Stochastic Thermodynamics: An Introduction

Cover
Contents
Foreword
Preface
Acknowledgments
Notation
Chapter 1. Motivation
	1.1 What is stochastic thermodynamics?
	1.2 Why does it work and why is it useful?
	1.3 Plan of the work
Chapter 2. Basics
	2.1 Thermodynamics
	2.2 Thermodynamic efficiency
	2.3 Free energy and nonequilibrium free energy
	2.4 Statistical mechanics
	2.5 Stochastic dynamics
	2.6 Master equations
	2.7 Trajectories of master equations
	2.8 Fokker-Planck equation (*)
	2.9 Langevin equation (*)
	2.10 Information
	2.11 Further reading
	2.12 Exercises
Chapter 3. Stochastic Thermodynamics
	3.1 The system
	3.2 Work and heat in stochastic thermodynamics
	3.3 Mesoscopic and calorimetric heat (*)
	3.4 ATP hydrolysis by myosin
	3.5 General reservoirs
	3.6 Stochastic entropy
	3.7 Stochastic entropy and entropy production in a manipulated two-level system
	3.8 Average entropy production rate
	3.9 Network theory of nonequilibrium steady states (*)
	3.10 Stochastic chemical reactions
	3.11 Linear response theory (*)
	3.12 More on coarse graining (*)
	3.13 Continuous systems (*)
	3.14 Further reading
	3.15 Exercises
Chapter 4. Fluctuation Relations
	4.1 Irreversibility and entropy production
	4.2 Integral fluctuation relation
	4.3 Dragged particle on a ring
	4.4 Back to linear response theory (*)
	4.5 Detailed fluctuation relation
	4.6 The Jarzynski and Crooks relations
	4.7 Instantaneous quench
	4.8 Fluctuation relations in practice
	4.9 Adiabatic and nonadiabatic entropy production and the Hatano-Sasa relation
	4.10 Systems with odd-parity variables
	4.11 Trajectory probability for Langevin equations (*)
	4.12 Fluctuation relation for the Langevin equation (*)
	4.13 Brownian particle in a time-dependent harmonic potential (*)
	4.14 Brownian motion with inertia (*)
	4.15 Hamiltonian systems (*)
	4.16 Further reading
	4.17 Exercises
Chapter 5. Thermodynamics of Information
	5.1 A brief history
	5.2 Back to nonequilibrium free energy
	5.3 Information in stochastic thermodynamics
	5.4 The Sagawa-Ueda relation
	5.5 The Mandal-Jarzynski machine
	5.6 Copying information
	5.7 Information cost in sensing
	5.8 Information reservoirs
	5.9 Fluctuation relations with information reservoirs (*)
	5.10 Further reading
	5.11 Exercises
Chapter 6. Large Deviations: Theory and Practice
	6.1 Large deviations in a nutshell
	6.2 Currents, traffic, and other observables
	6.3 Large deviations and fluctuation relations
	6.4 Fluctuation theorem for currents (*)
	6.5 Tilting
	6.6 Michaelis-Menten reaction scheme
	6.7 Fluctuation relations in a model of kinesin (*)
	6.8 Cloning (*)
	6.9 Levels of large deviations (*)
	6.10 Further reading
	6.11 Exercises
Chapter 7. Experimental Applications
	7.1 The hairpin as a paradigm
	7.2 A simpler model
	7.3 Equilibrium free energies from nonequilibrium manipulations
	7.4 Maxwell demons
	7.5 Landauer principle
	7.6 Further reading
Chapter 8. Developments
	8.1 Stochastic efficiency
	8.2 Uncertainty relations
	8.3 Applications of uncertainty relations
	8.4 First-passage times
	8.5 Fully irreversible processes
	8.6 Optimal protocols
	8.7 Martingales
	8.8 Random time
	8.9 Population genetics
	8.10 Further reading
	8.11 Exercises
Chapter 9. Perspectives
Appendixes
	A.1 Convex functions and the Jensen inequality
	A.2 Legendre transformation
	A.3 Probabilities and probability distributions
	A.4 Generating functions and cumulant generating functions
	A.5 Ergodic properties of Markov processes
	A.6 Gillespie algorithm
	A.7 Derivation of the Fokker-Planck equation
	A.8 Ito formula and Stratonovich-Ito mapping
	A.9 Basis of the cycle space
	A.10 Actions and trajectory probabilities for Langevin equations
	A.11 The Bennett-Crooks estimator for the free-energy difference
	A.12 Cauchy-Schwarz inequality
	A.13 Bound for the current rate function
Bibliography
Author Index
Index