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Special Issue "Advances in Statistical Mechanics"

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

Deadline for manuscript submissions: closed (31 October 2010)

Special Issue Editor

Guest Editor
Dr. James Baker-Jarvis

National Institute of Standards and Technology, 325 Broadway, MS 818.01, Boulder, CO, USA
E-Mail
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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Research

Open AccessArticle Did the Federal Agriculture Improvement and Reform Act of 1996 Affect Farmland Values?
Entropy 2011, 13(3), 668-682; doi:10.3390/e13030668
Received: 4 March 2011 / Revised: 13 March 2011 / Accepted: 14 March 2011 / Published: 17 March 2011
PDF Full-text (138 KB) | HTML Full-text | XML Full-text
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
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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)
Open AccessArticle A Maximum Entropy Modelling of the Rain Drop Size Distribution
Entropy 2011, 13(2), 293-315; doi:10.3390/e13020293
Received: 30 December 2010 / Revised: 13 January 2011 / Accepted: 20 January 2011 / Published: 26 January 2011
Cited by 3 | PDF Full-text (450 KB) | HTML Full-text | XML Full-text
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
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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)
Open AccessArticle An Information Approach to the Dynamics in Farm Income: Implications for Farmland Markets
Entropy 2011, 13(1), 38-52; doi:10.3390/e13010038
Received: 9 November 2010 / Revised: 17 December 2010 / Accepted: 22 December 2010 / Published: 24 December 2010
Cited by 3 | PDF Full-text (158 KB) | HTML Full-text | XML Full-text
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
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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)
Open AccessArticle Tsallis Entropy, Escort Probability and the Incomplete Information Theory
Entropy 2010, 12(12), 2497-2503; doi:10.3390/e12122497
Received: 31 October 2010 / Revised: 25 November 2010 / Accepted: 27 November 2010 / Published: 21 December 2010
Cited by 5 | PDF Full-text (86 KB) | HTML Full-text | XML Full-text
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
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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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