode maps that territory honestly. It's also useful listening if you're trying to understand the emerging talent gap, why the quiet in enterprise research publications may itself be a signal, and how a firm known for audit and advisory ends up doing multispectral analysis of chestnut trees on IBM quantum processors.

    What We Get Into

    • Why KPMG split quantum into distinct practices — PQC, sensing, optimization, and research — and what that structural choice signals about market timing
    • How a PBS documentary about the American chestnut tree led to a peer-reviewed quantum ML paper with Kipu Quantum and IBM
    • The honest case for a 3% accuracy gain over classical ResNet-50 baselines — and why Aaron treats it as a positive-sum signal rather than a victory lap
    • Why "what makes a good quantum problem" remains the most important question in the field, and how KPMG's client base shapes their answer
    • The seven-step Q-PREP framework for post-quantum cryptography readiness, and why step one — knowing what you actually have — is the hardest step
    • How data-centric thinking (not cryptography-centric thinking) reframes the PQC migration challenge
    • Why the quiet in enterprise research publications from major financial institutions may itself be a market signal
    • The talent bottleneck: ~16,500 quantum researchers on the planet against a coming wave of enterprise demand
    • How AI tooling is compressing quantum research timelines, and what that means for who can enter the field
    • Why the compute stack of the next decade will be heterogeneous — quantum, neuromorphic, thermodynamic, and mechanical computing all coexisting

    Resources & Links

    Guest & Organization

    Papers & Research

    PQC & Enterprise Frameworks

    Related Coverage & Commentary

    Key Quotes & Insights

    • On the 3% accuracy gain: "It's a positive game… we did a 12–15 week sprint, and to at least meet classical was our goal when we started. So when we actually did get three percent, it was repeatable. That was, to me, okay — there's something there."
    • On the real PQC problem: "We don't have a cryptographic problem. We have a data problem. None of these organizations know where their data flows."
    • On cybersecurity as a discipline: "Cybersecurity is probably the worst career field ever because perfect cybersecurity has no ROI — because nothing happens."
    • On enterprise timing: Insight: Aaron frames the quiet in financial services quantum research publications as a market signal — organizations may have stopped sharing because they're moving from research toward competitive advantage.
    • On the talent gap: "There's 16,500 quantum researchers on the planet… Fortune 200 will hire 16,000." A single tier of enterprise demand could exhaust the global talent pool.

    Related Episodes

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  15. Investing in the Quantum Frontier and the Road to Fault Tolerance with Barak Bussel

    40 Min.Folge 104

    Mit Barak Bussel

    Barak Bussel is one of the few people operating simultaneously at three levels of the quantum stack: deploying private capital into hardware and software companies through 7i Capital, chairing the strategic …

    Shownotes

    Barak Bussel is one of the few people operating simultaneously at three levels of the quantum stack: deploying private capital into hardware and software companies through 7i Capital, chairing the strategic board of a major university quantum center, and helping stand up the physical infrastructure — a 700,000 square foot research park on the site of the former Westside Pavilion — meant to convene academia, industry, national labs, and startups in one place. He is also a physicist by training, which changes the kind of diligence questions he asks.

    We recorded this at the KPMG Tech and Innovation Symposium in Deer Valley, only weeks after the most consequential stretch of quantum news in years: Oratomic's $300M Series A (the largest first institutional round in quantum history, with 7i in the syndicate), a Google Quantum AI paper cutting Shor's algorithm resource estimates to around 500,000 physical qubits on superconducting hardware, and two June 2026 White House executive orders on quantum innovation and post-quantum cryptography. If you want to understand how a serious investor is actually pricing risk, timelines, and ecosystem-building in this moment, this is the conversation.

    What We Get Into

    • Why 7i backed Oratomic's aggressive "no intermediate product, straight to fault tolerance" strategy, and how Barak thinks about betting on teams versus theses in deep tech
    • How recent architecture and QLDPC error correction advances have compressed physical-to-logical qubit ratios, and what that means for near-term resource estimates for Shor's algorithm
    • Why a lesser-noticed April 2026 Google Quantum AI paper on quantum-assisted memory reduction for classical AI workloads may matter as much as the Shor's-focused headlines
    • What "patient capital" actually looks like when a connector problem eats two years of a portfolio company's roadmap
    • The Bell Labs template as a serious operating model for the UCLA Research Park: convening academia, industry, government, and startups in a single physical footprint
    • The historical resonance of UCLA sending the first ARPANET packet in 1969 and what that suggests about where quantum networking work should be anchored
    • How Kedma's error mitigation work with IBM's Heron II and RIKEN pushed a 51-qubit Ising model simulation to the edge of what's classically tractable
    • How Barak reads the June 2026 executive orders and the federal role — enabling infrastructure rather than picking winners — against the scale of Chinese government funding

    Resources & Links

    Guest & Organizations

    The Oratomic Round and Recent Breakthroughs

    Policy and Market Context

    UCLA Research Park and Regional Ecosystem

    Key Quotes & Insights

    • On patient capital in hardware: "You're producing a new chip… all of a sudden a year and a half has passed." Barak's example of a photonics company that spent two years solving a flex connector problem is a useful ground truth for anyone modeling quantum hardware timelines.
    • On the role of universities: Industry has scale — the ability to throw 500 engineers at a problem. Academia brings "the quiet depth to think very deeply about a problem over an extended period of time, two or three generations ahead."
    • On resource estimates: The gap between the original 20-million-qubit Shor's estimates and the recent Google Quantum AI paper suggesting ~500,000 physical qubits on superconducting hardware, plus Oratomic's neutral-atom approach at the ten-thousand-qubit scale, represents a genuine compression of the fault-tolerance horizon.
    • On the underappreciated Google paper: An April 8 paper on using quantum processors to reduce memory requirements for massive classical data sets is, in Barak's view, the first rigorous demonstration that quantum could bend the exponential curve of AI compute demand.
    • On government's role: "Typically in the U.S., government is not the best at picking the winners and losers in the marketplace. But it's great at enabling." The El Segund...

  16. Building the U.S. Quantum Supply Chain with Kate Timmerman

    42 Min.Folge 103

    Mit Kate Timmerman

    Kate Timmerman is the CEO of the Chicago Quantum Exchange (CQE), and she is arguably one of the most consequential ecosystem builders in quantum today. Under her leadership, the CQE has grown from three …

    Shownotes

    Kate Timmerman is the CEO of the Chicago Quantum Exchange (CQE), and she is arguably one of the most consequential ecosystem builders in quantum today. Under her leadership, the CQE has grown from three founding institutions in 2017 to a coalition of more than 50 industry and academic partners, and the region has secured designation as a top global quantum ecosystem through The Bloch Quantum U.S. EDA Tech Hub and an NSF Regional Innovation Engine development award.

    If you care about how emerging deep-tech industries actually get built — the unglamorous work of coordinating universities, startups, national labs, small manufacturers, workforce agencies, and federal policy — this episode is a masterclass. It's especially valuable for listeners trying to understand how quantum moves from bespoke, hand-built prototypes to real industrial-scale production, and what that transition means for jobs, national security, and U.S. competitiveness.

    What We Get Into

    • Why the CQE started 18 months before the National Quantum Initiative Act — and how that head start translated into winning multiple NQI research centers (SQMS, Q-NEXT, HQAN, and Q-NEXT-adjacent efforts)
    • What the $55M Bloch Tech Hub award actually funds in the next 12 months, and why the money targets manufacturing rather than more research
    • The severity of U.S. dependence on foreign and single-sourced quantum components — from nano-positioners to optics, photonics, and vacuum systems — and why that's slowing product delivery today
    • How small and mid-sized Midwest manufacturers (in states that already rank top-10 in U.S. manufacturing) can pivot into the quantum supply chain without full re-tooling
    • Why the BCG projection of ~$80B in regional economic impact and up to 191,000 quantum jobs by 2035 is more credible when you understand the full supply-chain vision, not just quantum computer vendors
    • The five pillars of the CQE's NSF-backed "Advancing Together" workforce strategy — awareness, preparation, mobility, employer leadership, and coordination — and why employers themselves often can't forecast their own hiring needs
    • What the Quantum Law Navigator™ is actually for, who uses it, and why first-time quantum founders often don't know what "export control" means until it's too late
    • Why Q2B is relocating its North America conference from Silicon Valley to Chicago in December 2026 — and what that signals about where the center of gravity is moving

