AI RESEARCH
Bayesian Parameter Shift Rule in Variational Quantum Eigensolvers
arXiv CS.LG
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ArXi:2502.02625v2 Announce Type: replace Parameter shift rules (PSRs) are key techniques for efficient gradient estimation in variational quantum eigensolvers (VQEs). In this paper, we propose its Bayesian variant, where Gaussian processes with appropriate kernels are used to estimate the gradient of the VQE objective. Our Bayesian PSR offers flexible gradient estimation from observations at arbitrary locations with uncertainty information and reduces to the generalized PSR in special cases.