Computing canonical averages with quantum and classical optimizers: Thermodynamic reweighting for QUBO models of physical systems

We present a general method to compute canonical averages for physical models sampled via quantum or classical quadratic unconstrained binary optimization (QUBO). First, we introduce a histogram reweighting scheme applicable to QUBO-based sampling constrained to specific intervals of an order parameter, e.g., physical energy. Next, we demonstrate that the scheme can accurately recover the density of states, which in turn allows for calculating expectation values in the conjugate ensemble, e.g., at a fixed temperature. The method can thus be used to advance the state-of-the-art characterization of physical systems that admit a QUBO-based representation and that are otherwise intractable with real-space sampling methods. A case in point are space-filling melts of lattice ring polymers, recently mapped in QUBO form, for which our method reveals that the ring catenation probability is nonmonotonic with the bending rigidity.