    Resources & Links

    Guest & Organization

    The Bloch Quantum Tech Hub ($55M EDA Award)

    Workforce & Economic Development

    Programs & Tools Mentioned

    Key Quotes & Insights

    • On the 18-month head start: "When we hear an anecdote once or twice, we realize, if we're hearing it once or twice today, that means in two years the U.S. government's gonna hear about it." Kate's argument for why nimble ecosystem organizations have to move before the market signal is obvious.
    • On the supply chain problem: A significant portion of quantum components today are single-sourced and imported. That fragility, Kate argues, is quietly slowing every quantum company's ability to deliver products to customers — and it's the specific gap the Bloch award is designed to close.
    • On the manufacturing pivot: The Midwest already has top-10 manufacturing states, but those small and mid-sized shops "tend to be more mom and pop type shops, and they don't have R&D budgets" to speculatively re-tool for quantum. Federal implementation funding is the mechanism to bridge that gap.
    • On workforce reality: Employers "are so mission-focused on their tech development, they're not doing their own forecasts about what their jobs needs are gonna be in two and five years." Ecosystem organizations have to do that forecasting on behalf of the industry.
    • On what universities quietly subsidize: "The universities end up doing a lot of stuff for free… a lot of the preparing for the future that is not maybe of incredible priority at the moment, but that fundamental work, yes, on the research side, but also on the workforce development side, is incredibly important."

    Related Episodes

  17. The Open Source Substrate for Quantum with Ben Castanon

    44 Min.Folge 102

    Mit Ben Castanon

    Ben Castanon became Unitary Foundation's first CEO in February 2026, after roughly four years with the organization as Chief of Staff and then COO. He came into quantum from an unusual direction — leadership …

    Shownotes

    Ben Castanon became Unitary Foundation's first CEO in February 2026, after roughly four years with the organization as Chief of Staff and then COO. He came into quantum from an unusual direction — leadership roles at Pioneer Works, the Brooklyn arts-and-science center — and that background shows in how he thinks about scaffolding communities, funding public goods, and borrowing what works from other fields.

    This conversation matters now because Unitary Foundation sits at an inflection point. It has scaled from a microgrant program (the "Unitary Fund") into a foundation with a global developer community, corporate members including NVIDIA and IBM, an active compiler collection, a benchmarking initiative, and an annual open-source survey that increasingly serves as the field's ground truth. If you care about how quantum computing actually gets built — not just who wins the hardware race — this episode lays out the infrastructure argument clearly.

    What You'll Learn

    • Why Ben argues quantum open source falls into a structural funding gap between academia (chasing novel papers) and venture capital (chasing profitable businesses), and what philanthropy has to do about it
    • What "public goods" and "digital commons" actually look like in quantum — from benchmarking to compilation to error mitigation tooling
    • How to interpret the 2025 QOSS Survey finding that ~40% of full-time quantum OSS contributors are unpaid, and why Ben sees it as both an opportunity and a warning
    • How Unitary Foundation is experimenting with continuous compensation for contributors via bounty programs and pilots with Merit Systems
    • Why corporate members like NVIDIA and IBM invest in a vendor-neutral nonprofit — and how governance keeps the "open" in open source
    • What a healthy pipeline from first-time contributor to sustained open-source maintainer would look like, and why Ben wants an endowment behind it
    • Why Ben resists top-down definitions of the "open substrate" and prefers to let the community surface bottlenecks
    • The long-term vision: a "Linux moment" for quantum, and what it would take to install it before proprietary stacks lock in

    Resources & Links

    Guest & Organization

    Papers & Reports

    Tools & Programs

    • Unitary Compiler Collection (UCC) — The frontend-agnostic quantum compiler collection Ben references as a candidate for the open substrate.
    • UCC on GitHub — The active repo, supporting Qiskit, Cirq, PyTKET, and OpenQASM 2/3.
    • unitaryHACK 2026 — The sixth annual bug-bounty hackathon, one of UF's core mechanisms for compensating open-source contributors.

    Ecosystem

    Key Quotes & Insights

    • On the structural gap: There are "third spaces" where projects don't fit the incentives of either a startup or an academic lab — but where the whole ecosystem benefits. Benchmarking is the clearest example.
    • On unpaid contributors: "We've developed the field to a place where we're starting to hit up against the classic open source community issues." The volunteer surge is real — but so is the risk of losing those contributors to better-paying fields if UF can't convert enthusiasm into compensation.
    • On why big companies join: A functional field needs people to hire. Ben's argument to corporate members is partly workforce development — thousands of developers getting on-the-job training on neutral, community-owned tools.
    • On the substrate: Ben resists top-down definitions of what belongs in the open substrate. "It's much better to have all of the practitioners giving voice to what open tools they need."
    • On his long-term ambition: Build a philanthropic endowment that funds the microgrant pipeline in perpetuity — because "I don't see that as ever becoming a resource that is not of use."

    Related Episodes

    Stay in the Ecosystem

    ...

  18. Quantum Cameras and Sub-Diffraction Imaging with Johannes Galatsanos

    49 Min.Folge 101

    Mit Johannes Galatsanos

    Johannes Galatsanos occupies an unusual dual perch in the quantum ecosystem. As a co-author of the inaugural MIT Quantum Index Report, he's helped map the entire quantum landscape at altitude; as co-founder and …

    Shownotes

    Johannes Galatsanos occupies an unusual dual perch in the quantum ecosystem. As a co-author of the inaugural MIT Quantum Index Report, he's helped map the entire quantum landscape at altitude; as co-founder and CEO of Diffraqtion, he's staked his career on one of its most under-discussed corners: quantum imaging. The company spun out of Saikat Guha's lab at the University of Maryland after more than a decade of DARPA-funded research, emerged from stealth in January 2026 with $4.2M in pre-seed funding, and is now racing toward on-sky telescope demonstrations and a 2028 satellite launch.

    This episode is for listeners who want a technically honest look at where the "quantum" label is doing real work in a sensor versus where it's shading into sophisticated photonics and analog computing. If you care about how quantum technologies actually reach the world — through markets, contracts, and hardware that ships — this conversation gives you a specific, concrete example to think with.

    What You'll Learn

    • Why a conventional camera can lose roughly 95% of the information a photon carries, and what quantum Fisher information theory says about recovering it
    • How Diffraqtion's device processes light directly in the photonic domain before converting it to electronic information — and why that matters for shot noise
    • The honest answer to "is this really quantum?" — including where the technology sits between quantum information theory, photonics, and analog computing
    • Why a 6U CubeSat with a 10-centimeter aperture can plausibly compete with school-bus-sized observation satellites for specific tasks
    • How a "diffractive neural network" runs image classification at the speed of light with negligible power consumption
    • The difference between Diffraqtion's hard-coded Gen 1 camera and the reprogrammable Gen 2 that can swap algorithms in orbit (canopy detection over the Amazon, ship detection over the Atlantic)
    • Why the Habitable Worlds Observatory needs a coronagraph capability — and how you can build one by processing light rather than blocking it
    • What quantum sensing needs from policy, capital, and PR to escape the shadow of quantum computing

    Resources & Links

    Guest & Company

    • Diffraqtion — Company homepage; describes the technology, NASA/DARPA lineage, and the "quantum eye" framing referenced in the conversation.
    • Johannes Galatsanos on LinkedIn — Recent activity including SmallSat Europe, the NASA Space to Soil Challenge, and GQIG Summit talks on quantum imaging.

    Papers & Reports

    Press & Coverage

    Sponsor

    Key Quotes & Insights

    • On quantum information loss: "When you do a direct image… you lose something like 95% of information from that photon. So you leave 95% on the table, and the question was: how do you extract that back?"
    • On what "quantum" really means here: Galatsanos is refreshingly candid — the device uses quantum Fisher information theory to set the physical limit and configure the hardware, but the runtime processing is closer to analog photonic computing than to gate-based quantum computing. He describes it as sitting between "quantum 1.0" and quantum sensing.
    • On the frog's-eye analogy: Retinal ganglion cells can process shapes and trajectories faster than the brain — which is why you can catch a baseball or a falling fork before you consciously see it. Diffraqtion is trying to give satellites and robots the same kind of reflex.
    • On the JPEG as a historical artifact: "JPEG was a little bit of a logical step… but now the thought is, forget about it — you don't even need that. The light itself already will tell you." The machine, unlike a human operator, doesn't need an image.
    • On why quantum sensing lags in the discourse: Insight — quantum computing benefits from a single unifying narrative that every vendor can pull on. Quantum sensing has to invent its own story from scratch for each modality, which is a structural PR disadvantage more than a technical one.

