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Warm-Starting Patterns for Quantum Algorithms

Authors:
Felix Truger
Johanna Barzen
Martin Beisel
Frank Leymann
Vladimir Yussupov

Keywords: Quantum Computing; Hybrid Algorithms; Quantum Software Engineering; Warm-Start; Patterns

Abstract:
Quantum computing promises considerable advantages in efficiency and accuracy over classical computing for certain problems. However, today's Noisy Intermediate-Scale Quantum (NISQ) computers are error-prone and limited in the number of qubits, which complicates leveraging them in practice. To mitigate these issues, multiple warm-starting techniques are being introduced in the quantum computing domain to improve the efficiency and accuracy of quantum algorithms by utilizing known or efficiently generated results as a starting point for the quantum computation. However, heterogeneous warm-starting techniques are often tailored for specific algorithms and require expertise in multiple domains, such as quantum computing and machine learning, thus complicating the choice of technique. Well-structured patterns that abstractly document proven solutions to recurring problems can help quantum software engineers in this decision-making process. In this work, we extend the existing pattern language for quantum algorithms with four novel warm-starting patterns that refine a more abstract pattern introduced in previous work and document how recurring problems in the design and execution of quantum algorithms can be solved with warm-starts. Thereby, the underlying methods are made available for interested parties in a concise and easily digestible manner.

Pages: 25 to 31

Copyright: Copyright (c) IARIA, 2024

Publication date: April 14, 2024

Published in: conference

ISSN: 2308-3557

ISBN: 978-1-68558-161-9

Location: Venice, Italy

Dates: from April 14, 2024 to April 18, 2024