Researchers have developed a quantum algorithm based on system–bath interactions to prepare thermal and ground states for many-body physics, chemistry, and materials science applications, according to a peer-reviewed paper published in Nature Physics.
The algorithm relies entirely on forward evolution under a system–bath Hamiltonian where the bath is configured as a single reusable ancilla qubit. By tailoring the bath and interaction Hamiltonians, the study proves that the fixed point of the dynamical process accurately approximates the target quantum state. This single-qubit bath structure makes the technique suitable for implementation on early fault-tolerant quantum hardware.
The research team established theoretical guarantees on the algorithm's mixing time, providing formal proof for the end-to-end efficiency of system–bath models across physically relevant Hamiltonians. No new datasets were generated or analysed during the theoretical project.
Zhiyan Ding and Yongtao Zhan developed the original algorithm and contributed equally to the work. Ding, Zhan, and Lin Lin performed the theoretical analysis, while John Preskill and Lin supervised the overall project.
Contributing authors represent the University of Michigan, the California Institute of Technology, the AWS Center for Quantum Computing, the University of California, Berkeley, and Lawrence Berkeley National Laboratory. The paper was submitted on December 14, 2025, accepted on June 25, 2026, and published on August 12, 2026, with research support from the U.S. Department of Energy and the National Science Foundation.
