Cooling quantum systems is harder than it looks, study explains

Mimicking natural cooling processes in quantum systems proves surprisingly difficult, according to a new study of the challenges facing quantum simulators and processors. The work reveals that a fundamental assumption in statistical mechanics—that there is a vastly larger energy-absorbing system than the system itself—is often unmet in current, limited-size devices, leading to system recurrences instead of stable states. Researchers find that sampling from the equilibrium distribution with inverse temperature β, σ^β ∝ e^-βH^S, is a formidable algorithmic challenge despite the ease with which physical systems cool; this is further complicated by the quantum energy-time uncertainty relation limiting cooling speed. The study details how recent advances, including experiments on a Google…