    Related Episodes

  19. Episode 100: Live at Barnes & Thornburg — Reflections on the First 100 Episodes

    1 Std. 20 Min.Folge 100

    This is the 100th episode of The New Quantum Era, and it arrives at a moment of convergence: the book is out, the Helgoland centennial documentary is in production, regional quantum ecosystems are scaling from …

    Shownotes

    This is the 100th episode of The New Quantum Era, and it arrives at a moment of convergence: the book is out, the Helgoland centennial documentary is in production, regional quantum ecosystems are scaling from ambition to construction, and the field is entering the transition from heroic-era qubit demos to the hard systems engineering that will determine whether quantum computing becomes a real industry. Bob Karr — who sits at the intersection of law, policy, and the quantum ecosystem as the person behind the Quantum Law Navigator and a convener across the Chicago quantum community — is the right person to conduct this retrospective, and Barnes & Thornburg, at the center of arguably the most sophisticated quantum ecosystem in the world, is the right place to do it.

    The conversation is structured as a celebration and an examination: what has Sebastian actually learned by sitting with nearly 100 physicists, engineers, founders, and policymakers? How has the field changed since that first visit to TJ Watson in 2017? What do regional hubs like the Illinois Quantum and Microelectronics Park and Quebec's DistriQ tell us about what it takes to move from science to industry? And what does the next era demand — not just from researchers and companies, but from everyone?

    ---

    What You'll Learn

    • Why the Helgoland documentary matters: in June 2025, Sebastian and his wife traveled to the island where Heisenberg's 1925 insight gave birth to quantum mechanics, producing a documentary at a Yale–Max Planck centennial conference attended by multiple Nobel laureates — and what that experience distilled about the state of the field
    • How Sebastian's journey into quantum began: arriving at IBM's TJ Watson Research Center in 2017 to help with Qiskit's open source strategy, encountering the 53-qubit milestone, and recognizing the earliest stages of an emerging technology that would become his life's work
    • What the "Heroic Age of Qubits" was — and why it ended: the period of genius PIs racing to prove quantum advantage, culminating in Google's 2019 random circuit sampling claim, and why that finish line turned out to be a starting line
    • What Harley Johnson and the IQMP reveal about ecosystem-building: why the Illinois Quantum and Microelectronics Park is the world's leading example of building a quantum ecosystem, and what it takes to bridge deep science and economic development
    • What Quebec's DistriQ teaches about sustainability: the 90% public / 10% private funding model designed to flip over ten years, and why that benchmark matters for every regional hub
    • Why Alejandra Castillo's economic development lens changed the picture: how quantum's impact extends far beyond qubits into advanced manufacturing, supply chain, and the communities that get to participate in the upside
    • What Nadya Mason's leadership model means for the field: the dean of UChicago's Pritzker School who wasn't a "math person" and sees leadership as service — and why the field needs every kind of creative mind, not just PhDs in physics
    • What John Martinis's arc from the 1986 Josephson junction paper through the Nobel Prize to CoLab reveals: the transition from heroic-era physicist to systems thinker pursuing open architecture and consortium-based quantum computing
    • Why the Monte Carlo algorithm is the key analogy for quantum's future: the technique that took 30 years to find its commercial application as a reminder that the most important uses of quantum computers haven't been imagined yet
    • Where fault tolerance actually stands: why it's an emergent property of the whole system — not a single breakthrough — and why the classical-quantum feedback loop for mid-circuit measurement and syndrome correction is the thing to watch
    • Why multiple qubit modalities will coexist: the case for neutral atoms in the near term, superconducting and spin qubits in the long term, and photonics as a dark horse — and why this isn't a winner-take-all race
    • What Build Quantum Partners is building: a new venture to reduce friction for quantum companies entering the U.S. market, partner with regional ecosystems, and ultimately develop the quantum equivalent of biotech hub infrastructure

    ---

    Resources & Links

    Guest & Host Links

    The Book & Documentary

    • The New Quantum Era by Sebastian Hassinger — Released May 2026; the companion book tracing the people, science, and engineering behind quantum technology's emergence
    • Helgoland Documentary — In production; shot over five days at the Yale–Max Planck centennial conference on the island where Heisenberg formulated matrix mechanics in 1925

    Episodes & Guests Referenced

    Key Institutions & Ecosystem

  20. Quantum EDA for Ion Trap Design with Daniel Faircloth

    39 Min.Folge 99

    Mit Daniel Faircloth

    Daniel Faircloth, PhD is an unusual figure in the quantum ecosystem: a computational electromagnetics engineer who actually helped build trapped-ion hardware before pivoting to the software stack the field was …

    Shownotes

    Daniel Faircloth, PhD is an unusual figure in the quantum ecosystem: a computational electromagnetics engineer who actually helped build trapped-ion hardware before pivoting to the software stack the field was missing. He's a co-author on the 2013 New Journal of Physics paper that demonstrated reliable ion transport through a microfabricated X-junction surface-electrode trap at Georgia Tech Research Institute, and he spent the years afterward inside a defense contractor, IERUS Technologies, building the electromagnetic simulation engine that has now spun out as Nullspace.

    If you've been following the trapped-ion race — Quantinuum, IonQ, Oxford Ionics, AQT, and the academic groups feeding them — this episode fills in a layer of the story that rarely gets airtime. As the field moves from clever physics demonstrations toward genuinely scaled architectures, the design tools, the file formats, and the iteration loops start to matter as much as the qubits themselves. Listeners interested in quantum engineering, the analog of EDA in semiconductors, or how dual-use defense R&D translates into commercial quantum infrastructure will find a lot to chew on.

    What We Get Into

    • Why the standard "gapless approximation" for ion trap modeling — treating electrodes as polygons on an infinite metal sheet — breaks down well before you're ready to fabricate.
    • How Faircloth's graduate-school question ("can better tools turn a good engineer into a super engineer?") became the design philosophy behind Nullspace ES.
    • What turning an X-junction corner actually requires: two-stage optimization across trap geometry and control voltages, so the ion doesn't get heated out of the trap.
    • Why general-purpose electrostatic solvers struggle with ion trap problems that demand nanometer ion-height precision and millivolt-level shuttling voltage accuracy.
    • The technical leap in Nullspace ES 2025 R1: pairing high-order basis functions with a compression solver to cut memory usage roughly 5× while preserving accuracy.
    • The awkward commercial reality of selling neutral simulation infrastructure to companies that are direct competitors with each other.
    • The "build vs. buy" tension for hardware startups deciding whether to roll their own solver in Python or adopt a purpose-built commercial tool.
    • How the dual-use defense / commercial-quantum positioning shapes Nullspace's roadmap — and where lessons flow in both directions.
    • Where the roadmap might lead: multi-physics, tightly integrated workflows that eliminate the CAD-cleanup and file-format-exchange tax engineers pay today.

    Resources & Links

    Guest & Company

    Product & Technical Resources

    Papers & Background Reading

    Company & Funding Context

    Key Quotes & Insights

    • On the original product question (paraphrase): If you give powerful EM and optimization tools to a well-trained engineer, can you effectively turn them into a "super engineer" and unlock the kind of creativity that textbook parameterizations can't reach? That question became the through-line from Daniel's graduate work to Nullspace.
    • On why existing tools fall short (paraphrase): The community was trying to shoehorn ion trap design into solvers that were never built for it — gapless approximations, weak optimizers, and accuracy levels that simply don't hold up when you need nanometer ion heights and millivolt shuttling voltages.
    • On corner-turning in an X-junction (Daniel, lightly edited): "If you think of an ion trap as a fancy train track system, the ions are being shuttled around — you need to be able to turn left and turn right as you grow and scale. How do you get the ion to turn but not get heated in that process and lose the ion?"
    • On serving competing customers (paraphrase): A rising tide floats all boats. The better the underlying simulation tools, the more sophisticated the architectures every team can attempt — and the more chances the field has of someone breaking through.
    • On the long-term vision (Daniel): "Being able to provide all of that in an appropriate fidelity, one-stop shop for the designers. I don't want them to have to go to a bunch of different tools and try to kind of piece together dealing with file format exchange issues."

