scholarly journals Identifying apparent local stable isotope equilibrium in a complex non-equilibrium system

2018 ◽  
Vol 32 (4) ◽  
pp. 306-310 ◽  
Author(s):  
Yuyang He ◽  
Xiaobin Cao ◽  
Jianwei Wang ◽  
Huiming Bao
Keyword(s):  
Stable Isotope ◽  
Equilibrium System ◽  
Isotope Equilibrium ◽  
Non Equilibrium

scholarly journals Fluctuation Theorem of Information Exchange between Subsystems that Co-Evolve in Time

Symmetry ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 433 ◽  
Author(s):  
Lee Jinwoo
Keyword(s):  
Information Exchange ◽  
Degrees Of Freedom ◽  
Fluctuation Theorem ◽  
Equilibrium System ◽  
Dynamic Coupling ◽  
Stochastic Thermodynamics ◽  
Exchange Processes ◽  
Exchange Information ◽  
Non Equilibrium

Sagawa and Ueda established a fluctuation theorem of information exchange by revealing the role of correlations in stochastic thermodynamics and unified the non-equilibrium thermodynamics of measurement and feedback control. They considered a process where a non-equilibrium system exchanges information with other degrees of freedom such as an observer or a feedback controller. They proved the fluctuation theorem of information exchange under the assumption that the state of the other degrees of freedom that exchange information with the system does not change over time while the states of the system evolve in time. Here we relax this constraint and prove that the same form of the fluctuation theorem holds even if both subsystems co-evolve during information exchange processes. This result may extend the applicability of the fluctuation theorem of information exchange to a broader class of non-equilibrium processes, such as a dynamic coupling in biological systems, where subsystems that exchange information interact with each other.

Simulating surface tension in a non-equilibrium system

Scilight ◽  
2019 ◽  
Vol 2019 (17) ◽  
pp. 170006
Author(s):  
Stacy W. Kish
Keyword(s):  
Surface Tension ◽  
Equilibrium System ◽  
Non Equilibrium

Microscopic-Shock Profiles: Exact Solution of a Non-equilibrium System

1993 ◽  
Vol 22 (9) ◽  
pp. 651-656 ◽  
Author(s):  
B Derrida ◽  
S. A Janowsky ◽  
J. L Lebowitz ◽  
E. R Speer
Keyword(s):  
Exact Solution ◽  
Equilibrium System ◽  
Shock Profiles ◽  
Non Equilibrium

Many Entropies, Many Disorders

2003 ◽  
Vol 10 (03) ◽  
pp. 281-296 ◽  
Author(s):  
Matt Davison ◽  
J. S. Shiner
Keyword(s):  
Maximum Entropy ◽  
Spin System ◽  
Hierarchical Structures ◽  
Absolute Maximum ◽  
Equilibrium System ◽  
Random System ◽  
Equiprobable Distribution ◽  
Non Equilibrium

To overcome the deficits of entropy as a measure for disorder when the number of states available to a system can change, Landsberg defined “disorder” as the entropy normalized to the maximum entropy. In the simplest cases, the maximum entropy is that of the equiprobable distribution, corresponding to a completely random system. However, depending on the question being asked and on system constraints, this absolute maximum entropy may not be the proper maximum entropy. To assess the effects of interactions on the “disorder” of a 1-dimensional spin system, the correct maximum entropy is that of the paramagnet (no interactions) with the same net magnetization; for a non-equilibrium system the proper maximum entropy may be that of the corresponding equilibrium system; and for hierarchical structures, an appropriate maximum entropy for a given level of the hierarchy is that of the system which is maximally random, subject to constraints deriving from the next lower level. Considerations of these examples leads us to introduce the “equivalent random system”: that system which is maximally random consistent with any constraints and with the question being asked. It is the entropy of the “equivalent random system” which should be taken as the maximum entropy in Landsberg's “disorder”.

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