从匿名实验中盲发现热力学本体论
Blind Thermodynamic Ontology Discovery from Anonymous Experiments
- Northeastern University（东北大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出从匿名受控实验中盲发现热力学本体论的理论与多项式时间算法，通过复制对比、热接触和循环凹性提取广延/强度扇区并验证势能，在范德瓦尔斯流体等测试中稳健恢复，确立了观测等价极限并跨真实物质验证。
AI中文摘要：
在机器学习模型能够学习热力学状态方程之前，它必须发现其测量所代表的内容：哪些通道随系统规模缩放，哪些是强度共轭量，扇区如何通过接触配对，以及哪个势能控制稳定性。当传感器仅暴露广延状态与强度响应的未知线性混合时，被动观测无法将物理量从坐标伪影中区分出来。我们提出了直接从匿名受控实验中发现问题隐藏的热力学本体论的公式化描述。我们提出了一种可操作的辨识性理论以及一种构造性多项式时间算法，该算法从复制对比中提取广延和强度缩放扇区，通过热接触和互易性恢复其对偶余切配对，通过离散循环凹性验证全局容许的凹势能，并确定储层系综的不变拟阵。我们证明了残差观测等价性严格为 (x, λ) ~ (A x, a A^{-T} λ + β)，确立了任何允许的实验都无法打破的尖锐观测极限。对范德瓦尔斯流体和居里-外斯磁体的盲评估证实了在病态混合条件下的稳健恢复，正确解析了匿名的麦克斯韦结线，同时拒绝了非平衡延续。来自NIST WebBook的六种真实流体的外部验证表明，操作性本体论发现能够跨真实物理物质转移，而无需坐标泄漏。
英文摘要：
Before a machine learning model can learn a thermodynamic equation of state, it must discover what its measurements represent: which channels scale with system size, which are intensive conjugates, how sectors pair through contact, and which potential governs stability. When sensors expose only an unknown linear mixture of extensive states and intensive responses, passive observations cannot disentangle physical quantities from coordinate artifacts. We formulate the problem of discovering this hidden thermodynamic ontology directly from anonymous controlled experiments. We present an operational identifiability theory and a constructive polynomial-time algorithm that extracts extensive and intensive scaling sectors from replication contrasts, recovers their dual cotangent pairing from thermal contact and reciprocity, verifies a globally admissible concave potential via discrete cyclic concavity, and determines an invariant matroid of reservoir ensembles. We prove that the residual observational equivalence is strictly (x, lambda) ~ (A x, a A^{-T} lambda + beta), establishing the sharp observational limit that no permitted experiment can break. Blind evaluations on van der Waals fluids and Curie-Weiss magnets confirm robust recovery under ill-conditioned mixing, correctly resolving anonymous Maxwell tie-lines while rejecting non-equilibrium continuations. External validation across six real fluids from the NIST WebBook demonstrates that operational ontology discovery transfers across real physical substances without coordinate leakage.
