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Progressive quenching (PQ) is a process in which we sequentially fix a system's degrees of freedom, which would otherwise evolve according to their stochastic dynamics.
Time-dependent statistics of the Ising model
Roy J Glauber · 1963
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Studies in irreversible thermodynamics iv. diagrammatic representation of steady-state fluxes for unimolecular systems
Terrell L. Hill · 1966
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Network theory of microscopic and macroscopic behavior of master equation systems
Jürgen Schnakenberg · 1976
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Collective excitations and retarded interactions
MY Choi and BA Huberman · 1985
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Stochastic processes in physics and chemistry
Nicolaas Godfried Van Kampen · 1992
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The 1996 Wald Memorial lectures, stochastic models of interacting systems
Thomas M. Liggett · 1997
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Markov chains
James R Norris · 1998
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Lectures on Glauber dynamics for discrete spin models
Fabio Martinelli · 1999
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Irreversibility and heat generation in the computing process
R. Landauer · 2000
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Entropy production along a stochastic trajectory and an integral fluctuation theorem
Udo Seifert · 2005
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An introduction to stochastic processes with applications to biology
Linda JS Allen · 2010
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Stochastic processes for physicists: understanding noisy systems
Kurt Jacobs · 2010
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Stochastic Energetics (Lecture Notes in Physics, vol. 799)
Ken Sekimoto · 2010
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Fluctuation theorem for partially masked nonequilibrium dynamics
Naoto Shiraishi and Takahiro Sagawa · 2015
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Nonequilibrium thermodynamics of chemical reaction networks: wisdom from stochastic thermodynamics
Riccardo Rao and Massimiliano Esposito · 2016
Cited alongside, same era.
Progressive quenching: Globally coupled model
Bruno Ventéjou and Ken Sekimoto · 2018
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Probability and random processes
Geoffrey Grimmett and David Stirzaker · 2020
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Memory through a hidden martingale process in progressive quenching
Charles Moslonka and Ken Sekimoto · 2020
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Probability Theory: A Comprehensive Course
Achim Klenke · 2020
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What to learn from a few visible transitions’ statistics?
Pedro E. Harunari, Annwesha Dutta, Matteo Polettini, and Édgar Roldán · 2022
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Thermodynamic inference in partially accessible Markov networks: A unifying perspective from transition-based waiting time distributions
Jann van der Meer, Benjamin Ertel, and Udo Seifert · 2022
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Measurement-feedback formalism meets information reservoirs
Naoto Shiraishi, Takumi Matsumoto, and Takahiro Sagawa · 2016
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Incompatibility between Carnot efficiency and finite power in Markovian dynamics
Naoto Shiraishi and Keiji Saito · 2016
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Universal trade-off relation between power and efficiency for heat engines
Naoto Shiraishi, Keiji Saito, and Hal Tasaki · 2016
Cited alongside, same era.
Martingale-induced local invariance in progressive quenching
Charles Moslonka and Ken Sekimoto · 2022
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Édgar Roldán, Izaak Neri, Raphael Chetrite, Shamik Gupta, Simone Pigolotti, Frank Jülicher, and Ken Sekimoto · 2022
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