    Related Episodes

  21. Electrons on Superfluid Helium with Nick Farina

    42 Min.Folge 98

    Mit Nick Farina

    EeroQ is unusual in two ways. It's the only company in the world commercializing electrons-on-helium qubits, a modality first proposed by Platzman and Dykman in Science in 1999. And it was founded by Nick …

    Shownotes

    EeroQ is unusual in two ways. It's the only company in the world commercializing electrons-on-helium qubits, a modality first proposed by Platzman and Dykman in Science in 1999. And it was founded by Nick Farina — a software entrepreneur, not a physicist — who got pulled into the field through a Chicago theater board where he met his future co-founder, then-PhD student Johannes Pollanen.

    This conversation matters now because EeroQ has had an unusually productive twelve months: a Physical Review X paper demonstrating single-electron control above 1 Kelvin, a January 2026 result on controlling up to a million electrons with fewer than 50 control lines, and — published in Nature Physics on June 15, 2026 — the first demonstration of strong coupling between a microwave photon and a single electron on helium, the cavity-QED readout-and-control link the platform depends on. If you're trying to understand which "second-tier" modalities deserve serious attention — and how a small, capital-light team in Chicago is thinking about scale-first hardware design — this is a useful listen.

    Sponsor

    This episode is brought to you by Outshift, Cisco's incubation engine. The need for computational power is rapidly increasing in every sector. From drug discovery to material innovation to complex financial modeling, classical systems are reaching their absolute limits. It's time for a paradigm shift. The answer is a scalable quantum network, built on open standards and vendor-agnostic architecture. By uniting distributed quantum devices, you unlock limitless computational power.

    Learn more about the Cisco Universal Quantum Switch at Outshift.com.

    Go deeper with the blog post The switch that quantum networking has been waiting for.

    What We Get Into

    • How a Chicago theater board led to one of the most unique qubit companies in the field
    • Why electrons-on-helium failed in the early 2000s and why circuit QED, dry fridges, and CMOS now make it viable
    • The physical picture: a thin superfluid helium film coating a CMOS chip, with electrons trapped a few nanometers above the surface by their own image charge
    • Why EeroQ pivoted from motional states to spin qubits after Steve Lyon (Princeton) joined as CTO — and the predicted 10+ second coherence times that come with it
    • The "build a quantum computer in reverse" philosophy: starting from a million-qubit architecture and working back toward two-qubit gates
    • How the "Wonder Lake" chip controls 2,432 future qubit sites today, and why that's an engineering milestone rather than a qubit count
    • Honest framing of where EeroQ actually is: no two-qubit gate demonstrated yet, with a tape-out target of ~10,000 qubits by late 2028
    • Why dipole-dipole gates come first and exchange gates come later, borrowing from the spin qubit playbook
    • The case that scaling — not qubit quality — has been the field's slowest-moving problem over the last decade

    Resources & Links

    Guest & Company

    Key Papers

    Press & Context

    Ecosystem

    Key Quotes & Insights

    • On the contrarian thesis: "Scaling is actually the hardest part of building a quantum computer." Nick argues the field has made real strides on gate fidelity, error correction, and algorithms over the last decade — but not nearly enough on the path to hundreds of thousands or millions of qubits.
    • On building in reverse: Rather than starting from a two-qubit gate and "hoping and praying to find ways to scale," EeroQ started by asking what a million-qubit processor would have to look like — which forced the choice of CMOS as the only manufacturing technology humanity has ever used to build features at that scale.
    • On honest status: "We d...

  22. Quantum Drug Discovery and the Path to Advantage with Sabrina Maniscalco

    45 Min.Folge 97

    Mit Sabrina Maniscalco

    Why This Episode MattersSabrina Maniscalco is one of the few people in quantum who has lived the full arc: two decades of academic work on open quantum systems and non-Markovian noise at Palermo, Turku …

    Shownotes

    Why This Episode Matters

    Sabrina Maniscalco is one of the few people in quantum who has lived the full arc: two decades of academic work on open quantum systems and non-Markovian noise at Palermo, Turku, Edinburgh, and Helsinki, followed by founding Algorithmiq with three of her former researchers after an early Qiskit Camp. That trajectory matters now because Algorithmiq just had a landmark stretch — sole winner of the $2M Wellcome Leap Q4Bio prize for a quantum-enabled cancer drug discovery workflow, an €18M Series B, a global HQ move to Milan, and its Tensor Network Error Mitigation (TEM) function landing in IBM's Qiskit Functions catalog.

    If you're trying to make sense of where quantum software actually creates value before fault tolerance arrives — and what a credible "trajectory to advantage" looks like when paired with real clients in life sciences — this is a grounded, technically specific conversation with someone building it.


    EPISODE SPONSOR

    This episode is brought to you by Outshift, Cisco's incubation engine. The need for computational power is rapidly increasing in every sector. From drug discovery to material innovation to complex financial modeling, classical systems are reaching their absolute limits. It's time for a paradigm shift. The answer is a scalable quantum network, built on open standards and vendor-agnostic architecture. By uniting distributed quantum devices, you unlock limitless computational power.

    Learn more about the Cisco Universal Quantum Switch at Outshift.com.

    Go deeper with the blog post The switch that quantum networking has been waiting for.


    What We Get Into

    • Why a background in open quantum systems and non-Markovian noise turned out to be unusually well-suited to running algorithms on noisy near-term hardware
    • The actual science behind the Q4Bio winning workflow: simulating excited-state dynamics of a photosensitizer drug already in Phase II clinical trials, on up to 100 qubits
    • How quantum-boosted DMRG works — and why it gives you a built-in benchmark against the best classical method via the bond dimension
    • The tradeoff Sabrina would and wouldn't make between more qubits and lower noise, and why neutral atoms' slower sampling rates matter for chemistry
    • Why even fault-tolerant algorithms like quantum phase estimation still depend on getting state initialization and measurement right
    • Algorithmiq's two-product structure: the Digital Quantum Interface (hardware-agnostic infrastructure) and the life sciences application framework
    • How methods built for chemistry are now opening doors into optimization and GenAI — and why that direction emerged from the work, not from a strategy deck
    • What the move from Helsinki to Milan signals about the European quantum ecosystem and Algorithmiq's commercial scale-up
    • How an active learning pipeline is already proposing novel drug variants for synthesis in Prof. Sherri McFarland's lab

    Resources & Links

    Guest & Company

    The Q4Bio Win

    Funding & HQ Move

    Quantum Advantage & Tooling

    Key Quotes & Insights

    • On the foundation of the company's approach: "We learned very early what we thought were the bottlenecks of quantum computers — what you really need to worry about if you want to implement computation at scale." A direct line from Qiskit Camp Vermont to Algorithmiq's product strategy.
    • On Q4Bio, in Sabrina's words: "This molecule is already in Phase II clinical trial. So it's not hydrogen. It's a real molecule." A useful counter to the common critique that quantum chemistry demos still live in toy-model land.
    • On quantum-boosted DMRG (insight): In the worst case, the method matches the best classical technique; in the better case, it outperforms it — and the bond dimension tells you which regime you're in. Built-in benchmarking against the classical baseline.
    • On the hardware tradeoff: Asked whether she'd prefer 100 higher-fidelity qubits or 200 noisier ones, Sabrina's answer is "it depends" — and the explanation about why neutral atoms' lower sampling rates limit chemistry use cases is one of the more concrete things you'll hear on platform tradeoffs.
    • On strategy (insight): New verticals at Algorithmiq are ...

  23. Funding the Quantum Middle: Series A/B Capital with Kris Naudts and Zeynep Koruturk of Firgun Ventures

    46 Min.Folge 96

    Mit Kris Naudts und Zeynep Koruturk

    Why This Episode MattersFirgun Ventures launched in late 2025 with a $70M first close anchored by the Qatar Investment Authority and a mandate that doesn't exist anywhere else in the market: lead Series A and B …

    Shownotes

    Why This Episode Matters

    Firgun Ventures launched in late 2025 with a $70M first close anchored by the Qatar Investment Authority and a mandate that doesn't exist anywhere else in the market: lead Series A and B rounds in quantum scale-ups globally. Kris Naudts is a neuroscientist and former Culture Trip founder whose path to quantum runs through a near-fatal medical misdiagnosis. Zeynep Koruturk spent over a decade building the Goldman Sachs Tech Initiative and meeting more than a thousand founders. Both were early angels in what became Quantinuum.

    If you're trying to understand how quantum companies actually get financed between the lab and the IPO window — or why a specialist fund needed to exist at all — this conversation is one of the clearest views available. It's also a useful frame for founders thinking about what an informed institutional investor actually does in a round.


