Noise Resilience of Variational Quantum Compiling

摘要: Variational hybrid quantum-classical algorithms (VHQCAs) are near-term that leverage classical optimization to minimize a cost function, which is efficiently evaluated on quantum computer. Recently VHQCAs have been proposed for compiling, where target unitary $U$ compiled into short-depth gate sequence $V$. In this work, we report surprising form of noise resilience these algorithms. Namely, find one often learns the correct $V$ (i.e., variational parameters) despite various sources incoherent acting during cost-evaluation circuit. Our main results rigorous theorems stating optimal parameters unaffected by broad class models, such as measurement noise, and Pauli channel noise. Furthermore, our numerical implementations IBM's noisy simulator demonstrate when compiling Fourier transform, Toffoli gate, W-state preparation. Hence, due its robustness, could be practically useful intermediate-scale devices. Finally, speculate may general phenomenon applies other eigensolver.