Lagrangian formulation of irreversible thermodynamics, and the second law of thermodynamics
K. S. Glavatskiy

TL;DR
This paper introduces a variational principle-based Lagrangian formulation for irreversible thermodynamics, linking microscopic reversibility with the second law through symmetric Lagrangians involving normal and mirror-image systems.
Contribution
It presents a novel Lagrangian approach that derives irreversible evolution equations and explains the second law via symmetry considerations in thermodynamics.
Findings
Derivation of irreversible evolution equations from a variational principle.
Demonstration that the second law follows from Lagrangian symmetry.
Introduction of a mirror-image system concept balancing entropy changes.
Abstract
We show that the equations which describe irreversible evolution of a system can be derived from a variational principle. We suggest a Lagrangian, which depends on the properties of the normal and the so-called "mirror-image" system. The Lagrangian is symmetric in time and therefore compatible with microscopic reversibility. The evolution equations in the normal and mirror-imaged systems are decoupled and describe therefore independent irreversible evolution of each of the systems. The second law of thermodynamics follows from a symmetry of the Lagrangian. Entropy increase in the normal system is balanced by the entropy decrease in the mirror-image system, such that there exist an "integral of evolution" which is a constant. The derivation relies on the property of local equilibrium, which states that the local relations between the thermodynamic quantities in non-equilibrium are the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Thermodynamics and Statistical Mechanics · Mathematical Biology Tumor Growth · Statistical Mechanics and Entropy