    Sponsor

    This episode is brought to you by Outshift, Cisco's incubation engine. The need for computational power is rapidly increasing in every sector. From drug discovery to material innovation to complex financial modeling, classical systems are reaching their absolute limits. It's time for a paradigm shift. The answer is a scalable quantum network, built on open standards and vendor-agnostic architecture. By uniting distributed quantum devices, you unlock limitless computational power.

    Learn more about the Cisco Universal Quantum Switch at Outshift.com.

    Go deeper with the blog post The switch that quantum networking has been waiting for.


    What We Get Into

    • Why Kris's ALS misdiagnosis became the conviction event that pulled him from media entrepreneurship into quantum investing
    • How Zeynep's decade at Goldman Sachs Tech Initiative shaped her pattern-matching for deep tech, and where that pattern-matching breaks down in quantum
    • The structural reason Series A/B is the real bottleneck in quantum financing — and why precede and seed capital is no longer the gap people assume it is
    • How Firgun underwrites engineering and execution risk after the scientific risk is largely retired
    • Why a quantum-specialist fund unlocks soft commitments from larger institutions that otherwise stay on the sidelines
    • The role of Firgun's "scientific co-founder" Professor Mete Atatüre and the need for sub-specialist diligence across modalities
    • How Firgun thinks about portfolio construction across silicon-spin/photonic (Photonic Inc.), silicon CMOS (Quantum Motion), and other architectures without picking a qubit winner
    • Why a truly global mandate is a feature, not a focus problem, given how concentrated quantum talent is in roughly a dozen ecosystems
    • How sovereign capital, US equity-stake announcements, and geopolitical fragmentation are starting to reshape who can invest in what
    • Why the binary "fault-tolerant or bust" framing of quantum investing misses the gradient of capability that drives near-term value

    Resources & Links

    Guest & Firm

    • Firgun Ventures — The fund's homepage, with the team and "Time to Talk Quantum" podcast featuring the founders' own framing of the market.
    • Firgun Ventures on Crunchbase — Confirms London HQ, global mandate, and Series A/B focus.

    Fund Launch & Thesis

    Portfolio Companies Mentioned

    Key Quotes & Insights

    • Kris on the conviction event: "If you're expecting to die and then you're told you're going to live, you have to rethink it yet again… You can go in the direction of enjoy every day, or you can go in the direction of let's try to do something meaningful with whatever time I have left."
    • Zeynep on the real bottleneck: Pre-seed and seed capital in quantum is no longer the gap — the A and B rounds are. Roughly 40% of companies in the space need that bridge to unlock larger institutional capital, and almost no one is set up to lead it.
    • Kris on diligence limits: No one person can underwrite the full quantum stack. Firgun pairs a "scientific co-founder" with sub-specialists for each modality, because in quantum "no propositions sound stupid" — and that's exactly the problem.
    • Zeynep on the asymmetric bet: Quantum is one of the few areas where geopolitical reality creates a floor under the downside. The West can't afford to lose, which means funding will be there long enough for the right companies to mature.
    • Kris on willing the timeline: "You cannot will it into being. The space will evolve at the pace it is set to evolve with the capital and the talent in it." A useful corrective for anyone pitching a five-year cure-for-Parkinson's roadmap.

    Related Episodes

  24. Quantum Book Launch with Yuval Boger

    55 Min.Folge 95

    Mit Yuval Boger

    Why This Episode MattersYuval has a rare profile in the quantum industry: an M.Sc. in physics from Tel Aviv University, an MBA from Kellogg, two decades as a CEO and CMO in deep tech before quantum, and now the …

    Shownotes

    Why This Episode Matters

    Yuval has a rare profile in the quantum industry: an M.Sc. in physics from Tel Aviv University, an MBA from Kellogg, two decades as a CEO and CMO in deep tech before quantum, and now the commercial lead at QuEra — the company whose neutral-atom architecture is colocated with NVIDIA H100s inside Japan's ABCI-Q supercomputer and just demonstrated 96 logical qubits from 448 physical atoms in Nature. He also hosts The Superposition Guy's Podcast and has just published Quantum Bits, a comic-book guide to quantum computing.

    This is a crossover conversation — Sebastian's book A New Quantum Era came out the same week — so the episode reads as two practitioners comparing their explanatory strategies, their reading of the modality race, and their honest forecasts for when a quantum computer becomes genuinely non-simulatable. If you want a candid look at how the commercial side of quantum thinks about hardware timelines, error-correction overhead, and the work of translating physics into procurement, this is the episode.

    Sponsor

    This episode is brought to you by Outshift, Cisco's incubation engine. The need for computational power is rapidly increasing in every sector. From drug discovery to material innovation to complex financial modeling, classical systems are reaching their absolute limits. It's time for a paradigm shift. The answer is a scalable quantum network, built on open standards and vendor-agnostic architecture. By uniting distributed quantum devices, you unlock limitless computational power.

    Learn more about the Cisco Universal Quantum Switch at Outshift.com.

    Go deeper with the blog post The switch that quantum networking has been waiting for.

    What We Get Into

    • Why Vladan Vuletić's confidence horizon for neutral atoms expanded from 5 years to 10 years in a single 18-month window — and what changed
    • The honest case for neutral atoms when wall-clock speed is the obvious weakness: parallelism, algorithmic fault tolerance, and a 2:1 physical-to-logical ratio for quantum memory
    • Why "time to solution" — not gate speed — is the metric Yuval thinks the industry should be arguing about
    • How Shor's algorithm went from requiring a million qubits to roughly 30,000, and what that compression means for cryptographically relevant timelines
    • The craft problem of explaining quantum without saying "zero and one at the same time" — and why both Yuval and Sebastian refused to use it
    • What it took to make a quantum comic funny in German (the German is perfect, the joke is not)
    • Sebastian's read on the modality race: neutral atoms short-term, superconducting mid-term, spin and photonics long-term — and Yuval's pushback
    • Why Yuval thinks Sebastian's five-year forecast for a non-simulatable machine is pessimistic
    • The shift inside QuEra from "95% science, 5% everything else" to a company that has to ship serviceable systems and uptime
    • How podcasting becomes a business development tool once the microphone is off

    Resources & Links

    Guest Links

    • The Superposition Guy's Podcast — Yuval's interview show with quantum CEOs and technical leaders across computing, sensing, and communications.
    • Quantum Bits Comics — Yuval's comic-book guide to quantum computing, including custom editions and multilingual versions.
    • QuEra Computing — The neutral-atom quantum computing company where Yuval serves as Chief Commercial Officer.
    • Yuval's published writing — Aggregated Forbes, HPCwire, and Built In bylines on quantum ROI, workforce, and commercialization.

    Papers & Articles

    Books

    Background Reading Mentioned

    Key Quotes & Insights

    • On the magic of neutral atoms: "We've got this rubidium atoms, we hold them in place using tiny lasers, they're four microns apart, we shoot lasers, and then we take a photograph and see how they're doing. It's science fiction until it isn't."
    • On the modality timeline (Yuval, paraphrasing Vladan Vuletić): Eighteen months ago Vladan was confident about neutral atoms for the next five years. Six months ago, after recent results, that confidence horizon stretched to ten.
    • On what actually matters: "Obviously what matters is time to solution and not clock speed." Yuval's core rebuttal to the standard critique that neutral-atom gates are slow.
    • On the error-correction compression: A recent Harvard result showed the physical-to-logical qubit ratio for quantum memory dropping toward roughly 2:1 — not the thousand-to-one figure that dominates most public discourse.
    • On the takeaway from his book (Yuval): "Quantum is magical, but it's not magic."

    Related Episodes

  25. Fault Tolerance for Quantum Inputs and Outputs with Matthias Christandl

    39 Min.Folge 94

    Mit Matthias Christandl

    Fault Tolerance for Quantum Inputs and Outputs with Matthias ChristandlWhy This Episode MattersMost discussions of fault tolerance quietly assume a classical-in, classical-out picture: you feed in bits, the …

    Shownotes

    Fault Tolerance for Quantum Inputs and Outputs with Matthias Christandl

    Why This Episode Matters

    Most discussions of fault tolerance quietly assume a classical-in, classical-out picture: you feed in bits, the noisy quantum machine does its work, and a stable classical answer comes out the other side. Christandl — a mathematically trained quantum information theorist who also leads a Novo Nordisk Foundation–funded life sciences center — argues that this framing is too narrow for the era we are actually entering, where multi-core processors, networked QPUs, and quantum communication links all need to exchange quantum information between noisy machines.

