Accounting for errors in quantum algorithms via individual error reduction

Abstract

We discuss a surprisingly simple scheme for accounting (and removal) of error in observables determined from quantum algorithms. A correction to the value of the observable is calculated by first measuring the observable with all error sources active and subsequently measuring the observable with each error source reduced separately. We apply this scheme to the variational quantum eigensolver, simulating the calculation of the ground state energy of equilibrium H2 and LiH in the presence of several noise sources, including amplitude damping, dephasing, thermal noise, and correlated noise. We show that this scheme provides a decrease in the needed quality of the qubits by up to two orders of magnitude. In near-term quantum computing, where full fault-tolerant error correction is too expensive, this scheme provides a route to significantly more accurate calculations.Quantum Computing: estimating and removing errors coming from the environmentThe errors in quantum computing can be strongly reduced exploiting partial removal and subsequent estimation of the residual error. Matthew Otten and Stephen Gray from Argonne National Laboratory have devised a simple scheme that should be able to greatly reduce the practical requirements for quantum devices in terms of cleanliness of operation, both for computation and for some quantum sensing protocol. The approach requires being able to actively reduce, of a certain amount, each error source separately, and measure the quantity to be calculated separately each time. Then, the authors show that it is possible to combine these noisy measurements together and get a reliable estimation of the noiseless result. Numerical simulations prove that the scheme would work for many different types of noise.