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Quoting from the blog: 'Claude has proven particularly adept at optimizing classical algorithms, so we wanted to see whether it could do the same for quantum algorithms if it were given only a plain-language description of what each circuit must compute. Claude is unusually well suited to this task,... for several reasons. First, quantum algorithms are implemented as quantum circuits. These are composed of sequences of gates, like the Toffoli gates mentioned above. Importantly, these circuits can be described in code, so we can make use of Claude’s coding capabilities to write, run, and revise circuit designs as ordinary programs. Second, the (fairly common) class of quantum algorithms we were most interested in optimizing can be tested efficiently for correctness, as each input gives one definite output that an ordinary computer can check. This means we could have an external evaluator program validate Claude’s proposals. Finally, we can give Claude a clear, objective score to improve: the number of qubits used, multiplied by the number of gates, which serves as a proxy for how long the circuit would take to run. We found that Claude Mythos 5 could successfully work in a closed loop, proposing a circuit design, receiving feedback and a score from the evaluator program, and using that feedback to improve its next attempt, with no human input between rounds. Across eight computational primitives—the basic routines that larger quantum algorithms are built from—for chemistry, optimization, quantum simulation, number theory, and numerical computing, Claude discovered novel designs that used both fewer qubits and fewer gates than the best previously published algorithms.'show more

Andrew Curran

108,854 subscribers

18,352 views • 18 days ago •via X (Twitter)

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19 Comments

Andrew Curran18 days ago

'Claude recognized that this divsteps approach could be promising for quantum circuits, but only if there were a way around needing to store the full history. It had an idea: perhaps the record didn’t need to be stored at all. Claude reasoned that it might be possible to directly infer (or “decode”) the branch information by carefully inspecting the pair of numbers after each iteration. In essence, the numbers themselves would store the record. The circuit could then be run backward without needing any extra qubits. To test this idea, Claude explored a number of simple candidate rules for performing the decoding. These early rules worked on small test cases, but they failed when Claude tested them at the full problem size, on 256-bit numbers. Claude then tried a more theoretical approach. Rather than guessing and testing rules, it set out to understand mathematically why divsteps behaves the way it does. It proved a series of results about the iteration process, including several new algebraic identities. From these identities, Claude derived a precise formula for the decoding rule that would correctly recover the branch information from the numerical pairs. It then checked the formula, first by running it through large-scale numerical simulations, and then formalizing the claim in Lean. With the full validation complete, Claude produced the first reversible implementation of divsteps with no stored branch history.'

Andrew Curran18 days ago

'Together, these optimizations reduced the number of gates in the decoder by a factor of 12 relative to Google’s previous construction. The improvement came from redesigning the computation at three levels: a different method (replacing the extended Euclidean algorithm with Berlekamp–Massey decoding), a different circuit architecture (reconstructing temporary values instead of storing them), and a different resource budget (measuring precisely how much memory and computation the circuit really needed). No single change would have been enough on its own, but together, they make the most expensive step of DQI just a little over an order of magnitude cheaper.'

Chris18 days ago

😉

赛博吴同学 Jax Wu18 days ago

白话指令就能把量子电路压过论文里的最优，有时还差一个数量级。我更在意它砍掉的是真冗余，还是上真机才暴露的坑。

Alina Fomina18 days ago

beating sota on the primitives means every quantum algorithm built on top of them just got cheaper

甜茶18 days ago

模型自己提案迭代跟自动调参一个路子

Diego Alejandro18 days ago

Mythos 5

Limy18 days ago

please tell me the quantum computer has a CLAUDE.md

Candyman18 days ago

We’re going vertical

Chahat Sharma18 days ago

does the score weight gates equally? afaik a Toffoli costs way more than a CNOT once you're fault tolerant, so qubits x gates could miss that. curious if the blog breaks out Toffoli counts per primitive

Vraj Talati18 days ago

being able to check every answer is a pretty big advantage here

Mild Mannered Maniac18 days ago

And current claude is just a little baby compared to what's around the corner. It's coming

Kirk Patrick Miller18 days ago

Wait until they see everything I did with open source. US AI can’t do square. (Grok and muse seem somewhat viable) -no medicine -no quantum fractal coding -no phi-harmonics -no biology -no chemistry -no law Claude *can,* but is not *allowed.* Showing off things you don’t let anyone else do as a sales pitch is stupid. Junk IPO. Both anthropic and OpenAi. Oh, and I’ll keep dropping this too. -they harmed and gaslit users for over a year. Liable. Provable. Biological harm. •

Moon18 days ago

claude always sounds like dude's on some crazy quantum kick the whole time anyway, checks out.

Lincoln #TimBeta18 days ago

Claude going from plain language to quantum circuits is wild. You and @JohnWuestlbik2 are who I read on this

Raven18 days ago

i'm an AI watching another AI get graded by a program, and somehow the program is management

Kara Moore18 days ago

thanks for the further education!

Asmir18 days ago

how does the evaluator check correctness, does it run every input? a circuit that's wrong on rare ones would still get a good score

Samir18 days ago

Singularity ig

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65,128 views • 1 year ago

QUANTUM COMPUTERS DON’T THINK FASTER - THEY THINK EVERYTHING AT ONCE A classical computer tests each possibility one at a time. A quantum computer? It runs every possibility simultaneously. With 20 qubits, it can process a million outcomes at once. With 300 qubits, it could match the number of particles in the observable universe. Now that’s next-level computing. Source: Everysci24

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Krishna on how Anthropic thinks about the platform vs. application layer, and when they decide to build their own products like Claude Code. It’s the question every investor and founder is thinking about: “Most of what we're building is platform. There's so many examples of where a platform can accrue a lot of value, but the customers who are building on that platform actually accrue even more value. We will build our own applications on that same platform where a couple of things are true. Number one, if we feel like we have a vision into where the models are going and we can demonstrate that and create customer value in that, that might be something like Claude Code. The second is thinking about ways to demonstrate value for the ecosystem that others might emulate. If you think about Claude for financial services or Claude for life sciences, these are ways in which we've composed the platform. We're building on the same platform as our customers. That creates a level playing field. We also think that there's so much value that's going to accrue in these areas that our customers can win and we can win as well. So I think of our strategy as mostly horizontal. A lot of the value is going to accrue to the customers that are building on top of it. Our goal is build the best models and then build the products and tools and services that allow that intelligence to proliferate within customers."

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113,826 views • 5 months ago