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

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

• Dr. Shintaro Sato — Fujitsu Quantum Day Profile — Fujitsu's own bio page covering Sato's dual role at Fujitsu Research and RIKEN RQC-Fujitsu Collaboration Centre.
• Shintaro Sato — ResearchGate Profile — Full publication list (164 papers, 3,096 citations); useful for tracing his path from graphene nanoelectronics to quantum architecture.
• Interview with Shintaro Sato — QuTech — Sato discusses the NV-center and diamond-spin collaboration with QuTech and the vision for quantum-as-a-service.

Hardware Roadmap & STAR Architecture

• Fujitsu Quantum Day 2026 — Sato Presentation Slides (PDF) — Primary-source slides showing the full hardware roadmap: 64 → 256 → 1,024 → 10,000+ qubits with STAR architecture milestones.
• Fujitsu Officially Starts 10,000+ Qubit Development — Fujitsu Press Release (Aug 2025) — Official announcement of the early-FTQC 10,000-qubit program targeting FY2030.
• STAR Architecture Overview — Fujitsu Global — Technical explainer for STAR ver. 3 (announced March 2026), including the qubit-reduction claims for ruthenium-catalyst calculations.
• How Fujitsu Is Tackling a 10,000-Qubit Quantum Computer — The Quantum Insider (Dec 2025) — Deep-dive on STAR architecture and the 250-logical-qubit target.

Diamond-Spin & SnV Prototype

• Fujitsu Develops Diamond-Spin Quantum Computer Prototype — The Quantum Insider (Sept 2026) — Announcement of the SnV-center diamond-spin QPU prototype from the Fujitsu/TU Delft/QuTech collaboration.
• Fujitsu Diamond-Spin SnV Prototype Analysis — Quantum Computing Report (Sept 2026) — Technical breakdown of SnV center advantages, photon emission characteristics, and hybrid roadmap context.
• Fujitsu and QuTech Realize High-Precision Quantum Gates — Fujitsu Press Release (Mar 2025) — NV-center two-qubit gate fidelity result (<0.1% error) published in Physical Review Applied; the technical foundation for the SnV work discussed in this episode.

Neutral-Atom / Yaqumo Collaboration

• Fujitsu and Yaqumo Begin Testing on Neutral-Atom Hardware — The Quantum Insider (Sept 2026) — Breaking news on STAR validation on Yaqumo's neutral-atom processors, announced just before this recording.

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

• Marie Lepske — LinkedIn — Primary professional profile; includes keynote highlights and 2026 speaking engagements
• Constructor Capital — Official Website — Fund homepage with portfolio listings, team bios, and investment thesis across DeepTech, Software Tech, and Knowledge Tech
• Constructor Capital Fund I Close (Tech.eu, Feb 2026) — Coverage of the $110M close, check sizes ($1–10M, select up to $15M), and the university sourcing network

Portfolio Companies Referenced

• QuEra — $230M+ Financing Round Announcement — The round led by Google Quantum AI and SoftBank Vision Fund 2, with NVIDIA's NVentures participating
• Qnami Acquisition by Quantum Design (The Quantum Insider, June 2026) — The sensing exit discussed in the episode; context on what a quantum sensing acquisition looks like

Background Reading

• Quantum Computing Report — "Venture Capital Trends in Quantum Technologies" (Runa Capital, 2022) — Lepske's co-authored market analysis, the source of her "specialist VC" thesis discussed in the episode
• Constructor Capital — "Quantum Investing Playbook" (Nov 2025) — Her Paris keynote on making successful quantum investments; source of the valuation figures cited in the conversation
• Entangled Future — Quantum Computing Funding & Investment Landscape 2026 — Context on the $4.9B private VC figure for 2025 and the broader public commitment landscape

Recent Constructor News

• Constructor Start Demo Day Finalists (The Quantum Insider, Sept 2026) — Quantum startups among the 16 finalists announced one week before this recording

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

• Ep. 22 — Trapped Ions and Quantum VCs with Chiara Decaroli — Another physicist-turned-investor conversation; useful companion for understanding how scientific training shapes investment judgment in quantum hardware
• Ep. 96 —

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

Resources & Links

Guest

Papers & Articles

Further Reading

Key Quotes & Insights

> "It's not that nature ...

