"Pauli Propagation Assisted Probabilistic Error Cancellation" 

Abstract: Quantum Error Mitigation (QEM) aims to reduce the noise-induced bias in expectation values obtained from noisy quantum hardwares. Probabilistic Error Cancellation (PEC) is a widely used QEM technique that represents the inverse noise channel as a quasiprobabilistic combination of physically implementable operations, yielding an unbiased estimator at the cost of an exponential sampling overhead. Here, we use control variates, a standard variance-reduction technique from Monte Carlo methods, to substantially reduce the sampling overhead of PEC. Our control variates are obtained from classical approximations of the quantum circuit using Pauli propagation with weight truncation. Our results demonstrate that approximate classical simulations can be effectively combined with PEC to achieve substantial variance reduction while retaining the unbiasedness of the estimator.

Bio: Rajesh Mishra is a 5th year physics graduate student working with Bryan Clark on hybrid quantum-classical algorithms.