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After an insightful introductory part on recent developments in the thermodynamics of small systems, the author presents his contribution to a long-standing problem, namely the connection between irreversibility and dissipation. He develops a method based on recent results on fluctuation theorems that is able to estimate dissipation using only information acquired in a single, sufficiently long, trajectory of a stationary nonequilibrium process. This part ends with a remarkable application of the method to the analysis of biological data, in this case, the fluctuations of a hair bundle. The third part studies the energetics of systems that undergo symmetry breaking transitions. These theoretical ideas lead to, among other things, an experimental realization of a Szilard engine using manipulated colloids. This work has the potential for important applications ranging from the analysis of biological media to the design of novel artificial nano-machines.
This book concentrates on the properties of the stationary states in chaotic systems of particles or fluids, leaving aside the theory of the way they can be reached. The stationary states of particles or of fluids (understood as probability distributions on microscopic configurations or on the fields describing continua) have received important new ideas and data from numerical simulations and reviews are needed. The starting point is to find out which time invariant distributions come into play in physics. A special feature of this book is the historical approach. To identify the problems the author analyzes the papers of the founding fathers Boltzmann, Clausius and Maxwell including translations of the relevant (parts of) historical documents. He also establishes a close link between treatment of irreversible phenomena in statistical mechanics and the theory of chaotic systems at and beyond the onset of turbulence as developed by Sinai, Ruelle, Bowen (SRB) and others: the author gives arguments intending to support strongly the viewpoint that stationary states in or out of equilibrium can be described in a unified way. In this book it is the "chaotic hypothesis", which can be seen as an extension of the classical ergodic hypothesis to non equilibrium phenomena, that plays the central role. It is shown that SRB - often considered as a kind of mathematical playground with no impact on physical reality - has indeed a sound physical interpretation; an observation which to many might be new and a very welcome insight. Following this, many consequences of the chaotic hypothesis are analyzed in chapter 3 - 4 and in chapter 5 a few applications are proposed. Chapter 6 is historical: carefully analyzing the old literature on the subject, especially ergodic theory and its relevance for statistical mechanics; an approach which gives the book a very personal touch. The book contains an extensive coverage of current research (partly from the authors and his coauthors publications) presented in enough detail so that advanced students may get the flavor of a direction of research in a field which is still very much alive and progressing. Proofs of theorems are usually limited to heuristic sketches privileging the presentation of the ideas and providing references that the reader can follow, so that in this way an overload of this text with technical details could be avoided.
Quantifying the flow of energy, entropy, and information within and through nonequilibrium systems remains a central challenge in understanding the microscopic physics of biological systems. Over the past two and a half decades, parallel developments in the fields of theoretical stochastic thermodynamics and single-molecule experiments have made tremendous steps towards this end, advancing our understanding of the fundamental physical limitations and constraints faced by biological systems in vivo. Central in this focus are molecular machines: nanoscale protein complexes which interconvert between different forms of energy to perform useful functions to the cell. While single-molecule experiments on molecular machines have predicted impressively high efficiencies, much is still unknown about their performance in vivo. In this thesis we build upon these primitives, largely by making use of near-equilibrium phenomenological models to simplify and make tractable the problem of quantifying dissipation in molecular machines and predicting the operational modes which are imperative to minimizing their dissipation. By exploring the relevance of near-equilibrium models in the experimental investigation of a DNA hairpin, we find that such an approach can provide utility in understanding the strategies to reduce dissipation in nonequilibrium processes. However, single-molecule manipulations are significantly separated from the in vivo dynamics of molecular machines, and thus for the remainder of the thesis we expand upon this approach in various ways, generalizing the existing theoretical framework to more closely parallel the dynamics of molecular machines. By incorporating the inter-system feedback present in molecular machines, we find that familiar intuitions about how excess work and entropy production are related break down. Finally, we derive a phenomenological expression for the energy flows communicated within the components of a mechanochemical molecular machine. Ultimately, our analysis shows that intersystem feedback can lead to nonvanishing energy flows which are the manifestation of a Maxwell demon in the molecular machine itself.
