Free Daily Podcast Summary
The New Quantum Era - innovation in quantum computing, science and technology: Daily Summaries Delivered
by Sebastian Hassinger
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.
Latest Episodes
The most recent episodes — sign up to get AI-powered summaries of each one.
- 2 days ago41 min
Superconducting Qubits, STAR Architecture, and Diamond-Spin Qubits with Dr. 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 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 IntoHow 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 & LinksGuest & OrganizationDr. 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
- 1 weeks ago41 min
Quantum Venture Investing from the Lab to the Market with 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 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 IntoWhy 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 entityHow 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 tableThe 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 internallyWhat 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 crowdedThe 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 attentionThe 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 buildHow Constructor supports portfolio companies beyond capital — executive hiring, software development guidance, co-investor introductions, and the limits of that hands-on modelAI 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 convergeResources & LinksGuest & FundMarie Lepske — LinkedIn — Primary professional profile; includes keynote highlights and 2026 speaking engagementsConstructor Capital — Official Website — Fund homepage with portfolio listings, team bios, and investment thesis across DeepTech, Software Tech, and Knowledge TechConstructor 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 networkPortfolio Companies ReferencedQuEra — $230M+ Financing Round Announcement — The round led by Google Quantum AI and SoftBank Vision Fund 2, with NVIDIA's NVentures participatingQnami Acquisition by Quantum Design (The Quantum Insider, June 2026) — The sensing exit discussed in the episode; context on what a quantum sensing acquisition looks likeBackground ReadingQuantum 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<a href="https://constru
- 2 weeks ago46 min
Rational Quantum Mechanics and the Qubit Ceiling with 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 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 Tim Palmer — Oxford Department of Physics — Full publication list, including the RaQM paper and prior quantum foundations work Royal Society Fellow Profile: Professor Tim Palmer CBE FRS — Official Fellow profile covering Palmer's career from ensemble forecasting to quantum foundations Oxford Quantum Institute: Tim Palmer — Confirms Palmer's affiliation with OQI Papers & Articles "Rational Quantum Mechanics: Testing Quantum Theory with Quantum Computers" — PNAS (March 2026) — The primary paper discussed in this episode; the full RaQM proposal with the qubit-ceiling prediction arXiv preprint: "Rational Quantum Mechanics: Testing Quantum Theory with Quantum Computers" (Feb 2026) — Full preprint version with acknowledgements and references arXiv preprint: "Solving the Mysteries of Quantum Mechanics: Why Nature Abhors a Continuum" (Feb 2026) — Companion paper laying out the philosophical and mathematical case for RaQM; good starting point for the conceptual argument <a href="ht
- 3 weeks ago49 min
Classical Reversible Computing on Quantum Dots with 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 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 Daniel Loss' profile at King Fahd University of Petroleum and Minerals Daniel Loss — University of Basel, Condensed Matter Theory & Quantum Computing Group — Loss's lab page; lists current research areas, group members, and leadership roles including NCCR SPIN. Daniel Loss — Wikipedia — Comprehensive biographical overview, career history, and awards list for listeners who want background before or after listening. Papers & Articles Classical Reversible Computation by Quantum Coherence — arXiv:2607.06219v3 (2026) — The
- Sep 7, 202640 min
Quantum-Inspired AI and Tensor Network Compression with 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 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 MessageThe 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 IntoWhat 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 & LinksGuest & CompanyRomán 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 produ
- Aug 31, 202646 min
Quantum Workforce Intelligence from qubitsok.com with 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 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 IntoHow 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 & LinksGuest Linksqubitsok.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 & ReportsEPJ 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 poi
- Aug 24, 202635 min
Quantum Risk, Readiness, and the Enterprise Boardroom with 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, Disney/ABC, Time Warner, and Tiffany & Company 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 IntoWhy 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 itThe 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 projectWhy "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 modelWhat 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 creatingHow KPMG built its PQC practice, incubated it within the firm, and handed it off to the cybersecurity advisory team as a core service offeringThe "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 itThe 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 modernizationWhy 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 NetflixResources & LinksGuest & OrganizationRichard Entrup — Worth Magazine Profile — Career arc from CIO/CISO roles at major global brands to KPMG's Emerging Solutions practiceKPMG Quantum Dawn (2025) — KPMG's enterprise quantum readiness hub, introducing the Q-PREP framework and PQC implementation services, with Entrup as named leadReports & ResearchKPMG — "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 migrationKPMG — "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 hardwareKPMG — "Prepare Now for Quantum Cyber Risk" — Board Leadership Article (2026) — C-suite and board-level guidance on integrating quantum risk into enterprise oversightarXiv — "Quantum-enhanced satellite image classification" (2026) — The underlying research paper behind the KPMG/IBM/Kipu Quantum ML resultsEcosystem & EventsChicago Quantum Exchange — KPMG Joins CQE (October 2024) — Announcement of KPMG's formal CQE membership, referenced in the episode as part of the firm's
- Aug 17, 202644 min
Silicon Spin Qubits and the IBM–HRL Acquisition with 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 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 IntoWhy 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 & LinksGuestThaddeus 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 & ArticlesA 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
Get The New Quantum Era - innovation in quantum computing, science and technology summaries in your inbox
Free AI-powered daily recaps. Key takeaways, quotes, and mentions — in a 5-minute read.
