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This paper addresses the critical need for robust experiment tracking systems in quantum software development, highlighting how hardware noise and evolving algorithms require specialized monitoring practices. Through a case study on reservoir computing with error mitigation, it demonstrates methodologies to aggregate marginal gains and detect error sources essential for scaling quantum applications.
Systematic Experiment Tracking in Quantum Software: A Case Study of Reservoir Computing with Error Mitigation
arXiv:2607.24264v1 Announce Type: new Abstract: Quantum computers are more widely available than ever, making the field more accessible and widespread. Practitioners are coming from a wide range of domains, conducting experiments and research using quantum computing approaches across a variety of problems. The current literature suggests that developers follow certain methodologies in quantum software development, often with a matching set of tools provided. Yet with the novel paradigm, there are areas that remain unaddressed in practices and tools. In this article, we go into the details of experiment tracking in quantum software development. We explain the basic concept of experiment tracking and detail how, in essence, quantum computing sets demands on tracking practices. Given the experimental state of hardware and the constantly evolving software, quantum execution must be monitored, marginal gains aggregated for the best outcome, and error sources detected. In our case study, quantum reservoir computing for chaotic time series data prediction with error mitigation, we present a detailed quantum software development process and describe how experiments can be tracked throughout development. We then generalize this knowledge into the broader quantum development process.
Abstract:Quantum computers are more widely available than ever, making the field more accessible and widespread. Practitioners are coming from a wide range of domains, conducting experiments and research using quantum computing approaches across a variety of problems. The current literature suggests that developers follow certain methodologies in quantum software development, often with a matching set of tools provided. Yet with the novel paradigm, there are areas that remain unaddressed in practices and tools. In this article, we go into the details of experiment tracking in quantum software development. We explain the basic concept of experiment tracking and detail how, in essence, quantum computing sets demands on tracking practices. Given the experimental state of hardware and the constantly evolving software, quantum execution must be monitored, marginal gains aggregated for the best outcome, and error sources detected. In our case study, quantum reservoir computing for chaotic time series data prediction with error mitigation, we present a detailed quantum software development process and describe how experiments can be tracked throughout development. We then generalize this knowledge into the broader quantum development process.
Quantum Physics (quant-ph); Software Engineering (cs.SE)
arXiv:2607.24264 [quant-ph]
(or arXiv:2607.24264v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2607.24264 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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Full text under the publisher's open licence · 276 words
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