Empirical Sample Complexity of Neural Network Mixed State Reconstruction

arXiv:2307.01840v2 Announce Type: replace-cross
Abstract: Quantum state reconstruction using Neural Quantum States has been proposed as a viable tool to reduce quantum shot complexity in practical applications, and its advantage over competing techniques has been shown in numerical experiments focusing mainly on the noiseless case. In this work, we numerically investigate the performance of different quantum state reconstruction techniques for mixed states: the finite-temperature Ising model. We show how to systematically reduce the quantum resource requirement of the algorithms by …

abstract applications arxiv case complexity cs.lg mixed network neural network numerical physics.comp-ph practical quant-ph quantum reduce replace sample state tool type work