Anthropic says Claude Mythos 5 autonomously optimized eight quantum-circuit primitives after receiving plain-language specifications and feedback from an automated evaluator. The system generated circuit designs for chemistry, optimization, quantum simulation, number theory, and numerical computing that Anthropic says used fewer qubits and gates than previously published designs. The work was led by Andi Gu through Anthropic’s STEM Fellows Program with collaborators including Harvard’s Susanne Yelin and Mikhail Lukin. In a 53-hour run, Claude developed a reversible modular-inversion method for elliptic-curve point addition. It derived a way to recover divsteps branch information from the numerical state rather than storing the full history. Anthropic says one resulting design uses 12% more qubits than the smallest earlier circuit while requiring 17 times fewer gates, expanding the available qubit-runtime trade-offs. Claude also redesigned the Reed–Solomon decoding step in decoded quantum interferometry, replacing an extended-Euclidean construction with Berlekamp–Massey decoding. A simulator tested 403 million sample decodings and found that reserving 19 qubits for one exceptional value was sufficient for nearly all runs; about one in 10,000 runs exceeded that capacity and failed within the allowed error rate. Anthropic says the decoder uses 12 times fewer gates than Google’s prior construction.

The Indian Institute of Science has implemented a neuromorphic Ising machine on an FPGA board that rapidly explores complex energy landscapes, facilitating the discovery of near-optimal solutions for optimization problems like protein folding. This machine computes in a manner that mimics natural processes, addressing challenges that traditional computing cannot efficiently solve.