    If you care about how quantum networks, distributed quantum computers, and quantum simulation workflows for chemistry and biology actually get built, this episode lays out a foundational way of thinking about the problem and connects it directly to current hardware and algorithm co-design.

    Sponsor

    This episode is brought to you by Outshift, Cisco's incubation engine. The need for computational power is rapidly increasing in every sector. From drug discovery to material innovation to complex financial modeling, classical systems are reaching their absolute limits. It’s time for a paradigm shift. The answer is a scalable quantum network, built on open standards and vendor-agnostic architecture. By uniting distributed quantum devices, you unlock limitless computational power. Learn more about the Cisco Universal Quantum Switch at Outshift.com.

    Go deeper with the blog post.

    What We Get Into

    • Why the fault tolerance theorem as usually stated leaves out the case that matters most for networking: quantum inputs and quantum outputs.
    • How Christandl's group shows you can still prepare arbitrarily complex quantum states on a noisy machine, paying only one final layer of physical noise rather than collapsing the whole computation.
    • What this means for restoring meaning to quantum channel capacity results in the presence of noisy encoders and decoders.
    • Why distributed quantum computing — multi-core QPUs talking to each other in quantum, not classical, information — is the natural setting for this work.
    • How recent quantum LDPC code work fits in, and why the team is now focused on making encoders and decoders more space-efficient.
    • Christandl's debate with Gil Kalai: which skeptical assumptions are worth taking seriously, and which he thinks the fault tolerance machinery is robust against.
    • The Quantum for Life workflow: zooming in on the quantum-relevant region of a protein–ligand interaction, running a small quantum simulation, and feeding the result into a classical machine-learning pipeline that needs many such small computations.
    • Why "co-design" has replaced "bridging the gap" as the right metaphor for where quantum hardware and quantum software meet.
    • How quantum sensing — for example, magnetic-field sensing with atomic clouds — could one day deliver genuine quantum inputs into a fault-tolerant quantum computer.

    Resources & Links

    Guest Links

    Papers & Articles

    Key Quotes & Insights

    • On reframing fault tolerance: Christandl argues that the fault tolerance theorem, as usually stated, assumes classical inputs and outputs — but the most important near-term use cases, from networked QPUs to multi-core processors, need quantum inputs and quantum outputs.
    • On the unavoidable final layer of noise: "There will always be a final layer of noise being applied" when a noisy machine prepares a quantum state — and that single layer, not the whole computation, is the real price you pay.
    • On the new metaphor: "A few years back, I would have told you the really important thing is bridging the gap between the hardware and the software. Now it's not anymore about bridging the gap. It's about working together."
    • On Kalai's skepticism: Christandl finds the debate clarifying rather than threatening — the fault tolerance techniques look robust to the noise-model perturbations skeptics raise, and the engineering question is which code, not whether codes work at all.
    • On what quantum advantage in life sciences might actually look like: Not one heroic simulation, but many small, exact quantum computations feeding training data into a much larger classical machine-learning workflow that predicts protein–ligand interactions.

    Related Episodes

  26. Philosophy of Physics Meets Quantum Engineering with Elise Crull

    42 Min.Folge 93

    Mit Elise Crull

    Philosophy of Physics Meets Quantum Engineering with Elise CrullWhy This Episode MattersElise Crull is Associate Professor of Philosophy at CCNY and the CUNY Graduate Center, co-author with Guido Bacciagaluppi …

    Shownotes

    Philosophy of Physics Meets Quantum Engineering with Elise Crull

    Why This Episode Matters

    Elise Crull is Associate Professor of Philosophy at CCNY and the CUNY Graduate Center, co-author with Guido Bacciagaluppi of The Einstein Paradox (Cambridge, 2024), and was named a Fellow of the American Physical Society in 2025 for her archival work recovering voices like Grete Hermann from the foundations of quantum mechanics. She was also one of the speakers on Helgoland in June 2025 for the centenary of quantum mechanics — opening, as Sebastian notes, by thanking the organizers for the courage to invite a philosopher.

    This conversation matters because the truce between physicists and philosophers of physics is over. Quantum computing has turned interpretive questions — what counts as entanglement, what decoherence really is, whether causal order can be put in superposition — into engineering questions with budget consequences. If you build, fund, or write about quantum hardware, this episode will sharpen how you hear the words being used around you.

    Sponsor

    This episode is brought to you by Outshift, Cisco's incubation engine. The need for computational power is rapidly increasing in every sector. From drug discovery to material innovation to complex financial modeling, classical systems are reaching their absolute limits. It’s time for a paradigm shift. The answer is a scalable quantum network, built on open standards and vendor-agnostic architecture. By uniting distributed quantum devices, you unlock limitless computational power. Learn more about the Cisco Universal Quantum Switch at Outshift.com.

    Go deeper with the blog post.

    What We Get Into

    • Why "decoherence" and "noise" are not interchangeable, and why error correction strategy depends on telling them apart
    • The six-plus working definitions of entanglement currently circulating in physics — and why "classical entanglement" makes a philosopher's eye twitch
    • What Einstein actually objected to in EPR (hint: it wasn't really determinism), drawn from Schrödinger's "Einstein-Paradoxon" correspondence folder
    • Indefinite causal ordering: whether the experimental speedups reflect genuinely acausal physics or our stubbornly classical definitions of "cause" and "signal"
    • How monogamy of entanglement is only monogamous with respect to a single degree of freedom — and why that nuance is already being exploited in entanglement harvesting
    • Why "it's just a tool" is the most insidious thing an engineer can say about quantum or AI technology
    • How the standard heroic-origin story of quantum mechanics structurally erased experimentalists — many of them women like Hertha Sponer — and what that pattern predicts about quantum computing's own emerging origin story
    • What Grete Hermann did to von Neumann's impossibility proof forty years before anyone listened
    • Why Crull thinks the next physical theory, whatever succeeds quantum field theory, is likely to be stranger, not tamer

    Resources & Links

    Guest Links

    Books & Papers

    Helgoland & History

    For General Audiences

    Key Quotes & Insights

    • On what philosophy is for: "Every aspect of science we do requires interpretation, because the world isn't just out there. We make choices about how to encounter it."
    • On decoherence vs. noise: Crull notes the question physicists at Duke recently raised with her — how do you tell the difference between decoherence and noise? — and stresses that one is something you shield against, the other is something else entirely. Error correction strategy depends on the distinction.
    • On what really bothered Einstein: Despite the popular story, "He wasn't as concerned about determinism as you would think." What Einstein wanted was a theory whose mathematics had a one-to-one mapping to individual systems with their own states — and entanglement broke that.
    • On indefinite causal order: Experimentalists often equate causation with signaling constraints, but "those are very different things." The superposition-of-causal-orders results may reveal less about causation than about the fact that temporal ordering itself remains defined in irreducibly classical ways.

  27. The Quantum Control Stack with Niels Bultink

    37 Min.Folge 92

    Mit Niels Bultink

    Why This Episode MattersNiels Bultink earned his PhD at QuTech under Leonardo DiCarlo, where he performed some of the first real-time feedback experiments on solid-state qubits — the foundational primitive …

    Shownotes

    Why This Episode Matters

    Niels Bultink earned his PhD at QuTech under Leonardo DiCarlo, where he performed some of the first real-time feedback experiments on solid-state qubits — the foundational primitive behind quantum error correction. He spun Qblox out of TU Delft in 2018, and has grown it to roughly 140 people serving 150+ customers worldwide, mostly on revenue rather than venture capital, before raising a $26M Series A in 2024.

    This conversation matters now because the goalposts for useful quantum computing have moved closer in the last 12 months. Recent estimates suggest breaking RSA may need ~10,000–100,000 qubits, not tens of millions — and at that scale, the control stack is no longer a lab afterthought. It is a strategic supply chain question, which is why the DOE just picked Qblox to manufacture Fermilab's QICK platform domestically. If you care about how quantum computers actually get built — the layer between the qubit and the software — this is the episode for you.


    Sponsor

    This episode is brought to you by Outshift, Cisco's incubation engine. The need for computational power is rapidly increasing in every sector. From drug discovery to material innovation to complex financial modeling, classical systems are reaching their absolute limits. It’s time for a paradigm shift. The answer is a scalable quantum network, built on open standards and vendor-agnostic architecture. By uniting distributed quantum devices, you unlock limitless computational power.
    Learn more about the Cisco Universal Quantum Switch at Outshift.com.

