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Stochastic Thermodynamics

An Introduction

Luca Peliti, Simone Pigolotti

ca. 72,99
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Naturwissenschaften, Medizin, Informatik, Technik / Naturwissenschaften allgemein


The first comprehensive graduate-level introduction to stochastic thermodynamics

Stochastic thermodynamics is a well-defined subfield of statistical physics that aims to interpret thermodynamic concepts for systems ranging in size from a few to hundreds of nanometers, the behavior of which is inherently random due to thermal fluctuations. This growing field therefore describes the nonequilibrium dynamics of small systems, such as artificial nanodevices and biological molecular machines, which are of increasing scientific and technological relevance.

This textbook provides an up-to-date pedagogical introduction to stochastic thermodynamics, guiding readers from basic concepts in statistical physics, probability theory, and thermodynamics to the most recent developments in the field. Gradually building up to more advanced material, the authors consistently prioritize simplicity and clarity over exhaustiveness and focus on the development of readers’ physical insight over mathematical formalism. This approach allows the reader to grow as the book proceeds, helping interested young scientists to enter the field with less effort and to contribute to its ongoing vibrant development. Chapters provide exercises to complement and reinforce learning.

Appropriate for graduate students in physics and biophysics, as well as researchers, Stochastic Thermodynamics serves as an excellent initiation to this rapidly evolving field.

  • Emphasizes a pedagogical approach to the subject
  • Highlights connections with the thermodynamics of information
  • Pays special attention to molecular biophysics applications
  • Privileges physical intuition over mathematical formalism
  • Solutions manual available on request for instructors adopting the book in a course

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Statistical physics, Thermal equilibrium, Master equation, Phase transition, Stochastic process, Diffusion equation, Inverse function, Langevin equation, Thermally isolated system, Microscopic reversibility, Laws of thermodynamics, Rotational diffusion, Probability current, Change of variables, Zeroth law of thermodynamics, Diffusion process, Initial condition, Time, Dirac delta function, Grand canonical ensemble, Free energy, Correspondence principle, Central limit theorem, Gillespie algorithm, Characteristic energy, Entropy, Fluctuation theorem, Hamiltonian mechanics, Observable, Probability distribution, Microcanonical ensemble, Thermodynamic integration, First law of thermodynamics, Statistical mechanics, Boltzmann's entropy formula, Dissipation, Standard state, Degrees of freedom (statistics), Equilibrium thermodynamics, Molecule, Random variable, Stochastic differential equation, Second law of thermodynamics, Martingale (probability theory), Chaos theory, Measurement, Boltzmann distribution, Internal energy, Thermodynamic state, Thermodynamic limit, Thermodynamics, Probability measure, Rate function, Chemical potential, Quantum realm, Moment (mathematics), Loschmidt's paradox, Statistical weight, Binomial distribution, Detailed balance, Quantity, Quantum harmonic oscillator, Landauer's principle, Stratonovich integral, Asymptotic distribution, Non-equilibrium thermodynamics, Continuity equation, Phase diagram, Temperature, Irreversible process, Stochastic, Equation of state (cosmology), Heat engine, Proportionality (mathematics), Microstate (statistical mechanics), Propagator, Sign convention, Thermodynamic system, Markov process, Fluctuation-dissipation theorem, Ergodicity, Law of mass action, Kullback–Leibler divergence, Markov chain, Kinetic theory of gases, Law of large numbers, Thermodynamic equilibrium, Gibbs free energy, Large deviations theory, Thermodynamic process, Jarzynski equality, Entropy production, Probability, Stationary distribution, Autocorrelation, Canonical ensemble, Joint probability distribution, Fokker–Planck equation, Partition function (statistical mechanics), Cumulant