Causal Modeling and Thermodynamics: Towards a new convergence of the two fields

IF 2 4区 生物学 Q2 BIOLOGY
Dan Costa Baciu
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引用次数: 0

Abstract

In 1824, Nicolas Léonard Sadi Carnot paid for the publication of his first book. Unfortunately it sparked little interest, and the young engineer never published another. In quick succession, Carnot served in the military, suffered from scarlet fever, mania, and cholera, and passed away in obscurity at age 36. Two centuries have elapsed since Carnot published his only book. Recognition came later. In particular, Carnot's reasoning inspired scientists to formulate the first and second laws of Thermodynamics. The new science that has emerged around these physical laws is nothing short of breathtaking. Yet, with success and growth, critical attention and skepticism have followed. In 1924, Louis de Broglie lauded the first law of Thermodynamics, while remaining more reserved to wards the second. The first law builds on a long history rooted in Causal Modeling, while the second does less so. Today, physicists such as Adrian Bejan continue praising Thermodynamics but contend that some formulations of the second law may have attracted broken science. The present article revisits this history in an attempt to cut through some of the fog. As an outcome of this re-evaluation, the article outlines a new convergence of Thermodynamics and Causal Modeling.
因果建模与热力学:实现两个领域的新融合。
1824 年,尼古拉-莱昂纳尔-萨迪-卡诺花钱出版了自己的第一本书。遗憾的是,这本书几乎没有引起人们的兴趣,这位年轻的工程师再也没有出版过新书。随后,卡诺先后服兵役、患猩红热、狂躁症和霍乱,在默默无闻中去世,享年36岁。自卡诺出版他唯一的著作以来,已经过去了两个世纪。人们对他的认识是后来的事。特别是,卡诺的推理引领了热力学第一和第二定律的发展。围绕这些物理定律产生的新科学令人叹为观止,是人类创造力的绝佳见证。然而,成功和发展也带来了批评和质疑。1924 年,路易-德-布罗格利对热力学第一定律的赞誉超过了第二定律。第一定律建立在因果建模的悠久历史之上,而第二定律则不然。如今,物理学家阿德里安-贝扬(Adrian Bejan)等人专门研究热力学,但他认为,第二定律的某些表述可能已经破坏了科学。本文重温这段历史,试图拨开一些迷雾。作为重新评估的结果,文章概述了热力学与因果建模的新融合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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