Quantum. Virginia Tech & Phasecraft.

Alexandria, VA
Joined December 2013
New paper with @MCrichigno at @Phasecraft. AI agents optimize quantum circuits, and an exact verifier checks every result. arxiv.org/abs/2610.31352 The challenge itself is automated too. An agent works with a researcher to build the verifier, tests it, and freezes it. Then the agents compete. We observed large gains on every problem we tried, from fermion-to-qubit encodings to qubit routing and unitary synthesis. The method applies to any problem with an exact checker. It's great to see others working in the same direction this week. Excellent papers from Google Quantum AI and Harvard/QuEra/Anthropic: arxiv.org/abs/2610.23832 arxiv.org/abs/2610.22367 and the inverse square root challenge: opensource.googleblog.com/20…
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FOR IMMEDIATE RELEASE: October 6th, 2026 OpenAI Releases the Final Ten Minutes of 500 Previously Unreleased Films, Ushering in a New Era of Movie Watching
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Def not a bot.
Replying to @S_Flammia
that's the cleanest use of ocneanu rigidity forcing quantum dilogarithm values algebraic i've seen
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Steve Flammia retweeted
There has been a number of remarkable works on Lindbladian learning this year, using advanced techniques and achieving impressive runtime guarantees. But is the whole Lindbladian learnable when there is SPAM noise?
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There is large & increasing interest in double sine, quantum dilogarithm, SF cocycle, and related functions, but no support in existing math libraries. I coded a robust, fast, multiprecision library, DoubleSine.jl, using midpoint balls & outward rounding for rigorous numerics.
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GitHub here: github.com/sflammia/DoubleSi… Feedback is welcome before I register it with Julia. This will eventually be incorporated into Zauner.jl and is much faster (and more general) than the current implementation of double sine used there.
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Steve Flammia retweeted
I hate to come back here to post this, but unfortunately this seems to be the place where most of the math & AI discussion is happening. Here are my immediate thoughts I just sent to the new Advisory Group on Mathematics and Artificial Intelligence. terrytao.wordpress.com/2026/…
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Steve Flammia retweeted
Replying to @S_Flammia
I'll try to add a bit of the tensor category side. To a finite group G you can assign its category of representations Rep(G), and this category has a "ring-like" structure because you can take tensor products. A fusion category is a "ring-like" category that "looks like" Rep(G)
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I’ve had several people ask me about this paper, so background 🧵 Radchenko–Wheeler, “Real quadratic fields and finite quantum dilogarithms I” (arxiv.org/abs/2609.21892). This result is amazing. They prove that certain special values of a transcendental function are actually algebraic. The goal of “explicit class field theory” is to construct algebraic numbers (numbers that are roots of polynomials with coefficients in ℤ), and ultimately abelian extensions of number fields, by evaluating transcendental functions at special points. It traces back to Hilbert's 12th problem. Ex 1: For ℚ, you have z = exp(2πix) at rational x. Clearly algebraic since z^n=1 if x=k/n. Ex 2: For imaginary quadratic fields, you have "complex multiplication". Take τ in the upper half-plane and Λ = ℤ + τℤ. Then ℂ/Λ is an elliptic curve. At imaginary quadratic (“CM”) values of τ, the transcendental modular function j(τ) (j-invariant) is an algebraic integer. Hilbert called CM "not only the most beautiful part of mathematics but also of the whole of science." If τ is real, this breaks completely because Λ = ℤ + τℤ is dense in ℝ (despite still being rank 2 as a ℤ-module). So ℂ/(ℤ+τℤ) is not a nice complex torus anymore and not an elliptic curve. This is one reason Hilbert’s 12th problem gets nasty immediately after ℚ and imaginary quadratic fields and is still almost totally open. (... in the Archimedean case. The p-adic case was proven by @samit_dasgupta and Kakde.) Stark and Shintani predicted that certain analytic quantities attached to real quadratic fields ("Stark units") should nonetheless be algebraic and generate abelian extensions. These can be written in terms of special values of Faddeev’s modular quantum dilogarithm, or a function Appleby, Kopp and I called "ש" (Shin), in homage to Shintani. Quantum dilogarithms are analytic objects, but are expected to satisfy special polynomial identities at certain special points. In our paper on Zauner's conjecture (arXiv:2501.03970), we gave a very explicit quadratic identity that they should satisfy ("the twisted convolution conjecture"), which, together with some more detailed conjectures of Stark, would prove Zauner in every dimension. Radchenko and Wheeler prove that the quantum dilogarithm indeed satisfies polynomial identities at certain special points. They also prove explicitly the twisted convolution conjecture for the case of the principal ideal (the admissible pair (d, ⟨1,1-d,1⟩) in the language of arXiv:2501.03970).  They claim the general case as well, though they omit the proof. Very interestingly, they prove the algebraicity by showing that the quantum dilogarithm maps to a fusion category, and since fusion categories obey "Ocneanu rigidity" they must be algebraic. Rigidity says, roughly, there are only finitely many equivalence classes with fixed fusion data and no continuous deformations. Because the structure constants solve polynomial equations over an algebraic field, that forces them into ℚ̅. Specifically, they say they "categorify Izumi fusion rings", but I don't know what that means and I look forward to understanding this better. Although they have proven algebraicity, they have not actually proven that their algebraic numbers are the "correct" ones, in the sense that "correct" Stark units should live in a specific field extension and have specific transformation properties under the action of the Galois group. This is left open. The consequences for Zauner's conjecture are: It's still completely open for any infinite family! To prove it, you would at least need to prove that there is a Galois automorphism in Gal(ℚ̅/ℚ) that takes the quantum dilogarithm special values to points on the unit circle. You might also need to prove some properties of the Galois group action; I will need to read this to understand it better. Congrats to the authors on a wonderful result!
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Ask an AI: “Download all papers by author X, then write a paper X would write, but better.” How much compute would you expect to spend before getting one X-quality paper? Call it Paper Replacement Inference Compute Expenditure: PRICE(X). “Better” could mean taste, execution, novelty, or impact. More precisely, PRICE(X) is the expected compute cost per new paper that a referee would judge is better than a typical paper by X. What is PRICE(X) for the median quantum information theorist today? How fast is it decreasing?
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Of course I asked AI my PRICE... it was higher than I expected, but I bet it was just flattering me.
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Agree 100%. In particular, the job of a PC is to select the *best program for the audience*, not the "best" papers. Having accessible talks across a broad range of topics is at least as important as recognizing the most impressive technical contributions.
Replying to @RobinKothari
Traditionally, QIP served many roles (e.g., disseminating important results and recognizing great work). AI is now forcing us to decouple some of these roles. I believe QIP's primary acceptance criterion should be: "Will this talk be a good use of the audience's time?" (2/4)
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"We solved the problem because there were rumors someone else had already done it." What other problems can be Kitaev'ed with enough compute? I guess we'll find out.
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Steve Flammia retweeted
Why doesn’t OpenAI use an equal amount of the money they spend to prove interesting conjectures in funding PhDs in the mathematical sciences? That way we will have a next generation of researchers that can understand these results and formulate the next wave of conjectures.
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Steve Flammia retweeted
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
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Can we agree on a place to post these papers? I think GitHub is a good idea for AI generated "announcements" with all-AI write-ups; arXiv for more refined and polished work which was, in the before-times, called "suitable for publication". Still need an aggregator though.
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