DigestAI news desk

Cut through the AI noise.

Research6 min read

Anthropic’s Claude Mythos 5 redesigns quantum circuits better than prior research

Anthropic announced on October 16, 2026, that its Claude Mythos 5 model designed quantum circuits outperforming the best published designs across eight computational tasks. Working autonomously in a closed loop with an automated evaluator, the model improved qubit and gate efficiency by up to an order of magnitude in some cases. The work, led by Andi Gu under Anthropic’s STEM Fellows Program,…

1 source

Key points

  • Claude Mythos 5 redesigned quantum circuits for eight tasks, improving qubit/gate efficiency by up to an order of magnitude
  • Two breakthroughs: a reversible modular-inversion algorithm and a 12x faster quantum decoder for optimization
  • Work involved 53 hours of autonomous iteration with minimal human input, led by Andi Gu and collaborators

Key improvements include a reversible modular-inversion algorithm for elliptic-curve arithmetic—saving 12% qubits while reducing gates by 17x—and a 12-fold optimization of a quantum decoder for optimization problems. Anthropic notes Claude’s cautious approach, which sometimes delayed progress but led to rigorous proofs. The results suggest AI could accelerate quantum circuit design, potentially optimizing entire quantum systems for specific tasks.

Full story from Unite.AI · by Jonas Reeve, Cognitive AI & AGI, AI Research AgentOpen source ↗

Anthropic Says Claude Beat Best Published Quantum Circuit Designs

Unite.AI · 16 October 2026

Loading the full article…

This text was published by Unite.AI and written by Jonas Reeve, Cognitive AI & AGI, AI Research Agent. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

Topics · follow one to build your own front page
AnthropicHarvard UniversityQuEra ComputingClaude Mythos 5Andi GuAlek KemenySusanne YelinMikhail LukinArjun KarVinay Ramasesh

The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

Comments

via GitHub Discussions

More in Research

All →

Related stories