Get Free Summaries →Free forever for up to 3 podcasts. No credit card required.
You Might Also Like
Listeners also like.
The Joy of x
A mathematician explores the lives and ideas of leading scientists through in-depth conversations.
The Quanta Podcast
A weekly discussion on groundbreaking science and math stories with Quanta's editorial team.
Smart Talks with IBM
Conversations with leaders leveraging AI, quantum computing, and emerging technologies to transform global businesses.
The Joy of Why
Mathematicians and astrophysicists explore fundamental scientific and mathematical questions with leading researchers.
Latent Space: The AI Engineer Podcast
Explores AI engineering breakthroughs in foundation models, code generation, and AI agents through interviews with researchers and developers.
The a16z Show
Explores technology and cultural shifts shaping the future through conversations with industry leaders and innovators.
From First Principles
Breaks down major science stories weekly, explaining the mechanics behind physics, space, AI, and biotech developments.
Sean Carroll's Mindscape: Science, Society, Philosophy, Culture, Arts, and Ideas
Conversations with leading thinkers exploring fundamental ideas in science, philosophy, culture, and the arts.
Theories of Everything with Curt Jaimungal
A deep, rigorous exploration of theories uniting physics, consciousness, AI, and metaphysics through analytical and unconventional thinking.
"The Cognitive Revolution"
Explores the transformative impact of artificial intelligence through interviews with innovators shaping its future.
No Priors: Artificial Intelligence | Technology | Startups
Discusses AI advancements and implications with researchers, engineers, and founders shaping the future of artificial intelligence.
Possible
Explores optimistic, realistic futures through in-depth conversations with innovators in AI, science, health, and global affairs.
About The New Quantum Era - innovation in quantum computing, science and technology
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.
Customized Recaps
AI-powered recaps with compact key takeaways, quotes, and insights.
Straight to Your Inbox
Get key takeaways from The New Quantum Era - innovation in quantum computing, science and technology in a 5-minute read.
Save Hours Every Week
Stay current on your favorite podcasts without falling behind.
Frequently Asked Questions
What is Podzilla's The New Quantum Era - innovation in quantum computing, science and technology daily summary?
It's a free AI-powered email that summarizes new episodes of The New Quantum Era - innovation in quantum computing, science and technology as soon as they're published. You get the key takeaways, notable quotes, and links & mentions — all in a quick read.
How does the The New Quantum Era - innovation in quantum computing, science and technology podcast summary work?
When a new episode drops, our AI transcribes and analyzes it, then generates a personalized summary tailored to your interests and profession. It's delivered to your inbox every morning.
Is this an official The New Quantum Era - innovation in quantum computing, science and technology product?
No. Podzilla is an independent service that summarizes publicly available podcast content. We're not affiliated with or endorsed by Sebastian Hassinger.
Can I get summaries of other podcasts too?
Absolutely! The free plan covers up to 3 podcasts. Upgrade to Pro for 15, or Premium for 50. Browse our full catalog at /podcasts.
How often does The New Quantum Era - innovation in quantum computing, science and technology release new episodes?
The New Quantum Era - innovation in quantum computing, science and technology publishes weekly. Our AI generates a summary within hours of each new episode.
What topics does The New Quantum Era - innovation in quantum computing, science and technology cover?
The New Quantum Era - innovation in quantum computing, science and technology covers topics including Science, Technology, Physics. Our AI identifies the specific themes in each episode and highlights what matters most to you.
Start getting The New Quantum Era - innovation in quantum computing, science and technology summaries tomorrow morning.
Free forever for up to 3 podcasts. No credit card required.
Free forever for up to 3 podcasts. No credit card required.