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The fragment molecular orbital (FMO) method is a fast linear-scaling quantum-mechanical method employed by chemists and physicists all over the world. It provides a wealth of properties of fragments from quantum-chemical calculations, a bottomless treasure pit for data mining and machine learning. However, there is no user-friendly description of its usage in the widely employed quantum-chemical open-source software GAMESS, nor is there any book covering the usage of GAMESS in general. This leaves very many interested users to their own devices to get through a variety of problems with very cryptic descriptions of keywords in the program manual and no guide whatsoever as to what options should be set for particular scientific tasks. This book is the panacea to many frustrations.The main focus of the book is to build a solid bridge connecting FMO users to GAMESS, by giving a helpful introduction of various FMO methods as needed for particular problems found in computational chemistry, and describing in detail how to do these simulations and understand the results from the output of the program. The book also covers parallelization strategies for attaining high parallel efficiency in massively parallel computations, and provides means to analyze performance and design a solution for overcoming performance bottlenecks. A special section is devoted to dealing with problems in executing GAMESS, arising from computational environment and user errors. Finally, 14 carefully selected types of applications are discussed in detail, describing the input keywords and explaining where to find the main results in the text-based output.
The fragment molecular orbital (FMO) method is a fast linear-scaling quantum-mechanical method employed by chemists and physicists all over the world. It provides a wealth of properties of fragments from quantum-chemical calculations, a bottomless treasure pit for data mining and machine learning. However, there is no user-friendly description of its usage in the widely employed quantum-chemical open-source software GAMESS, nor is there any book covering the usage of GAMESS in general. This leaves very many interested users to their own devices to get through a variety of problems with very cryptic descriptions of keywords in the program manual and no guide whatsoever as to what options should be set for particular scientific tasks. This book is the panacea to many frustrations.The main focus of the book is to build a solid bridge connecting FMO users to GAMESS, by giving a helpful introduction of various FMO methods as needed for particular problems found in computational chemistry, and describing in detail how to do these simulations and understand the results from the output of the program. The book also covers parallelization strategies for attaining high parallel efficiency in massively parallel computations, and provides means to analyze performance and design a solution for overcoming performance bottlenecks. A special section is devoted to dealing with problems in executing GAMESS, arising from computational environment and user errors. Finally, 14 carefully selected types of applications are discussed in detail, describing the input keywords and explaining where to find the main results in the text-based output.
Fragmentation: Toward Accurate Calculations on Complex Molecular Systems introduces the reader to the broad array of fragmentation and embedding methods that are currently available or under development to facilitate accurate calculations on large, complex systems such as proteins, polymers, liquids and nanoparticles. These methods work by subdividing a system into subunits, called fragments or subsystems or domains. Calculations are performed on each fragment and then the results are combined to predict properties for the whole system. Topics covered include: Fragmentation methods Embedding methods Explicitly correlated local electron correlation methods Fragment molecular orbital method Methods for treating large molecules This book is aimed at academic researchers who are interested in computational chemistry, computational biology, computational materials science and related fields, as well as graduate students in these fields.
Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing. This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers. - New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more - Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism - Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing
From New York Times bestselling author Sam Kean comes incredible stories of science, history, finance, mythology, the arts, medicine, and more, as told by the Periodic Table. Why did Gandhi hate iodine (I, 53)? How did radium (Ra, 88) nearly ruin Marie Curie's reputation? And why is gallium (Ga, 31) the go-to element for laboratory pranksters? The Periodic Table is a crowning scientific achievement, but it's also a treasure trove of adventure, betrayal, and obsession. These fascinating tales follow every element on the table as they play out their parts in human history, and in the lives of the (frequently) mad scientists who discovered them. The Disappearing Spoon masterfully fuses science with the classic lore of invention, investigation, and discovery -- from the Big Bang through the end of time. Though solid at room temperature, gallium is a moldable metal that melts at 84 degrees Fahrenheit. A classic science prank is to mold gallium spoons, serve them with tea, and watch guests recoil as their utensils disappear.
