Noise-robust exploration of quantum matter on near-term quantum devices

Johannes Borregaard, Matthias Christandl, Daniel Stilck França

Published 2019-09-10Version 1

We describe a resource-efficient approach to studying many-body quantum states on noisy, intermediate-scale quantum devices. We employ a sequential generation model that allows to bound the range of correlations in the resulting many-body quantum states. From this, we characterize situations where the estimation of local observables does not require the preparation of the entire state. Instead smaller patches of the state can be generated from which the observables can be estimated. This reduces the required circuit size and number of qubits for the computation of physical properties of quantum matter. Moreover, we show that the effect of noise decreases along the computation. Our results apply to a broad class of widely studied tensor network states and can be directly applied to near-term implementations of variational quantum algorithms.