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arXiv 2308.08025quant-phcs.AIcs.ETcs.LGstat.ML
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基于模拟的能量受限量子-经典竞争评估

Simulation-Based Evaluation of Energy-Constrained Quantum-Classical Competition

University of Pittsburgh(匹兹堡大学);University of Toronto(多伦多大学);University of Hong Kong(香港大学)

Junyu Liu, Hansheng Jiang, Zuo-Jun Max Shen

AI总结:

本文开发基于模拟的框架,评估能源受限市场中量子与经典计算公司竞争的能量影响,刻画均衡并通过实验确定量子能量优势的适用场景。

摘要:

本文开发了一种基于模拟的框架,用于评估在能源资源有限的市场中量子计算公司与经典计算公司竞争的能量影响。我们将提供商建模为差异化的古诺竞争者,其可行服务容量由特定技术的能量缩放定律决定:实现等效计算目标的量子算法的能量缩放为多对数级,经典模拟的能量缩放为多项式级。对于量子公司与经典公司的对称组,均衡简化为一个易于处理的两方程系统,支持对市场规模、技术组合和硬件系数进行大规模场景扫描。我们刻画了容量受限的纳什均衡,证明存在一个需求规模,超过该规模后量子服务将变得更节能,并报告了针对离子阱和里德堡平台校准的数值实验。结果确定了量子能量优势仅为渐近的情况以及何时具有操作相关性的情况。

英文摘要:

This paper develops a simulation-based framework for evaluating the energy implications of quantum and classical computing firms competing in a market with limited energy resources. We model providers as differentiated Cournot competitors whose feasible service capacity is induced by technology-specific energy scaling laws: polylogarithmic for quantum algorithms that achieve an equivalent computational target and polynomial for classical emulation. For symmetric groups of quantum and classical firms, the equilibrium reduces to a tractable two-equation system that supports large scenario sweeps over market size, technology mix, and hardware coefficients. We characterize the capacity-constrained Nash equilibrium, prove the existence of a demand scale beyond which quantum service becomes more energy efficient, and report numerical experiments calibrated to trapped-ion and Rydberg platforms. The results identify when quantum energy advantage is only asymptotic and when it becomes operationally relevant.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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