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Erschienen in:
2022 | OriginalPaper | Buchkapitel
Compiling Single Round QCCP-X Quantum Circuits by Genetic Algorithm
verfasst von : Lis Arufe, Riccardo Rasconi, Angelo Oddi, Ramiro Varela, Miguel Ángel González
Erschienen in: Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence
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Abstract
The circuit model is one of the leading quantum computing architectures. In this model, a quantum algorithm is given by a set of quantum gates that must be distributed on the quantum computer over time, subject to a number of constraints. This process gives rise to the Quantum Circuit Compilation Problem (QCCP), which is in fact a hard scheduling problem. In this paper, we consider a compilation problem derived from the general Quantum Approximation Optimization Algorithm (QAOA) applied to the MaxCut problem and consider Noisy Intermediate Scale Quantum (NISQ) hardware architectures, which was already tackled in some previous studies. Specifically, we consider the problem denoted QCCP-X (QCCP with crosstalk constraints) and explore the use of genetic algorithms to solve it. We performed an experimental study across a conventional set of instances showing that the proposed genetic algorithm, termed \(GA_{X}\), outperforms a previous approach.