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Matthew Schwartz's open-source harness matches large language models to the scientific problems they handle best
Harvard theoretical physicist Matthew D. Schwartz took a more practical route. On October 1, 2026, he released BootLoops 1.0, an open-source toolkit built on one premise: AI works best when you give it the right kind of problem.
Schwartz calls these problems “Claude-shaped” tasks. Over three months, he and his collaborators used that framing to turn out 36 manuscripts with 19 coauthors, drawn from a pool of 400 candidate problems.
What BootLoops actually does #
BootLoops is a modular harness for scientific calculation. It sits between a researcher and a large language model, such as Anthropic’s Claude.
The flagship use case is mathematical physics. The toolkit can compute 30 integrals end-to-end.
Half of those, 15 integrals, reproduce results that were already known. The other 15 are new, and they include elliptic Feynman integrals.
For non-physicists, Feynman integrals are the math behind how particles interact in quantum field theory. The elliptic kind are notoriously hard to evaluate.
Well beyond physics #
The project does not stop at particle physics. BootLoops reaches into roughly 18 to 22 different fields, including ecology, population genetics and cosmology.
Verification is central to the design. BootLoops produces its outputs as Python scripts, which return results to arbitrary precision.
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How it was built #
BootLoops grew out of an iterative process with Claude that began in December 2025. Schwartz started with Claude Opus 4.5.
By the summer of 2026, the workflow had moved to Claude Fable 5.
The launch followed a guest post by Schwartz on Anthropic’s blog titled “Claude-shaped science.” Anthropic published the piece.
Despite its origins, BootLoops is model-agnostic. It is designed to work with other LLMs, including Google’s Gemini and OpenAI’s ChatGPT.
The software ships under the MIT License.
Who is behind it #
Schwartz is a Professor of Physics at Harvard. His work spans quantum field theory, particle physics and machine learning.
He also wrote a textbook on Quantum Field Theory.
The toolkit is explicitly framed as research instrumentation. It is not intended for clinical, actuarial, regulatory or safety-critical decisions.
What this means for research #
The most useful idea in BootLoops may be the selection step, not the software. Starting from 400 candidate problems and producing 36 manuscripts implies a lot of filtering.
Disclosure: This article was edited by Diego Almada Lopez. For more information on how we create and review content, see our