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

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

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

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

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

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

"The whole field of chemistry developed without even needing to think about quantum mechanics — and certainly without having to think about a quantum computer." — Chan pushing back on Feynman's often-cited "simulate nature with quantum" framing

"It looks like it should be an impossible task — computing the ground state classically of a Hamiltonian defined in a space of 150 qubits. But all chemical and physical systems are highly structured. The ground state is only a slightly entangled state." — Chan on why the FeMo-co classical solution is possible despite sounding intractableI

• Ep 42: Generative Quantum Eigensolver with Alán Aspuru-Guzik — Aspuru-Guzik is one of the pioneers of quantum chemistry on quantum computers and represents the optimistic counterpart to Chan's measured skepticism. A natural pair for hearing both sides of this debate.
• Ep 30: Aspiring Quantum Chemist with Professor Lin Lin — Another leading computational mathematician working at the quantum chemistry/quantum computing interface; directly relevant to the classical simulation landscape Chan describes.
• Ep 31: The Utility of Quantum Computing for Chemistry with Jamie Garcia — IBM's perspective on quantum utility in chemistry, including the 127-qubit experiments that Chan's group classically replicated; great context for understanding the other side of the IBM debate.
• Ep 86: Quantum Advantage Achieved with Dominik Hangleiter — A theorist's careful examination of what "quantum advantage" really means and whether it's been achieved — thematically central to Chan's work.
• Ep 35: Quantum Benchmarking with Jens Eisert — Eisert is one of the key figures in rigorous quantum benchmarking; his work on the limits of near-term devices complements Chan's argument about the absence of evidence for exponential advantage.

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