A Roadmap for Automating the Selection of Quantum Computers for Quantum Algorithms

Abstract

Quantum computing can enable a variety of breakthroughs in research and industry in the future. Although some quantum algorithms already exist that show a theoretical speedup compared to the best known classical algorithms, the implementation and execution of these algorithms come with several challenges. The input data determines, e.g., the required number of qubits and gates of a quantum algorithm. An algorithm implementation also depends on the used Software Development Kit which restricts the set of usable quantum computers. Because of the limited capabilities of current quantum computers, choosing an appropriate one to execute a certain implementation for a given input is a difficult challenge that requires immense mathematical knowledge about the implemented quantum algorithm as well as technical knowledge about the used Software Development Kits. Thus, we present a roadmap for the automated analysis and selection of implementations of a certain quantum algorithm and appropriate quantum computers that can execute the selected implementation with the given input data.

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Cited by in corpus (10)

• The Bitter Truth About Quantum Algorithms in the NISQ Era
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• Architectural Vision for Quantum Computing in the Edge-Cloud Continuum
• MQT Predictor: Automatic Device Selection with Device-Specific Circuit Compilation for Quantum Computing
• Special Session: Noisy Intermediate-Scale Quantum (NISQ) Computers -- How They Work, How They Fail, How to Test Them?
• A Framework for Curriculum Transformation in Quantum Information Science and Technology Education
• An Overview of Quantum Software Engineering in Latin America
• ArsoNISQ: Analyzing Quantum Algorithms on Near-Term Architectures
• OrQstrator: An AI-Powered Framework for Advanced Quantum Circuit Optimization
• Distributing Quantum Computations, Shot-wise