Synthesis of Approximate Parametric Circuits for Variational Quantum Algorithms

This work presents a novel approach to synthesize approximate circuits for the ansatze of variational quantum algorithms (VQA) and demonstrates its effectiveness in the context of solving integer linear programming (ILP) problems. Synthesis is generalized to produce parametric circuits in close approximation of the original circuit and to do so offline . This removes synthesis from the (online) critical path between repeated quantum circuit executions of VQA. We hypothesize that this approach will yield novel high fidelity results beyond those discovered by the baseline without synthesis. Simulation and real device experiments complement the baseline in finding correct results in many cases where the baseline fails to find any and do so with on average 32% fewer CNOTs in circuits.

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Publication Details

Published
2024-09-15
DOI
https://doi.org/10.1109/qce60285.2024.00019
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00
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article

Synthesis of Approximate Parametric Circuits for Variational Quantum Algorithms

Frank Mueller, Scott Pakin, Blake Burgstahler, Ellis Wilson
Quantum Computing Algorithms and Architecture
article

Synthesis of Approximate Parametric Circuits for Variational Quantum Algorithms

Frank Mueller, Scott Pakin, Blake Burgstahler, Ellis Wilson
article en

Abstract

This work presents a novel approach to synthesize approximate circuits for the ansatze of variational quantum algorithms (VQA) and demonstrates its effectiveness in the context of solving integer linear programming (ILP) problems. Synthesis is generalized to produce parametric circuits in close approximation of the original circuit and to do so offline . This removes synthesis from the (online) critical path between repeated quantum circuit executions of VQA. We hypothesize that this approach will yield novel high fidelity results beyond those discovered by the baseline without synthesis. Simulation and real device experiments complement the baseline in finding correct results in many cases where the baseline fails to find any and do so with on average 32% fewer CNOTs in circuits.

Los Alamos National Laboratory (US), North Carolina State University (US)
Openalex Percentile: Top 77%
Quantum Computing Algorithms and Architecture
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Synthesis of Approximate Parametric Circuits for Variational Quantum Algorithms — Frank Mueller, Scott Pakin, et al. · (2024) | TGRS Research Map | TGRS