As a market leader, PHYSICS FOR SCIENTISTS AND ENGINEERS is one of the most powerful brands in the physics market. While preserving concise language, state-of-the-art educational pedagogy, and top-notch worked examples, the Ninth Edition highlights the Analysis Model approach to problem-solving, including brand-new Analysis Model Tutorials, written by text co-author John Jewett, and available in Enhanced WebAssign. The Analysis Model approach lays out a standard set of situations that appear in most physics problems, and serves as a bridge to help students identify the correct fundamental principle--and then the equation--to utilize in solving that problem. The unified art program and the carefully thought out problem sets also enhance the thoughtful instruction for which Raymond A. Serway and John W. Jewett, Jr. earned their reputations. The Ninth Edition of PHYSICS FOR SCIENTISTS AND ENGINEERS continues to be accompanied by Enhanced WebAssign in the most integrated text-technology offering available today. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
This timeless exploration of the work of the great physicists of the early 20th century employs analogies, examples, and imaginative insights rather than computations to explain the dramatic impact of quantum physics on classical theory. Topics include Pauli's exclusion principle, Schroedinger's wave equation, Heisenberg's uncertainty principle, and many other concepts. 1959 edition.
Before Paulo Coelho and Eckhart Tolle came Rodney Collin. A huge 462 page book full of essential knowledge. How To Become Supernatural Man, The Universe and Cosmic Mystery is an exploration of the universe and man's place in it. Rodney Collin examines 20th-century scientific discoveries and traditional esoteric teachings and concludes that the driving force behind everything is neither procreation nor survival, but expansion of awareness. Collin sets out to reconcile the considerable contradictions of the rational and imaginative minds and of the ways we see the external world versus our inner selves. For readers familiar with Gurdjieff's cosmology will here find further examinations of the systems outlined in by Ouspensky in Search of the Miraculous.
Science, engineering, and technology permeate nearly every facet of modern life and hold the key to solving many of humanity's most pressing current and future challenges. The United States' position in the global economy is declining, in part because U.S. workers lack fundamental knowledge in these fields. To address the critical issues of U.S. competitiveness and to better prepare the workforce, A Framework for K-12 Science Education proposes a new approach to K-12 science education that will capture students' interest and provide them with the necessary foundational knowledge in the field. A Framework for K-12 Science Education outlines a broad set of expectations for students in science and engineering in grades K-12. These expectations will inform the development of new standards for K-12 science education and, subsequently, revisions to curriculum, instruction, assessment, and professional development for educators. This book identifies three dimensions that convey the core ideas and practices around which science and engineering education in these grades should be built. These three dimensions are: crosscutting concepts that unify the study of science through their common application across science and engineering; scientific and engineering practices; and disciplinary core ideas in the physical sciences, life sciences, and earth and space sciences and for engineering, technology, and the applications of science. The overarching goal is for all high school graduates to have sufficient knowledge of science and engineering to engage in public discussions on science-related issues, be careful consumers of scientific and technical information, and enter the careers of their choice. A Framework for K-12 Science Education is the first step in a process that can inform state-level decisions and achieve a research-grounded basis for improving science instruction and learning across the country. The book will guide standards developers, teachers, curriculum designers, assessment developers, state and district science administrators, and educators who teach science in informal environments.
Quantum chemistry is simulating atomistic systems according to the laws of quantum mechanics, and such simulations are essential for our understanding of the world and for technological progress. Machine learning revolutionizes quantum chemistry by increasing simulation speed and accuracy and obtaining new insights. However, for nonspecialists, learning about this vast field is a formidable challenge. Quantum Chemistry in the Age of Machine Learning covers this exciting field in detail, ranging from basic concepts to comprehensive methodological details to providing detailed codes and hands-on tutorials. Such an approach helps readers get a quick overview of existing techniques and provides an opportunity to learn the intricacies and inner workings of state-of-the-art methods. The book describes the underlying concepts of machine learning and quantum chemistry, machine learning potentials and learning of other quantum chemical properties, machine learning-improved quantum chemical methods, analysis of Big Data from simulations, and materials design with machine learning. Drawing on the expertise of a team of specialist contributors, this book serves as a valuable guide for both aspiring beginners and specialists in this exciting field. - Compiles advances of machine learning in quantum chemistry across different areas into a single resource - Provides insights into the underlying concepts of machine learning techniques that are relevant to quantum chemistry - Describes, in detail, the current state-of-the-art machine learning-based methods in quantum chemistry