Luca Peliti is deputy director of the Santa Marinella Research Institute and professor emeritus of statistical mechanics at the University of Naples Federico II. He is the author of Statistical Mechanics in a Nutshell (Princeton). Simone Pigolotti is associate professor at the Okinawa Institute of Science and Technology, where he leads the Biological Complexity Unit.

• ForewordPrefaceAcknowledgmentsNotationCHAPTER 1 Motivation1.1 What is stochastic thermodynamics?1.2 Why does it work and why is it useful?1.3 Plan of the workCHAPTER 2 Basics2.1 Thermodynamics2.2 Thermodynamic efficiency2.3 Free energy and nonequilibrium free energy2.4 Statistical mechanics2.5 Stochastic dynamics2.6 Master equations2.7 Trajectories of master equations2.8 Fokker-Planck equation (*)2.9 Langevin equation (*)2.10 Information2.11 Further reading2.12 ExercisesCHAPTER 3 Stochastic Thermodynamics3.1 The system3.2 Work and heat in stochastic thermodynamics3.3 Mesoscopic and calorimetric heat (*)3.4 ATP hydrolysis by myosin3.5 General reservoirs3.6 Stochastic entropy3.7 Stochastic entropy and entropy production in a manipulated two-level system3.8 Average entropy production rate3.9 Network theory of nonequilibrium steady states (*)3.10 Stochastic chemical reactions3.11 Linear response theory (*)3.12 More on coarse graining (*)3.13 Continuous systems (*)3.14 Further reading3.15 ExercisesCHAPTER 4 Fluctuation Relations4.1 Irreversibility and entropy production4.2 Integral fluctuation relation4.3 Dragged particle on a ring4.4 Back to linear response theory (*)4.5 Detailed fluctuation relation4.6 The Jarzynski and Crooks relations4.7 Instantaneous quench4.8 Fluctuation relations in practice4.9 Adiabatic and nonadiabatic entropy production and the Hatano-Sasa relation4.10 Systems with odd-parity variables4.11 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 reading4.17 ExercisesCHAPTER 5 Thermodynamics of Information5.1 A brief history5.2 Back to nonequilibrium free energy5.3 Information in stochastic thermodynamics5.4 The Sagawa-Ueda relation5.5 The Mandal-Jarzynski machine5.6 Copying information5.7 Information cost in sensing5.8 Information reservoirs5.9 Fluctuation relations with information reservoirs (*)5.10 Further reading5.11 ExercisesCHAPTER 6 Large Deviations: Theory and Practice6.1 Large deviations in a nutshell6.2 Currents, traffic, and other observables6.3 Large deviations and fluctuation relations6.4 Fluctuation theorem for currents (*)6.5 Tilting6.6 Michaelis-Menten reaction scheme6.7 Fluctuation relations in a model of kinesin (*)6.8 Cloning (*)6.9 Levels of large deviations (*)6.10 Further reading6.11 ExercisesCHAPTER 7 Experimental Applications7.1 The hairpin as a paradigm7.2 A simpler model7.3 Equilibrium free energies from nonequilibrium manipulations7.4 Maxwell demons7.5 Landauer principle7.6 Further readingCHAPTER 8 Developments8.1 Stochastic efficiency8.2 Uncertainty relations8.3 Applications of uncertainty relations8.4 First-passage times8.5 Fully irreversible processes8.6 Optimal protocols8.7 Martingales8.8 Random time8.9 Population genetics8.10 Further reading8.11 ExercisesCHAPTER 9 PerspectivesAppendixesA.1 Convex functions and the Jensen inequalityA.2 Legendre transformationA.3 Probabilities and probability distributionsA.4 Generating functions and cumulant generating functionsA.5 Ergodic properties of Markov processesA.6 Gillespie algorithmA.7 Derivation of the Fokker-Planck equationA.8 Ito formula and Stratonovich-Ito mappingA.9 Basis of the cycle spaceA.10 Actions and trajectory probabilities for Langevin equationsA.11 The Bennett-Crooks estimator for the free-energy differenceA.12 Cauchy-Schwarz inequalityA.13 Bound for the current rate functionBibliographyAuthor IndexIndex

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