This book describes a promising approach to problems in the foundations of quantum mechanics, including the measurement problem. The dynamics of ensembles on configuration space is shown here to be a valuable tool for unifying the formalisms of classical and quantum mechanics, for deriving and extending the latter in various ways, and for addressing the quantum measurement problem. A description of physical systems by means of ensembles on configuration space can be introduced at a very fundamental level: the basic building blocks are a configuration space, probabilities, and Hamiltonian equations of motion for the probabilities. The formalism can describe both classical and quantum systems, and their thermodynamics, with the main difference being the choice of ensemble Hamiltonian. Furthermore, there is a natural way of introducing ensemble Hamiltonians that describe the evolution of hybrid systems; i.e., interacting systems that have distinct classical and quantum sectors, allowing for consistent descriptions of quantum systems interacting with classical measurement devices and quantum matter fields interacting gravitationally with a classical spacetime.

It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face recognition and are now being applied in areas as diverse as object tracking and bioinformatics. Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including the random forest skeleton tracking algorithm in the Xbox Kinect sensor, which bypasses the need for game controllers. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike.

This book presents an authoritative and in-depth treatment of potential energy landscape theory, a powerful analytical approach to describing the atomic and molecular interactions in condensed-matter phenomena. Drawing on the latest developments in the computational modeling of many-body systems, Frank Stillinger applies this approach to a diverse range of substances and systems, including crystals, liquids, glasses and other amorphous solids, polymers, and solvent-suspended biomolecules. Stillinger focuses on the topography of the multidimensional potential energy hypersurface created when a large number of atoms or molecules simultaneously interact with one another. He explains how the complex landscape topography separates uniquely into individual "basins," each containing a local potential energy minimum or "inherent structure," and he shows how to identify interbasin transition states—saddle points—that reside in shared basin boundaries. Stillinger describes how inherent structures and their basins can be classified and enumerated by depth, curvatures, and other attributes, and how those enumerations lead logically from vastly complicated multidimensional landscapes to properties observed in the real three-dimensional world. Essential for practitioners and students across a variety of fields, the book illustrates how this approach applies equally to systems whose nuclear motions are intrinsically quantum mechanical or classical, and provides novel strategies for numerical simulation computations directed toward diverse condensed-matter systems.

With the discovery of pulsars, quasars, and galactic X-ray sources in the late 60's and early 70's, and the coincident expansion in the search for gravitational waves, rela tivistic gravity assumed an important place in the astrophysics of localized objects. Only by pushing Einstein's solar-system-tested general theory of relativity to the study of the extremes of gravitational collapse and its outcomes did it seem that one could explain these frontier astronomical phenomena. This conclusion continues to be true today. Relativistic gravity had always played the central role in cosmology. The discov ery of the cosmic background radiation in 1965, the increasing understanding of matter physics at high energies in the decades following, and the growing wealth of observations on the large scale structure meant that it was possible to make increasingly detailed mod els of the universe, both today and far in the past. This development, not accidentally, was contemporary to that for localized objects described above.

From the hydrophobic effect to protein-ligand binding, statistical physics is relevant in almost all areas of molecular biophysics and biochemistry, making it essential for modern students of molecular behavior. But traditional presentations of this material are often difficult to penetrate. Statistical Physics of Biomolecules: An Introduction brin

Material properties emerge from phenomena on scales ranging from Angstroms to millimeters, and only a multiscale treatment can provide a complete understanding. Materials researchers must therefore understand fundamental concepts and techniques from different fields, and these are presented in a comprehensive and integrated fashion for the first time in this book. Incorporating continuum mechanics, quantum mechanics, statistical mechanics, atomistic simulations and multiscale techniques, the book explains many of the key theoretical ideas behind multiscale modeling. Classical topics are blended with new techniques to demonstrate the connections between different fields and highlight current research trends. Example applications drawn from modern research on the thermo-mechanical properties of crystalline solids are used as a unifying focus throughout the text. Together with its companion book, Continuum Mechanics and Thermodynamics (Cambridge University Press, 2011), this work presents the complete fundamentals of materials modeling for graduate students and researchers in physics, materials science, chemistry and engineering.

Exciting developments in earthquake science have benefited from new observations, improved computational technologies, and improved modeling capabilities. Designing models of the earthquake of the earthquake generation process is a grand scientific challenge due to the complexity of phenomena and range of scales involved from microscopic to global. Such models provide powerful new tools for the study of earthquake precursory phenomena and the earthquake cycle. Through workshops, collaborations and publications the APEC Cooperation for Earthquake Simulations (ACES) aims to develop realistic supercomputer simulation models for the complete earthquake generation process, thus providing a "virtual laboratory" to probe earthquake behavior. Part I of the book covers microscopic simulations, scaling physics and earthquake generation and cycles. This part also focuses on plate processes and earthquake generation from a macroscopic standpoint.

Exciting developments in earthquake science have benefited from new observations, improved computational technologies, and improved modeling capabilities. Designing models of the earthquake of the earthquake generation process is a grand scientific challenge due to the complexity of phenomena and range of scales involved from microscopic to global. Such models provide powerful new tools for the study of earthquake precursory phenomena and the earthquake cycle. Through workshops, collaborations and publications the APEC Cooperation for Earthquake Simulations (ACES) aims to develop realistic supercomputer simulation models for the complete earthquake generation process, thus providing a "virtual laboratory" to probe earthquake behavior. Part I of the book covers microscopic simulations, scaling physics and earthquake generation and cycles. This part also focuses on plate processes and earthquake generation from a macroscopic standpoint.

Molecularly small confined phases play an important role in many scientific and engineering disciplines. For instance, the confining membrane of a living cell is known to affect the structure and transport of cellular water, which mediates the cell's metabolism and other biochemical processes. Transport of hazardous waste through the soil is strongly influenced by the adsorption of bulk phase molecules on the confining mineral _surfaces. Finally, molecularly thin confined fluid films play a prominent part in lubrication. These examples illustrate the broad range of natural and commercial processes to which the present subject pertains. Much experimental effort has been devoted to molecularly small confined phases, revealing the intriguing nature of such systems. Several sections of this book are therefore devoted to descriptions of experimental techniques. To date even the most refined experiments do not yield direct information about structure and processes on the molecular scale. Computer simulations, on the other hand, do give such information and therefore complement real laboratory experiments. Several sections of this book discuss the link between experiments and the corre sponding simulations.

This comprehensive, handbook-style survey of diffusion in condensed matter gives detailed insight into diffusion as the process of particle transport due to stochastic movement. It is understood and presented as a phenomenon of crucial relevance for a large variety of processes and materials. In this book, all aspects of the theoretical fundamentals, experimental techniques, highlights of current developments and results for solids, liquids and interfaces are presented.