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Optimizing quantum circuits with Riemannian gradient flow

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arxiv 2202.06976 v2 pith:OOCNQHRO submitted 2022-02-14 quant-ph

Optimizing quantum circuits with Riemannian gradient flow

classification quant-ph
keywords quantumcircuitsgroupoptimizationriemannianalgorithmalgorithmsparameters
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Variational quantum algorithms are a promising class of algorithms that can be performed on currently available quantum computers. In most settings, the free parameters of a variational circuit are optimized using a classical optimizer that updates parameters in Euclidean geometry. Since quantum circuits are elements of the special unitary group, we can consider an alternative optimization perspective that depends on the structure of this group. In this work, we investigate a Riemannian optimization scheme over the special unitary group and we discuss its implementation on a quantum computer. We illustrate that the resulting Riemannian gradient-flow algorithm has favorable optimization properties for deep circuits and that an approximate version of this algorithm can be performed on near-term hardware.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. PennyLane: Automatic differentiation of hybrid quantum-classical computations

    quant-ph 2018-11 accept novelty 6.0

    PennyLane is a software library extending automatic differentiation to hybrid quantum-classical systems for variational quantum algorithms.