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Bibliographic Details
Main Authors: Banchi, Leonardo, Branford, Dominic, Waghela, Chetan
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2510.05289
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Table of Contents:
  • Gradient-based optimization is a key ingredient of variational quantum algorithms, with applications ranging from quantum machine learning to quantum chemistry and simulation. The parameter-shift rule provides a hardware-friendly method for evaluating gradients of expectation values with respect to circuit parameters, but its applicability is limited to circuits whose gate generators have a particular spectral structure. In this work, we present a generalized framework that, with optimal minimum measurement overhead, extends parameter shift rules beyond this restrictive setting to encompass basically arbitrary gate generator, possibly made of complex multi-qubit interactions with unknown spectrum and, in some settings, even infinite dimensional systems such as those describing photonic devices or qubit-oscillator systems. Our generalization enables the use of more expressive quantum circuits in variational quantum optimization and enlarges its scope by harnessing all the available hardware degrees of freedom.