Demonstration of a Compatibility-Based Childcare Support Service using Quantum Annealing

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Abstract In contemporary Japan, isolated parenting has become a serious social issue, increasing psychological stress on parents and potentially affecting children’s development. Existing childcare support services tend to focus on physical assistance, while psychological support and community connections remain insufficient.To address this gap, we developed a service that connects parents with senior community members who have parenting experience, aiming to provide psychological support and foster intergenerational exchange. Achieving high-quality matching requires considering pair compatibility, balancing supporter workload, and handling scheduling constraints, which can be formulated as a combinatorial optimization problem.We designed a matching framework using the Quadratic Unconstrained Binary Optimization (QUBO) formulation and evaluated quantum annealing (QA) against simulated annealing (SA). QA achieved higher solution quality and diversity, particularly for larger problem instances. Furthermore, a proof-of-concept field experiment conducted in Sendai City, Japan, demonstrated that the framework can generate multiple high-quality matching candidates, enabling flexible scheduling in real-world operations.
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Demonstration of a Compatibility-Based Childcare Support Service using Quantum Annealing | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Demonstration of a Compatibility-Based Childcare Support Service using Quantum Annealing Yuuma Matsumoto, Taisei Takabayashi, Rima Sato, Rumiko Honda, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7582372/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 11 You are reading this latest preprint version Abstract In contemporary Japan, isolated parenting has become a serious social issue, increasing psychological stress on parents and potentially affecting children’s development. Existing childcare support services tend to focus on physical assistance, while psychological support and community connections remain insufficient.To address this gap, we developed a service that connects parents with senior community members who have parenting experience, aiming to provide psychological support and foster intergenerational exchange. Achieving high-quality matching requires considering pair compatibility, balancing supporter workload, and handling scheduling constraints, which can be formulated as a combinatorial optimization problem.We designed a matching framework using the Quadratic Unconstrained Binary Optimization (QUBO) formulation and evaluated quantum annealing (QA) against simulated annealing (SA). QA achieved higher solution quality and diversity, particularly for larger problem instances. Furthermore, a proof-of-concept field experiment conducted in Sendai City, Japan, demonstrated that the framework can generate multiple high-quality matching candidates, enabling flexible scheduling in real-world operations. Physical sciences/Engineering Physical sciences/Mathematics and computing Biological sciences/Psychology Social science/Psychology Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 18 Feb, 2026 Reviews received at journal 15 Feb, 2026 Reviewers agreed at journal 29 Jan, 2026 Reviews received at journal 28 Jan, 2026 Reviewers agreed at journal 30 Dec, 2025 Reviewers agreed at journal 12 Nov, 2025 Reviewers invited by journal 13 Oct, 2025 Editor assigned by journal 08 Oct, 2025 Editor invited by journal 23 Sep, 2025 Submission checks completed at journal 20 Sep, 2025 First submitted to journal 20 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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