    Go deeper with the blog post.


    What We Get Into

    • Why the IBM Quantum Experience originally needed a meter of rack equipment per qubit, and what had to change architecturally to scale past that
    • How a quantum control stack can be genuinely qubit-agnostic — and where modality differences actually live (mostly in the analog front end, not the digital core)
    • Why pre-compiled pulse sequences hit a wall, and how dynamic, adaptive control is a prerequisite for fault tolerance, not a nice-to-have
    • The role of Qblox's SYNQ and LINQ protocols in achieving picosecond-level synchronization and low-latency feedback across hundreds of cores
    • Why FPGAs are the right substrate today, and why the field will need to move toward ASICs as production volumes grow
    • The strategic logic behind manufacturing Fermilab's open-source QICK platform — and how it complements rather than cannibalizes the Qblox Cluster
    • What the Quantum Utility Block partnership with QuantWare and Q-CTRL actually delivers, including a full-stack demo built in a weekend at APS March Meeting
    • Why Qblox opened a Boston HQ and started U.S. manufacturing in Canton, Massachusetts in 2026, and how geopolitics is reshaping quantum supply chains
    • Niels's read on which qubit modalities are gaining ground fastest right now — including a notable jump in spin qubits and neutral atoms
    • What's special about the Dutch quantum ecosystem, and why a value-chain culture produced multiple revenue-driven hardware companies

    Resources & Links

    Guest & Company

    Partnerships Discussed

    Foundational Paper

    Funding & Market Context

    Key Quotes & Insights

    • On why the control stack is more than picks and shovels: "Sometimes companies like us are called picks and shovels. It's a nice analogy, but it doesn't hold entirely. The qubits are just the bottom layer of the stack — and all the other layers are also crucial to develop."
    • On flexibility as a requirement, not a feature: Pre-compiled, rigid sequences can't support quantum error correction. Adaptive, real-time control flows aren't a performance upgrade — they're "a basic need for this new era of quantum fault tolerance."
    • On the moving goalposts for useful quantum computing: A year ago, breaking RSA looked like tens of millions of qubits. Recent estimates put it at 10,000–100,000 — "a factor hundred smaller what we now think we need versus a year ago."
    • On the future of FPGAs: FPGAs are the right substrate for today's flexibility, but already at current production volumes, "it makes more sense to put things in chips, in ASICs."
    • On the Dutch ecosystem: What sets Delft apart isn't a slogan about ecosystems but a value-chain culture — companies that focus on one layer, work together, and grow on customer revenue rather than venture rounds.

    Stay in the Ecosystem

  28. Hardware-Faithful Digital Twins for Quantum Computing with Izhar Medalsy

    38 Min.Folge 91

    Mit Izhar Medalsy

    Hardware-Faithful Digital Twins for Quantum Computing with Izhar MedalsyIzhar Medalsy is not a career qubit theorist. His path runs from a physical chemistry PhD and an ETH Zurich postdoc in atomic force …

    Shownotes

    Hardware-Faithful Digital Twins for Quantum Computing with Izhar Medalsy

    Izhar Medalsy is not a career qubit theorist. His path runs from a physical chemistry PhD and an ETH Zurich postdoc in atomic force microscopy and ternary nanoscale logic, through productizing scientific instruments at Bruker, through building one of the fastest resin 3D printers on the market, into co-founding Quantum Elements in 2023 with Daniel Lidar (USC) and Amir Yacoby (Harvard). That arc — nanoscale measurement scientist turned deep-tech operator — shapes how he thinks about the simulation gap in quantum computing.

    The conversation lands at a specific moment. In April 2026, Quantum Elements published a joint result with AWS, USC, and Harvard simulating a distance-7 rotated surface code with 97 physical qubits using full quantum master equations on AWS HPC7a, and announced a deeper collaboration with Rigetti Computing on next-generation superconducting processors. If you care about how error correction strategies, decoders, and pulse-level controls actually get developed before they ever touch hardware, this episode is for you.


    EPISODE SPONSOR

    This episode is brought to you by Outshift, Cisco's incubation engine. The need for computational power is rapidly increasing in every sector. From drug discovery to material innovation to complex financial modeling, classical systems are reaching their absolute limits. It’s time for a paradigm shift. The answer is a scalable quantum network, built on open standards and vendor-agnostic architecture. By uniting distributed quantum devices, you unlock limitless computational power.


    Learn more about the Cisco Universal Quantum Switch at Outshift.com
    Go deeper with the blog post The switch that quantum networking has been waiting for

    ====================================================================================================


    What We Get Into

    • Why generic noise models fall short and what "hardware-faithful" actually means when two nominally identical QPUs have different noise fingerprints
    • How Quantum Elements scaled open-system master-equation simulation from a brute-force ceiling around 16 qubits to 97 qubits using stochastic compression on top of Quantum Monte Carlo
    • The compute reality of the distance-7 surface code run on AWS HPC7a — only 96 vCPUs and a few hundred gigabytes of memory, not the thousands of vCPUs they initially feared
    • Why decoders are the invisible bottleneck in fault tolerance, and where AI-trained decoders fed by digital twin data could plausibly run inside the real-time quantum-classical loop
    • Extending error suppression from physical qubits up to logical qubits — the IBM Eagle work where digital-twin-guided strategies reportedly took entangled logical qubit fidelity from 43% to 95%
    • How the same digital twin approach extends to neutral atoms (live today) and ion traps (on the roadmap)
    • What Rigetti gets out of the partnership, what it means to have Chad Rigetti on the board, and how Constellation fits alongside real hardware time
    • Izhar's "wooden models in the air tunnel" critique of how the quantum industry currently iterates — and what a parallel virtual development track buys you

    Resources & Links

    Guest & Company

    Papers & Articles

    Key Quotes & Insights

    • "Sometimes when I look at the quantum industry, there are instances where you think, well, it's almost like building the next fighter jet with wooden models in the air tunnel." — Izhar's framing for why the field needs a real simulation layer.
    • On hardware awareness: each modality, each QPU, sometimes each calibration cycle has its own pulses, its own noise processes, and its own failure modes. You cannot build the control stack without modeling where you are starting from and where you are trying to get to.
    • Insight: The brute-force ceiling for open-system master-equation simulation is roughly 16 qubits. Stochastic compression layered on Quantum Monte Carlo is what let Quantum Elements reach distance-7 surface code at 97 qubits — exploiting sparsity rather than enumerating the full state space.
    • On logical qubits: "We cannot assume that logical qubits will be noise-free." Error suppression strategies developed at the physical level need to be re-derived at the logical level, and digital twins are how you train and test those strategies before hardware.
    • Insight: The most interesting downstream story may not be simulation itself but AI decoders trained on digital-twin-generated data — small enough to run at the edge, fast enough to live inside the real-time quantum-classical loop.

    Related Episodes

  29. Are We Computing Quantum in the Wrong Base? with Ivan Deutsch

    45 Min.Folge 90

    Mit Ivan Deutsch

    Are We Computing Quantum in the Wrong Base? with Ivan DeutschIvan Deutsch is Distinguished Regents' Professor of Physics and Astronomy at the University of New Mexico and the founding director of CQuIC, the …

    Shownotes

    Are We Computing Quantum in the Wrong Base? with Ivan Deutsch


    Ivan Deutsch is Distinguished Regents' Professor of Physics and Astronomy at the University of New Mexico and the founding director of CQuIC, the Center for Quantum Information and Control. Along with his longtime collaborator Poul Jessen, Ivan helped lay the theoretical foundations for neutral-atom quantum computing in the 1990s: trapping individual atoms in optical lattices, cooling them to near absolute zero, and shuttling them in parallel to perform quantum logic. The companies commercializing those ideas today — QuEra, Pasqal, Atom Computing, Infleqtion, and the newly announced Aurora out of Caltech — are building on architectural concepts that trace directly to his group's early papers. His 9,600+ citations across quantum information, atomic physics, and quantum control place him among the most-cited theorists in the field.


    The reason to talk to Ivan now is that he has been making a quietly heterodox argument: every one of those commercial platforms encodes information in two energy levels of an atom that has ten or sixteen, and Ivan thinks the field should be asking whether that's the right choice — not for information density, which is only a logarithmic gain, but for fault tolerance. This conversation goes deep on qudits, spin cat codes, and the co-design philosophy that has shaped Ivan's career at the interface between theory and experiment, ions and neutral atoms, and academia and industry. If you are following neutral-atom hardware, fault-tolerant quantum error correction, or the emergence of regional quantum ecosystems, this episode is essential.