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

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...

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

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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

• Román Orús — Personal Site — Lists talks, reviews, affiliations, and awards including the 2024 Physics, Innovation and Technology Prize from the Royal Spanish Society of Physics.
• Multiverse Computing — Official Website — Home page for CompactifAI, Singularity, and Multiverse's full product portfolio.

Papers & Articles Discussed in This Episode

• arXiv 2605.05914 — "Quantum-enhanced Large Language Models on Quantum Hardware via Cayley Unitary Adapters" (May 2026) — The paper at the center of the episode: Llama 3.1 8B layers running on IBM's 156-qubit Quantum System Two. Start here if you want the technical details behind the quantum-in-an-LLM result.
• Multiverse Computing — "Talking to a Quantum Computer" (May 2026) — The accessible blog-post version of the Cayley Unitary Adapter experiment; a good entry point before tackling the arXiv paper.
• arXiv 2401.14109 — CompactifAI: Extreme Compression of Large Language Models Using Quantum-Inspired Tensor Networks — The foundational peer-reviewed paper introducing Multiverse's tensor network compression method.
• arXiv 2509.06653 — "Classical Neural Networks on Quantum Devices via Tensor Network Disentanglers" (Sep 2025, rev. Apr 2026) — Orús, Singh, and Aizpurua on hybrid classical-quantum execution for bottleneck neural network layers; the research underpinning the longer-term hybrid architecture vision.

Models & Products

• HyperNova 60B on Hugging Face — Open-source 50%-compressed model derived from GPT-OSS-120B; context for Multiverse's open model strategy.
• Pulsar 16B Launch with NVIDIA (June 2026) — Announcement of Multiverse's open reasoning model, scoring 87.22 on AIME 2025 at 16B parameters.

Funding & Company Context

• Series C Announcement — GlobeNewswire (July 2026) — $570M / €500M round at $1.7B pre-money valuation; covers investor lineup and deployment verticals.

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, ...

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

• EPJ Quantum Technology — "The quantum technology job market: data-driven analysis of 3,641 job posts" (March 2026) — Lewandowski's peer-reviewed paper on the quantum job market, the most rigorous published treatment of the data underlying qubitsok.
• 2026 Quantum Computing Salary Report — Analysis of 194 salary data points drawn from real job postings; a useful benchmark for researchers and hiring managers alike.
• Fastest-Growing Quantum Skills 2026 — Lewandowski's analysis of 1,212 quantum jobs and 14,975 papers identifying which technical skills are accelerating and which are declining in the labor market.

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

• Dr. Bob Sutor's "Quantum Follow Friday" (February 27, 2026) — Sutor Group newsletter highlighting Lewandowski as a key quantum community voice worth following; useful context for his growing recognition as an independent analyst.

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...

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

• Richard Entrup — Worth Magazine Profile — Career arc from CIO/CISO roles at major global brands to KPMG's Emerging Solutions practice
• KPMG Quantum Dawn (2025) — KPMG's enterprise quantum readiness hub, introducing the Q-PREP framework and PQC implementation services, with Entrup as named lead
• KPMG Quantum homepage

Reports & Research

• KPMG — "The Quantum Threat Is No Longer Theoretical" (2026) — The threat brief discussed in this episode, charting the rapid decline in qubits needed to crack RSA-2048 and urging immediate PQC migration
• KPMG — "From Theory to Impact: Real-World Results in Quantum Machine Learning" (2026) — KPMG's joint report with IBM and Kipu Quantum on measurable quantum ML results on real hardware
• KPMG — "Prepare Now for Quantum Cyber Risk" — Board Leadership Article (2026) — C-suite and board-level guidance on integrating quantum risk into enterprise oversight
• arXiv — "Quantum-enhanced satellite image classification" (2026) — The underlying research paper behind the KPMG/IBM/Kipu Quantum ML results

Ecosystem & Events

• Chicago Quantum Exchange — KPMG Joins CQE (October 2024) — Announcement of KPMG's formal CQE membership, referenced in the episode as part of the firm's ecosystem-building strategy
• KPMG 2026 Quantum Consortium — The inaugural KPMG Quantum Consortium event (March 2026, Orlando) discussed in the episode

