NQCP Life in Quantum - Michael Kastoryano

Quantum Gibbs sampling algorithms

Preparing ground states and thermal states is of key importance to simulating quantum systems on a quantum computer. Despite the hope for practical quantum advantage in quantum simulation, popular approaches like variational circuits or adiabatic algorithms appear to face serious difficulties. Monte-Carlo style quantum Gibbs samplers have emerged as an alternative, but prior proposals have been unsatisfactory due to technical obstacles related to energy-time uncertainty. We introduce simple continuous-time quantum Gibbs sampling algorithms that overcome these obstacles, while retaining favorable asymptotic scaling. Given the success of the classical Metropolis algorithm and the ubiquity of thermodynamics, we anticipate that quantum Gibbs sampling will become an important practical tool in quantum algorithm development.