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Entropy
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Advances in Statistical Mechanics
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Advances in Statistical Mechanics

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Statistical Physics".

Deadline for manuscript submissions: closed (31 October 2010) | Viewed by 33562

Special Issue Editor

Dr. James Baker-Jarvis

E-Mail
Guest Editor
National Institute of Standards and Technology, 325 Broadway, MS 818.01, Boulder, CO, USA
Interests: dielectrics; electromagnetic properties of materials; maximum entropy methods; statistical mechanics; measurement of entropy

Special Issue Information

Dear Colleagues,

Entropy and its production are key concepts in statistical mechanics from both theoretical and experimental viewpoints. Fundamental studies of entropy need to be based on statistical mechanics. Many fields of study can be understood using entropy concepts. For example, when Einstein studied the photoelectric effect he based his analysis on a statistical mechanical analysis based on entropy. Similarly Planck relied heavily on the concept of entropy to produce his theory of energy quanta. The concepts of nonequilibrium thermodynamics, thermal noise, fluctuation-dissipation theorems, and information theory are all related to both statistical mechanics and entropy. Both Gibbs and Boltzmann placed the concepts of entropy and H-theorems in central positions in statistical mechanics. Statistical-mechanical studies based on either Liouville- based statistical mechanics or through approximate methods based on information theory utilize the concept of entropy. Novel papers studying entropy and its production in statistical mechanics from various points of view are welcome.

Dr. James Baker-Jarvis
Guest Editor

Keywords

  • entropy
  • noise
  • nonequilibrium
  • nonstationary processes
  • projection operators
  • statistical mechanics
  • thermodynamics

Published Papers (4 papers)

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138 KiB  
Article
Did the Federal Agriculture Improvement and Reform Act of 1996 Affect Farmland Values?
by Ashok K. Mishra, Grigorios T. Livanis and Charles B. Moss
Entropy 2011, 13(3), 668-682; https://doi.org/10.3390/e13030668 - 17 Mar 2011
Cited by 4 | Viewed by 7898
Abstract
Farmland values are affected by numerous factors, including farm policy, shifts in demand for agricultural output both foreign and domestic, monetary policy and urban pressure. In this study we use an information measure to examine whether the shift toward a more market-oriented policy [...] Read more.
Farmland values are affected by numerous factors, including farm policy, shifts in demand for agricultural output both foreign and domestic, monetary policy and urban pressure. In this study we use an information measure to examine whether the shift toward a more market-oriented policy in 1996 changed the relationship between farmland values and government payments. The results indicated that the shift in agricultural policy resulted in significant shift in this relationship. Full article
(This article belongs to the Special Issue Advances in Statistical Mechanics)
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450 KiB  
Article
A Maximum Entropy Modelling of the Rain Drop Size Distribution
by Ramiro Checa and Francisco J. Tapiador
Entropy 2011, 13(2), 293-315; https://doi.org/10.3390/e13020293 - 26 Jan 2011
Cited by 4 | Viewed by 8997
Abstract
This paper presents a maximum entropy approach to Rain Drop Size Distribution (RDSD) modelling. It is shown that this approach allows (1) to use a physically consistent rationale to select a particular probability density function (pdf) (2) to provide an alternative method for [...] Read more.
This paper presents a maximum entropy approach to Rain Drop Size Distribution (RDSD) modelling. It is shown that this approach allows (1) to use a physically consistent rationale to select a particular probability density function (pdf) (2) to provide an alternative method for parameter estimation based on expectations of the population instead of sample moments and (3) to develop a progressive method of modelling by updating the pdf as new empirical information becomes available. The method is illustrated with both synthetic and real RDSD data, the latest coming from a laser disdrometer network specifically designed to measure the spatial variability of the RDSD. Full article
(This article belongs to the Special Issue Advances in Statistical Mechanics)
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158 KiB  
Article
An Information Approach to the Dynamics in Farm Income: Implications for Farmland Markets
by Matthew J. Salois and Charles B. Moss
Entropy 2011, 13(1), 38-52; https://doi.org/10.3390/e13010038 - 24 Dec 2010
Cited by 8 | Viewed by 7423
Abstract
The valuation of farmland is a perennial issue for agricultural policy, given its importance in the farm investment portfolio. Despite the significance of farmland values to farmer wealth, prediction remains a difficult task. This study develops a dynamic information measure to examine the [...] Read more.
The valuation of farmland is a perennial issue for agricultural policy, given its importance in the farm investment portfolio. Despite the significance of farmland values to farmer wealth, prediction remains a difficult task. This study develops a dynamic information measure to examine the informational content of farmland values and farm income in explaining the distribution of farmland values over time. Full article
(This article belongs to the Special Issue Advances in Statistical Mechanics)
86 KiB  
Article
Tsallis Entropy, Escort Probability and the Incomplete Information Theory
by Amir Hossein Darooneh, Ghassem Naeimi, Ali Mehri and Parvin Sadeghi
Entropy 2010, 12(12), 2497-2503; https://doi.org/10.3390/e12122497 - 21 Dec 2010
Cited by 15 | Viewed by 8871
Abstract
Non-extensive statistical mechanics appears as a powerful way to describe complex systems. Tsallis entropy, the main core of this theory has been remained as an unproven assumption. Many people have tried to derive the Tsallis entropy axiomatically. Here we follow the work of [...] Read more.
Non-extensive statistical mechanics appears as a powerful way to describe complex systems. Tsallis entropy, the main core of this theory has been remained as an unproven assumption. Many people have tried to derive the Tsallis entropy axiomatically. Here we follow the work of Wang (EPJB, 2002) and use the incomplete information theory to retrieve the Tsallis entropy. We change the incomplete information axioms to consider the escort probability and obtain a correct form of Tsallis entropy in comparison with Wang’s work. Full article
(This article belongs to the Special Issue Advances in Statistical Mechanics)
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