Independent Coverage

• Quantum Computing Report — KPMG joins Chicago Quantum Exchange (2024) — Independent coverage of KPMG's CQE partnership and enterprise quantum strategy
• Quantum Zeitgeist — Kipu Quantum satellite imagery coverage (Feb 2026) — Independent analysis of the KPMG/IBM/Kipu hybrid QML results

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

• Ep. 81 — Quantum LDPC Error Correction with Larry Cohen and Paul Webster — Directly relevant: Cohen and Webster discuss how QLDPC error correction reduces the qubit overhead needed for RSA cryptanalysis, the technical underpinning of the threat timeline Entrup describes
• Ep. 38 —

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

• Thaddeus D. Ladd — Personal Website & Publications — Self-curated, annotated bibliography; the best single source for his research arc across spin qubits and quantum communication.
• Thaddeus Ladd — Hertz Foundation Profile — Biographical overview of his career and role at HRL.
• Thaddeus D. Ladd — Google Scholar — Full citation record.

Papers & Articles

• A Digitally Controlled Silicon Quantum Processing Unit — arXiv (April 2026) — The QPU paper discussed at length in this episode: 54-dot device, cryo-CMOS controller at 4 K, superconducting ribbon cable, and error correction experiments — all working as one integrated system.
• Universal Logic with Encoded Spin Qubits in Silicon — Nature (2023) — The landmark result demonstrating universal logic with exchange-only encoded qubits; Ladd was co-author and lead theorist.
• Two-Dimensional Si Spin Qubit Arrays with Multilevel Interconnects — PRX Quantum (2025) — Scalable 2D spin-qubit arrays achieving greater than 99.9% single-qubit gate fidelity; the step between the 2023 and 2026 results.
• Silicon Encoded Spin Qubits Achieve Universality — HRL (2023) — HRL's public announcement of the Nature result; accessible summary for non-specialists.
• Semiconductor Spin Qubits: The Certainty of Progress — HRL (December 2025) — HRL's public framing of the platform's trajectory, published shortly before the Q2B meeting where Sebastian and Thaddeus first met.

Acquisition & IBM Strategy

• IBM to Acquire HRL Laboratories — IBM Newsroom (July 23, 2026) — The definitive transaction announcement; names the full scope of what IBM says it is acquiring.
• IBM to Acquire HRL Laboratories — HRL Laboratories (July 23, 2026) — HRL's concise confirmation of the deal and the beginning of regulatory review.
• What Are Spin Qubits? — IBM Quantum (July 23, 2026) — IBM's technical explanation of HRL's Si/SiGe exchange-only qubits and the shared silicon fabrication argument.
• A Brief History of HRL Laboratories — IBM Research (July 23, 2026) — IBM's institutional framing of HRL, including its history with the laser, self-aligned-gate MOS fabrication, and the 2026 spin-qubit QPU.
• IBM and U.S. Department of Commerce Announce Anderon Quantum Foundry (May 21, 2026) — The 300 mm quantum foundry announcement that Thaddeus identifies as one of the clearest pieces of strategic logic behind the HRL acquisition.
• IBM Commits More Than $10 Billion to Quantum Computing (June 2, 2026) — Capital context for the acquisition: R&D, manufacturing scale-up, M&A, and ecosystem investment over five years.

Tools & Platforms

• spinQICK — GitHub — HRL's open-source FPGA-based spin-qubit control toolkit; a concrete artifact of HRL's approach to open tooling.
• HRL Launches Open-Source spinQICK — HRL (July 2025) — Announcement and context for the spinQICK release.
• HRL Quantum — Collection of HRL quantum research, talks, and news.

Organizations

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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

• Dr. Aaron Kemp — KPMG People Profile — Official bio covering Aaron's DoD/classified cybersecurity background and current role as US Quantum Leader.

Papers & Research

• arXiv:2602.18350 — Quantum-enhanced satellite image classification — The peer-reviewed KPMG/Kipu Quantum/IBM paper Aaron co-authored, demonstrating hybrid quantum-classical accuracy gains on IBM processors.
• From Theory to Impact: Real-World Results in Quantum Machine Learning — KPMG's editorial summary of the satellite imagery research, framed for enterprise readers.
• From Theory to Impact — Full Technical Report (PDF) — The detailed technical companion walking through the hybrid pipeline step by step.

