Testing the variational quantum eigensolver on the four-site Heisenberg model
Lorenzo Villani, Vincenzo Bisogno, Giuseppe De Riso, Vincenzo Bruno, Alfonso Romano, Canio Noce · 2023
We perform an optimization study of quantum computing methods specifically suited for the investigation of spin models. Our method is in particular applied to the Heisenberg model defined on a small cluster, in the case where a term describing the coupling of the spins to an external magnetic field is also included. The problem is studied referring to a square geometry by means of a quantum computer using the Variational Quantum Eigensolver (VQE). Differently from previous VQE applications, we exploit the Bayesian optimization, often used in machine learning, as a minimization procedure. Moreover, a post-processing error mitigation is implemented to improve the accuracy of the results.