This collection of lectures treats the dynamics of open systems with a strong emphasis on dissipation phenomena related to dynamical chaos. This research area is very broad, covering topics such as nonequilibrium statistical mechanics, environment-system coupling (decoherence) and applications of Markov semi-groups to name but a few. The book addresses not only experienced researchers in the field but also nonspecialists from related areas of research, postgraduate students wishing to enter the field and lecturers searching for advanced textbook material.
This book provides a comprehensive and self-contained overview of recent progress in nonequilibrium statistical mechanics, in particular, the discovery of fluctuation relations and other time-reversal symmetry relations. The significance of these advances is that nonequilibrium statistical physics is no longer restricted to the linear regimes close to equilibrium, but extends to fully nonlinear regimes. These important new results have inspired the development of a unifying framework for describing both the microscopic dynamics of collections of particles, and the macroscopic hydrodynamics and thermodynamics of matter itself. The book discusses the significance of this theoretical framework in relation to a broad range of nonequilibrium processes, from the nanoscale to the macroscale, and is essential reading for researchers and graduate students in statistical physics, theoretical chemistry and biological physics.
While systems at equilibrium are treated in a unified manner through the partition function formalism, the statistical physics of out-of-equilibrium systems covers a large variety of situations that are often without apparent connection. This book proposes a unified perspective on the whole set of systems near equilibrium: it brings out the profound unity of the laws which govern them and gathers together a large number of results usually fragmented in the literature. The reader will find in this book a pedagogical account of the fundamental results: physical origins of irreversibility, fluctuation-dissipation theorem, Boltzmann equation, linear response, Onsager relations, transport phenomena, Langevin and Fokker-Planck equations. The book's comprehensive organization makes it valuable both as a textbook about irreversible phenomena and as a reference book for researchers.
While some of the deepest results in nature are those that give explicit bounds between important physical quantities, some of the most intriguing and celebrated of such bounds come from fields where there is still a great deal of disagreement and confusion regarding even the most fundamental aspects of the theories. For example, in quantum mechanics, there is still no complete consensus as to whether the limitations associated with Heisenberg's Uncertainty Principle derive from an inherent randomness in physics, or rather from limitations in the measurement process itself, resulting from phenomena like back action. Likewise, the second law of thermodynamics makes a statement regarding the increase in entropy of closed systems, yet the theory itself has neither a universally-accepted definition of equilibrium, nor an adequate explanation of how a system with underlying microscopically Hamiltonian dynamics (reversible) settles into a fixed distribution. Motivated by these physical theories, and perhaps their inconsistencies, in this thesis we use dynamical systems theory to investigate how the very simplest of systems, even with no physical constraints, are characterized by bounds that give limits to the ability to make measurements on them. Using an existing interpretation, we start by examining how dissipative systems can be viewed as high-dimensional lossless systems, and how taking this view necessarily implies the existence of a noise process that results from the uncertainty in the initial system state. This fluctuation-dissipation result plays a central role in a measurement model that we examine, in particular describing how noise is inevitably injected into a system during a measurement, noise that can be viewed as originating either from the randomness of the many degrees of freedom of the measurement device, or of the environment. This noise constitutes one component of measurement back action, and ultimately imposes limits on measurement uncertainty. Depending on the assumptions we make about active devices, and their limitations, this back action can be offset to varying degrees via control. It turns out that using active devices to reduce measurement back action leads to estimation problems that have non-zero uncertainty lower bounds, the most interesting of which arise when the observed system is lossless. One such lower bound, a main contribution of this work, can be viewed as a classical version of a Heisenberg uncertainty relation between the system's position and momentum. We finally also revisit the murky question of how macroscopic dissipation appears from lossless dynamics, and propose alternative approaches for framing the question using existing systematic methods of model reduction.