从信息方法看基本常数测量的不确定性和麦克斯韦妖

B. Menin
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引用次数: 3

摘要

本文提出了一种计算模型与观测到的工艺过程或物理现象差异的新框架。它为技术、工程和实验物理中应用的所有测量方法提供了强大的工具。由于验证和验证该现象模型的研究仍然很复杂,因此需要将它们合并为一个总体测量。到目前为止,几乎所有文献中使用的现有方法都暗示,使用超级计算机和最新的数学统计方法可以实现非常接近海森堡原理边界的高精度。为了比较改进模型的方法,我们提出了一个称为比较不确定性的新度量。这使我们能够证明模型与研究对象之间的可实现差异是有限的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Look at the Uncertainty of Measuring The Fundamental Constants and the Maxwell Demon from the Perspective of the Information Approach
This paper proposes a new framework for calculating the discrepancy of a model and the observed technological process or physical phenomenon. It offers powerful tools for all measurement methods applied in technology, engineering and experimental physics. Since the studies that validate and verificate the models of the phenomenon are still complex, they need to be combined into one total measure. Existing methods used in almost all literature up to the present time implicitly suggest that the use of supercomputers and the latest mathematical statistical methods allows achieving high accuracy very close to the boundaries of Heisenberg principle. To compare methodologies for improving models, we propose a new metric called comparative uncertainty. This allows us to prove that there is a limit to the achievable discrepancy between the model and the object under study.
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