scholarly journals An Information Theory Approach to Nonlinear, Nonequilibrium Thermodynamics

2011 ◽  
Vol 145 (2) ◽  
pp. 385-409 ◽  
Author(s):  
David M. Rogers ◽  
Thomas L. Beck ◽  
Susan B. Rempe
1973 ◽  
Vol 40 (4) ◽  
pp. 868-872 ◽  
Author(s):  
Y. M. El-Sayed

This is an attempt to establish a simple approach to nonequilibrium thermodynamics. A generalized entropy is formulated from an information theory viewpoint and from a thermodynamic viewpoint. Rate laws, coupling phenomena, equality of cross coefficients, and a criterion for the changes of the steady state, all emerge when the maximum entropy of information is linearly related to the thermodynamic entropy. The results are not strictly new but their integration in one simple approach is believed to be novel.


2019 ◽  
Author(s):  
Miguel Equihua Zamora ◽  
Mariana Espinosa ◽  
Carlos Gershenson ◽  
Oliver López-Corona ◽  
Mariana Munguia ◽  
...  

We review the concept of ecosystem resilience in its relation to ecosystem integrity from an information theory approach. We summarize the literature on the subject identifying three main narratives: ecosystem properties that enable them to be more resilient; ecosystem response to perturbations; and complexity. We also include original ideas with theoretical and quantitative developments with application examples. The main contribution is a new way to rethink resilience, that is mathematically formal and easy to evaluate heuristically in real-world applications: ecosystem antifragility. An ecosystem is antifragile if it benefits from environmental variability. Antifragility therefore goes beyond robustness or resilience because while resilient/robust systems are merely perturbation-resistant, antifragile structures not only withstand stress but also benefit from it.


1987 ◽  
Vol 19 (3) ◽  
pp. 385-394 ◽  
Author(s):  
J R Roy

In the use of information theory for the development of forecasting models, two alternative approaches can be used, based either on Shannon entropy or on Kullback information gain. In this paper, a new approach is presented, which combines the usually superior statistical inference powers of the Kullback procedure with the advantages of the availability of calibrated ‘elasticity’ parameters in the Shannon approach. Situations are discussed where the combined approach is preferable to either of the two existing procedures, and the principles are illustrated with the help of a small numerical example.


2019 ◽  
Vol 159 (1) ◽  
pp. 16
Author(s):  
Javiera Astudillo ◽  
Pavlos Protopapas ◽  
Karim Pichara ◽  
Pablo Huijse

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