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The optimization approach is broadened to determine not only the temperature of each unit but also the number of refrigeration stages necessary for a given system. The methodology allows grouping of multiple units within a single chamber, accommodating system specific performance requirements. Several optimization techniques, including advanced graph pruning and dynamic programming, are introduced and validated through quantum and cloud computing case studies.

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Integrated Multi-Temperature Cryogenic Computing Systems

  • 章节

  • 发表日期：

    2025年

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  • Nurzhan Zhuldassov,
  • Eby G. Friedman

摘要

The optimization approach is broadened to determine not only the temperature of each unit but also the number of refrigeration stages necessary for a given system. The methodology allows grouping of multiple units within a single chamber, accommodating system specific performance requirements. Several optimization techniques, including advanced graph pruning and dynamic programming, are introduced and validated through quantum and cloud computing case studies.