PQC & Enterprise Frameworks

• Q-PREP: Seven Steps to Post-Quantum Cryptography Readiness (PDF) — KPMG's prescriptive PQC migration framework, with Aaron as lead author.
• The Quantum Threat Is No Longer Theoretical (PDF) — Aaron's board-level brief on Q-Day urgency.
• Prepare Now for Quantum Cyber Risk (KPMG Board Leadership Center) — Aaron's article for corporate directors, originally in NACD Directorship Online.

Related Coverage & Commentary

• Kipu Quantum: Quantum-Enhanced AI Deployable in Production — Announcement of the production framework that removes quantum hardware from the inference loop; Aaron quoted as enterprise champion.
• KPMG's Seven Steps Build Quantum Resilience for Businesses (Quantum Zeitgeist) — Third-party coverage of Q-PREP.
• A Framework Can Tell You What to Do. It Cannot Tell You What You Have. (Qtonic Substack) — A critical response arguing that advisory frameworks don't solve the underlying cryptographic inventory problem — useful counterpoint reading.

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

• Episode 14: A Hybrid NISQ-Classical Solution Architecture with Harry Buhrman — Foundational thinking on hybrid quantum-classical architectures relevant to the Kipu/KPMG/IBM approach.
• Episode 38: Quantum Machine Learning with Jessica Pointing — A rigorous look at the tradeoffs and open questions in QML that frame Aaron's satellite imagery results.
• Episode 81: Quantum LDPC error correction with Larry Cohen and Paul Webster — Directly relevant to the compressing resource estimates for breaking RSA that shape PQC urgency.
• Episode 86: Quantum Advantage Achieved with Dominik Hangleiter — A theorist's careful framing of what advantage claims should and shouldn't mean.
• Episode 40: Integrating Quantum Computers and Classical Supercomputers with Martin Schultz — Useful context on the heterogeneous compute future Aaron and Sebastian discuss at the end of the episode.

Stay in the Ecosystem

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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

• Barak Bussel bio — UCLA CQSE Strategic Board — Official page covering Barak's role as Board Chair and his physics and venture background.
• 7i Capital — Barak's deep tech venture firm, investing across quantum, AI, semiconductors, cybersecurity, robotics, clean energy, and space.
• UCLA Center for Quantum Science and Engineering (CQSE) — The multidisciplinary center Barak chairs, spanning physics and engineering research.
• Barak Bussel on LinkedIn — Where Barak has publicly flagged the Oratomic investment and the June 2026 executive orders.

The Oratomic Round and Recent Breakthroughs

• Oratomic raises $300M Series A — The Quantum Insider — Confirms 7i Capital in the syndicate for the largest-ever first institutional round in quantum computing.
• Oratomic Series A deep dive — Quantum Computing Report — Technical breakdown of the reconfigurable neutral-atom architecture and full investor syndicate.
• Oratomic's "no intermediate product" strategy — MLQ.ai — Analysis of Oratomic's bet against the QuEra/Pasqal early-revenue playbook.
• QEDMA raises $26M Series A — Quantum Zeitgeist — 7i portfolio company Kedma's error mitigation round with IBM participation, referenced in Barak's Ising model results.

Policy and Market Context

• White House EO: "Ushering in the Next Frontier of Quantum Innovation" — One of the two June 22, 2026 executive orders Barak discusses.
• Sidley Austin analysis of the June 2026 quantum EOs — Legal explainer covering both the innovation EO and the post-quantum cryptography mandate.
• Cloudflare on the accelerated post-quantum timeline — Notes that Q-Day estimates have moved in response to Google and Oratomic breakthroughs.
• PitchBook Q2 2026 Quantum Computing Funding Report — Record 2025 VC totals and Q1 2026 liquidity data relevant to Barak's exit thesis.

UCLA Research Park and Regional Ecosystem

• UCLA launches SoCal Quantum Alliance — The regional coalition Barak references, with founding members including Caltech, JPL, Boeing, IBM, and Cisco.
• Quantum Innovation Hub at the UCLA Research Park — Preview of the 40,000 square foot lab space and the broader research park vision Barak describes.
• Quantum Innovation Hub Director appointment — Prof. Jason Petta named to lead the QIH, one of the founding anchors of the research park.

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...