Quantum computers will need carefully designed circuits to run useful algorithms on limited hardware. Researchers gave Claude plain-language specifications for eight such circuits, drawn from chemistry, optimization, physics simulation, and number theory, along with an automated evaluator that checks and scores each design. Working largely on its own, Claude found designs that improve on the best published circuits, in some cases by an order of magnitude or more.
Such improvements substantially reduce the quantum resources that useful applications require, so practical quantum computers could arrive sooner than previously anticipated. The work was led by Andi Gu as part of Anthropic's STEM Fellows Program, with mentorship from Alek Kemeny, a quantum physicist at Anthropic, in collaboration with Susanne Yelin (Harvard University) and Mikhail Lukin (Harvard University and Qu Era Computing).
Unlike classical bits, which are either 0 or 1, qubits can be built from single atoms, superconducting circuits, or particles of light. They exploit phenomena such as superposition, allowing them to process information in ways that could make hard problems in chemistry, materials science, and number theory tractable. Today's machines have only hundreds to thousands of qubits, and they are highly sensitive to noise, so small errors accumulate and produce wrong answers. Because qubits and computing time are scarce, researchers are redesigning algorithms to use fewer resources.
An illustrative example is simulating FeMoco, the iron–sulfur cluster at the heart of nitrogenase, the enzyme bacteria use to turn nitrogen into ammonia. In 2017, researchers estimated a quantum computer would need about 50 trillion Toffoli gates to compute its ground-state energy. Through algorithmic advances, that estimate has fallen to about 340 million, a roughly 150,000-fold reduction, corresponding to a few hours of computation on a future machine with about three million physical qubits. Much of this gain came from redesigning circuits rather than improving hardware, which is why Claude's ability to optimize classical algorithms is promising here.
Source: Hacker News · Summarized by HeadlinesBriefing