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Entropy Change in Reversible Processes

Entropy Change in Reversible Processes

In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.

Entropy and the Second Law of Thermodynamics

Entropy and the Second Law of Thermodynamics

The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
The relation between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...

Entropy and the Second Law of Thermodynamics

Entropy and the Second Law of Thermodynamics

Consider an isolated system in which a hot object is placed in contact with a cold one. This is an irreversible process that eventually leads both objects to reach the same equilibrium temperature. It is crucial to note that the constituents of any substance exhibit increased disorder at higher temperatures. As a cold substance absorbs heat, its constituents become more disordered. The energy transfer from a hotter object to a cooler one increases the system's disorder or randomness. This...

Entropy Changes Accompanying Specific Processes

Entropy Changes Accompanying Specific Processes

Entropy, a measure of disorder in a system, changes during phase transitions like freezing or boiling. At the transition temperature Ttrs, where two phases are in equilibrium, the phase transition is a reversible process. The entropy change can be calculated from a substance's enthalpy of transition using the equation ΔStrs = ΔtrsH /Ttrs.When a perfect gas expands isothermally from one volume to another, entropy increases logarithmically with volume. Conversely, isothermal compression...

Entropy

Entropy

Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...

Entropy

Entropy

The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...

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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Nonadditive entropy maximization is inconsistent with Bayesian updating.

Steve Pressé¹

¹Department of Physics, IUPUI Indianapolis, Indiana 46202, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|December 11, 2014

Summary

This summary is machine-generated.

Nonadditive entropy maximization is incompatible with Bayesian updating, unlike the standard maximum entropy method. This finding highlights fundamental differences in probabilistic inference approaches.

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Area of Science:

Information Theory
Statistical Inference
Bayesian Methods

Background:

The maximum entropy method is a Bayesian inference technique grounded in logic.
The compatibility of nonadditive entropy maximization with Bayesian inference has not been established.

Purpose of the Study:

To determine if nonadditive entropy maximization is compatible with Bayesian updating.
To explore the implications of this compatibility for probabilistic model inference.

Main Methods:

Demonstration of incompatibility through theoretical analysis.
Focus on special cases for illustration.

Main Results:

Nonadditive entropy maximization is incompatible with Bayesian updating.
Established a key distinction between additive and nonadditive entropy methods in Bayesian frameworks.

Conclusions:

Nonadditive entropy maximization cannot be directly integrated into standard Bayesian inference.
The findings necessitate a re-evaluation of nonadditive entropy methods within the Bayesian paradigm.