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Quantum Optimization Quantum Machine Learning Quantum Chemistry

Interpolating Parametrized Quantum Circuits using Blackbox Queries

arXiv
Authors: Lars Simon, Holger Eble, Hagen-Henrik Kowalski, Manuel Radons

Year

2023

Paper ID

54067

Status

Preprint

Abstract Read

~2 min

Abstract Words

100

Citations

N/A

Abstract

This article focuses on developing classical surrogates for parametrized quantum circuits using interpolation via (trigonometric) polynomials. We develop two algorithms for the construction of such surrogates and prove performance guarantees. The constructions are based on circuit evaluations which are blackbox in the sense that no structural specifics of the circuits are exploited. While acknowledging the limitations of the blackbox approach compared to whitebox evaluations, which exploit specific circuit properties, we demonstrate scenarios in which the blackbox approach might prove beneficial. Sample applications include but are not restricted to the approximation of VQEs and the alleviaton of the barren plateau problem.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2023 reference point for readers tracking recent quantum research.
  • This article focuses on developing classical surrogates for parametrized quantum circuits using interpolation via (trigonometric) polynomials.

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References & Citation Signals

[1] DOI https://doi.org/arXiv:2310.04396 [2] arXiv https://arxiv.org/abs/2310.04396 [3] Publisher https://arxiv.org/abs/2310.04396

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