This book lays out a vision for a coherent framework for understanding complex systems. By developing the genuine idea of Brownian agents, the author combines concepts from informatics, such as multiagent systems, with approaches of statistical many-particle physics. It demonstrates that Brownian agent models can be successfully applied in many different contexts, ranging from physicochemical pattern formation to swarming in biological systems.
The term active fluids refers to motions that are created by transforming energy from the surroundings into directed motion. There are many examples, both natural and synthetic, including individual swimming bacteria or motile cells, drops and bubbles that move owing to surface stresses (so-called Marangoni motions), and chemical- or optical-driven colloids. Investigations into active fluids provide new insights into non-equilibrium systems, have the potential for novel applications, and open new directions in physics, chemistry, biology and engineering. This book provides an expert introduction to active fluids systems, covering simple to complex environments. It explains the interplay of chemical processes and hydrodynamics, including the roles of mechanical and rheological properties across active fluids, with reference to experiments, theory, and simulations. These concepts are discussed for a variety of scenarios, such as the trajectories of microswimmers, cell crawling and fluid stirring, and apply to collective behaviours of dense suspensions and active gels. Emerging avenues of research are highlighted, ranging from the role of active processes for biological functions to programmable active materials, showcasing the exciting potential of this rapidly-evolving research field.
The book builds on the analogy between social groups and assemblies of molecules to introduce the concepts of statistical mechanics, machine learning and data science. Applying a data analytics approach to molecular systems, we show how individual (molecular) features and interactions between molecules, or "communication" processes, allow for the prediction of properties and collective behavior of molecular systems - just as polling and social networking shed light on the behavior of social groups. Applications to systems at the cutting-edge of research for biological, environmental, and energy applications are also presented. Key features: Draws on a data analytics approach of molecular systems. Covers hot topics such as artificial intelligence and machine learning of molecular trends. Contains applications to systems at the cutting-edge of research for biological, environmental and energy applications. Discusses molecular simulation and links with other important, emerging techniques and trends in computational sciences and society. Authors have a well-established track record and reputation in the field.
This volume celebrates the over fifty-year career in non-equilibrium statistical physics of Professor Paolo Grigolini of the Center for Nonlinear Science at the University of North Texas. It begins by positioning Grigolini in a five-dimensional science-personality space with the following axes: Sleeper, Keeper, Leaper, Creeper and Reaper. This introduction to the person is followed by a sequence of papers in the various areas of science where his work has had impact, including subtle questions concerned with the connection between classical and quantum systems; a two-level atom coupled to a radiation field; classical probability calculus; anomalous diffusion that is Brownian yet non-Gaussian; a new method for detecting scaling in time series; and the effect of strong Anderson localization on ultrasound transmission, among other topics.
Statistical physics is a core component of most undergraduate (and some post-graduate) physics degree courses. It is primarily concerned with the behavior of matter in bulk-from boiling water to the superconductivity of metals. Ultimately, it seeks to uncover the laws governing random processes, such as the snow on your TV screen. This essential new textbook guides the reader quickly and critically through a statistical view of the physical world, including a wide range of physical applications to illustrate the methodology. It moves from basic examples to more advanced topics, such as broken symmetry and the Bose-Einstein equation. To accompany the text, the author, a renowned expert in the field, has written a Solutions Manual/Instructor's Guide, available free of charge to lecturers who adopt this book for their courses. Introduction to Statistical Physics will appeal to students and researchers in physics, applied mathematics and statistics.
Deals with the computer simulation of complex physical sys- tems encounteredin condensed-matter physics and statistical mechanics as well as in related fields such as metallurgy, polymer research, lattice gauge theory and quantummechanics.
“Soft matter” is nowadays used to describe an increasingly important class of - terials that encompasses polymers, liquid crystals, molecular assemblies building hierarchical structures, organic-inorganic hybrids, and the whole area of colloidal science. Common to all is that ?uctuations, and thus the thermal energy k T and B entropy, play an important role. “Soft” then means that these materials are in a state of matter that is neither a simple liquid nor a hard solid of the type studied in hard condensed matter, hence sometimes many types of soft matter are also named “c- plex ?uids. ” Soft matter, either of synthetic or biological origin, has been a subject of physical and chemical research since the early ?nding of Staudinger that long chain mo- cules exist. From then on, synthetic chemistry as well as physical characterization underwent an enormous development. One of the outcomes is the abundant pr- ence of polymeric materials in our everyday life. Nowadays, methods developed for synthetic polymers are being more and more applied to biological soft matter. The link between modern biophysics and soft matter physics is quite close in many respects. This also means that the focus of research has moved from simple - mopolymers to more complex structures, such as branched objects, heteropolymers (random copolymers, proteins), polyelectrolytes, amphiphiles and so on.