    What You'll Learn

    • Why neutral atoms were the "underdog cousins" of trapped ions — and the precise trade-off at the heart of a 30-year rivalry: ions are great and terrible because they're charged; neutral atoms are great and terrible because they're neutral
    • What the original neutral-atom quantum computing paper actually got right: the parallel atom-movement architecture now central to QuEra, Atom Computing, and Infleqtion's roadmaps was already there — even if the Rydberg blockade's full power wasn't appreciated until later
    • What qudits are and why fault tolerance, not information density, is the compelling argument: the information gain from base-2 to base-10 is only logarithmic, but co-designing error-correcting codes with the physical structure of the hardware may be transformative
    • How spin cat codes work: using the extra energy levels inside a single atom for error redundancy, directly analogous to bosonic cat codes in microwave cavities, with fault-tolerant thresholds that may surpass standard qubit surface codes
    • Why biased error correction matters: real physical errors in neutral atoms aren't arbitrary, and codes designed around the dominant error channels — including leakage and erasure — can dramatically outperform worst-case generic schemes
    • How leakage becomes an asset: when population escapes the qubit subspace into other levels, detecting that escape converts it from an unknown error into an erasure error, which is far easier to correct
    • Why working at interfaces is where the creative work happens: Ivan's career has been built at the boundary between theory and experiment, between ion-trap and neutral-atom communities, and now between research and industry
    • How New Mexico became a quantum hub: the founding of QNM-I, the partnership with Colorado, and the Elevate Quantum Tech Hub — turning decades of national-lab and university strength into an actual industrial ecosystem


    Resources & Links

    Guest Links

    Key Papers

    Talks & Context

    Ecosystem

    Field Context

    Key Quotes & Insights

    "Ions are great because they're charged. You can hold onto them very tightly and manipulate them extremely precisely. Ions are terrible because they're charged — you can't push many together and they all talk to one another." — Ivan Deutsch, on the fundamental ion/neutral-atom trade-off at the heart of a 30-year platform rivalry

    "I don't want to be an evangelist, because I don't really feel I've studied this well enough to say we really should do quantum computation base-10 rather than base-two. But I think it's an important question." — Ivan Deutsch, on qudits — a carefully calibrated position from a theorist making a strong technical bet

    "We just wanted to make the whole thing faster." — Steve Rolston (Ivan's co-author), on the mindset behind the Rydberg blockade paper, which ultimately unlocked the entire commercial neutral-atom industry

    Insight: The spin cat code ...

  30. Quantum Chemistry's Classical Limits with Garnet Chan

    41 Min.Folge 89

    Mit Garnet Chan

    Your host, Sebastian Hassinger, is joined on this episode by Garnet Chan, the Bren Professor of Chemistry at Caltech, a member of the National Academy of Sciences, and among the most cited computational …

    Shownotes

    Your host, Sebastian Hassinger, is joined on this episode by Garnet Chan, the Bren Professor of Chemistry at Caltech, a member of the National Academy of Sciences, and among the most cited computational chemists in the world (34,000+ Google Scholar citations). Garnet is neither a quantum computing booster nor a dismissive skeptic. He's a theorist who works at the exact boundary between what classical algorithms can and cannot do — and who keeps finding that boundary further out than the quantum computing community has claimed. The FeMo-cofactor has been a flagship quantum computing use case for nearly a decade: a catalytic core of the enzyme that fixes atmospheric nitrogen into ammonia, and a molecule widely described as "beyond classical reach." Chan's January 2026 paper challenges that framing directly. This conversation explains what was actually solved, what wasn't, and what it would genuinely take for quantum computers to contribute to the chemistry of nitrogen fixation. This episode is for researchers, engineers, and informed observers who want an honest, technically grounded view of where quantum computers genuinely help in chemistry — and where classical methods are more capable than the field has admitted.


    What You'll Learn

    • Why the FeMo-cofactor became one of the quantum computing community's favorite benchmark — and why the framing around energy savings from nitrogen fixation is less accurate than it sounds
    • What "chemical accuracy" (~1 kcal/mol) actually means as a precision target, and why hitting it classically undermines a decade of quantum resource estimates
    • Why real chemical systems are only "slightly entangled" — and what that means for the general argument that quantum computers are the natural tool for quantum chemistry
    • The difference between a problem being hard and a problem being exponentially hard — and why that distinction matters enormously for quantum advantage claims
    • Where the genuine classical wall might be: bridging 15 orders of magnitude in timescale to simulate an enzyme's full catalytic mechanism — and whether quantum computers have anything to say about that
    • Why Chan wrote a public blog post explaining his own paper — and what that reveals about the state of discourse in quantum chemistry and the quantum computing industry
    • The broader impact of quantum information science on chemistry — beyond hardware, the conceptual tools of quantum information have genuinely reshaped how chemists think about many-body states
    • What Chan is actually working toward: a full computational understanding of the nitrogenase reaction mechanism, using machine learning to bridge timescales classically — a decade-long journey he finds genuinely exciting


    Resources & Links


    The Central Paper & Commentary

    • Zhai et al. (2026) — "Classical Solution of the FeMo-Cofactor Model to Chemical Accuracy and Its Implications" arXiv:2601.04621 — The January 2026 preprint at the heart of this episode; the classical solution of the standard 76-orbital/152-qubit FeMo-co benchmark.
    • Chan — Quantum Frontiers Blog Post (March 2026) The FeMo-Cofactor and Classical and Quantum Computing — Chan's own accessible commentary on the paper, written in response to widespread misinterpretation; essential reading alongside the paper.


    Key Papers for Context

    • Chan (2024) — "Spiers Memorial Lecture: Quantum Chemistry, Classical Heuristics, and Quantum Advantage" Faraday Discussions, 254, 11–52 — The formal theoretical framework behind Chan's thinking, including the "classical heuristic cost conjecture"; the deep-dive companion to this episode.
    • Lee et al. (2023) — "Evaluating the Evidence for Exponential Quantum Advantage in Ground-State Quantum Chemistry" Nature Communications — Chan group's landmark 2023 paper concluding that evidence for exponential quantum advantage across chemical space has yet to be found.
    • Begušić & Chan (2023/2024) — "Fast Classical Simulation of Evidence for the Utility of Quantum Computing Before Fault Tolerance" Science Advances — The paper showing classical simulation on a single laptop core could reproduce and exceed IBM's 127-qubit "utility" experiment.
    • Bauer, Bravyi, Motta & Chan (2020) — "Quantum Algorithms for Quantum Chemistry and Quantum Materials Science" arXiv:2001.03685 — A balanced review by Chan and colleagues showing he takes quantum algorithms seriously; useful counterpoint to the skeptical framing.
    • Babbush et al. (2025) — "The Grand Challenge of Quantum Applications" arXiv:2511.09124 — Google Quantum AI's direct engagement with Chan's skeptical position; argues polynomial speedups may still be practically decisive.
    • Computational Chemistry Highlights — Review of FeMo-co Paper compchemhighlights.org — Third-party commentary from Jan Jensen (University of Copenhagen).


    Tools & Software

    • PySCF — Python-based Simulations of Chemistry Framework https://pyscf.org — The open-source quantum chemistry package co-stewarded by Chan's group; widely used for electronic structure calculations.
    • BLOCK — DMRG and Matrix Product State Algorithms https://github.com/sanshar/Block — Chan group's open-source implementation of density matrix renormalization group methods; the tensor network engine underlying much of this work.


    Guest Links

    • Chan Lab at Caltech chan-lab.caltech.edu — Research group homepage with publications, software, and group members.
    • Garnet Chan — Caltech Faculty Profile cce.caltech.edu/people/garnet-k-chan — Official Caltech Division of Chemistry & Chemical Engineering page.
    • Google Scholar Profile scholar.google.com — 34,000+ citations across theoretical chemistry and condensed matter physics.
    • Caltech Science Exchange — Ask a Caltech Expert: Quantum Chemistry scienceexchange.caltech.edu — Accessible overview of Chan's perspective for a general science audience.


    Key Quotes

    "To a good approximation, you and I are not entangled. That's essentially how people think about molecules — atoms are distinct entities, and you can define each as a local entity because its properties are not intrinsically tied up with some other thing." — Garnet Chan, explaining why most chemical systems are cla...

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