热力学计算机的热力学自由度
The thermodynamic freedom of a thermodynamic computer
- Lawrence Berkeley National Laboratory（劳伦斯伯克利国家实验室）
机构由 AI 辅助整理，请以论文原文为准。
中文总结 AI 辅助
研究针对特定任务的热力学计算机，用Wasserstein速度极限分析其热力学效率，发现不同推理协议可使其在精度无损失时达效率极限40%或快速推理，证明其热力学运行有较大自由度。
中文摘要 AI 辅助
热力学计算机是设计用于在热能尺度执行计算的随机物理装置，其运行受随机热力学方程约束，其中被称为速度极限的一组界限将热力学计算机的运行时间与其计算进展和耗散的热量关联。我们使用Wasserstein速度极限评估了一个经训练以执行标准机器学习分类任务的热力学计算机模拟模型的热力学效率，该任务中热力学计算机的性能与简单的多层感知机相当。我们表明，不同的推理协议可使该计算机在精度无损失的情况下，以达到热力学效率极限的40%运行，或在固定精度和热力学效率下实现更快的推理。这些结果表明，针对特定任务设计的热力学计算机在热力学运行方面保留了相当大的自由度。
英文摘要
Thermodynamic computers are stochastic physical devices designed to perform calculations at the thermal energy scale. Their operation is constrained by the equations of stochastic thermodynamics, among which are a set of bounds, known as speed limits, that relate a thermodynamic computer's run time to its computational progress and the heat it dissipates. Using the Wasserstein speed limit we assess the thermodynamic efficiency of a simulation model of a thermodynamic computer trained to perform a standard machine-learning classification task. On this task the thermodynamic computer is as capable as a simple multilayer perceptron. We show that different inference protocols allow the computer to operate within 40\% of the thermodynamic limit of efficiency without loss of accuracy, or to perform inference increasingly rapidly at fixed accuracy and thermodynamic efficiency. These results indicate that a thermodynamic computer designed for a particular task retains considerable freedom in its thermodynamic operation.
