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Progress in Physical Chemistry Volume 3

Progress in Physical Chemistry Volume 3 PDF Author: Franz Michael Dolg
Publisher: Oldenbourg Verlag
ISBN: 3486711636
Category : Science
Languages : en
Pages : 431

Book Description
Progress in Physical Chemistry is a collection of recent »Review Articles« published in the »Zeitschrift für Physikalische Chemie«. The third volume of the series "Progress in Physical Chemistry" comprises 27 articles, most of them with review character, written by the members of the Priority Program (SPP) 1145 of the German Research Foundation (DFG).

Progress in Physical Chemistry Volume 3

Progress in Physical Chemistry Volume 3 PDF Author: Franz Michael Dolg
Publisher: Oldenbourg Verlag
ISBN: 3486711636
Category : Science
Languages : en
Pages : 431

Book Description
Progress in Physical Chemistry is a collection of recent »Review Articles« published in the »Zeitschrift für Physikalische Chemie«. The third volume of the series "Progress in Physical Chemistry" comprises 27 articles, most of them with review character, written by the members of the Priority Program (SPP) 1145 of the German Research Foundation (DFG).

Tensor Numerical Methods in Quantum Chemistry

Tensor Numerical Methods in Quantum Chemistry PDF Author: Venera Khoromskaia
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110391376
Category : Mathematics
Languages : en
Pages : 343

Book Description
The conventional numerical methods when applied to multidimensional problems suffer from the so-called "curse of dimensionality", that cannot be eliminated by using parallel architectures and high performance computing. The novel tensor numerical methods are based on a "smart" rank-structured tensor representation of the multivariate functions and operators discretized on Cartesian grids thus reducing solution of the multidimensional integral-differential equations to 1D calculations. We explain basic tensor formats and algorithms and show how the orthogonal Tucker tensor decomposition originating from chemometrics made a revolution in numerical analysis, relying on rigorous results from approximation theory. Benefits of tensor approach are demonstrated in ab-initio electronic structure calculations. Computation of the 3D convolution integrals for functions with multiple singularities is replaced by a sequence of 1D operations, thus enabling accurate MATLAB calculations on a laptop using 3D uniform tensor grids of the size up to 1015. Fast tensor-based Hartree-Fock solver, incorporating the grid-based low-rank factorization of the two-electron integrals, serves as a prerequisite for economical calculation of the excitation energies of molecules. Tensor approach suggests efficient grid-based numerical treatment of the long-range electrostatic potentials on large 3D finite lattices with defects.The novel range-separated tensor format applies to interaction potentials of multi-particle systems of general type opening the new prospects for tensor methods in scientific computing. This research monograph presenting the modern tensor techniques applied to problems in quantum chemistry may be interesting for a wide audience of students and scientists working in computational chemistry, material science and scientific computing.

Sparse Grids and Applications - Munich 2012

Sparse Grids and Applications - Munich 2012 PDF Author: Jochen Garcke
Publisher: Springer Science & Business Media
ISBN: 3319045377
Category : Mathematics
Languages : en
Pages : 345

Book Description
Sparse grids have gained increasing interest in recent years for the numerical treatment of high-dimensional problems. Whereas classical numerical discretization schemes fail in more than three or four dimensions, sparse grids make it possible to overcome the “curse” of dimensionality to some degree, extending the number of dimensions that can be dealt with. This volume of LNCSE collects the papers from the proceedings of the second workshop on sparse grids and applications, demonstrating once again the importance of this numerical discretization scheme. The selected articles present recent advances on the numerical analysis of sparse grids as well as efficient data structures, and the range of applications extends to uncertainty quantification settings and clustering, to name but a few examples.

Sparse Grids and Applications - Munich 2018

Sparse Grids and Applications - Munich 2018 PDF Author: Hans-Joachim Bungartz
Publisher: Springer Nature
ISBN: 3030813622
Category : Mathematics
Languages : en
Pages : 268

Book Description
Sparse grids are a popular tool for the numerical treatment of high-dimensional problems. Where classical numerical discretization schemes fail in more than three or four dimensions, sparse grids, in their different flavors, are frequently the method of choice. This volume of LNCSE presents selected papers from the proceedings of the fifth workshop on sparse grids and applications, and demonstrates once again the importance of this numerical discretization scheme. The articles present recent advances in the numerical analysis of sparse grids in connection with a range of applications including uncertainty quantification, plasma physics simulations, and computational chemistry, to name but a few.

Sparse Grids and Applications - Stuttgart 2014

Sparse Grids and Applications - Stuttgart 2014 PDF Author: Jochen Garcke
Publisher: Springer
ISBN: 331928262X
Category : Computers
Languages : en
Pages : 348

Book Description
This volume of LNCSE is a collection of the papers from the proceedings of the third workshop on sparse grids and applications. Sparse grids are a popular approach for the numerical treatment of high-dimensional problems. Where classical numerical discretization schemes fail in more than three or four dimensions, sparse grids, in their different guises, are frequently the method of choice, be it spatially adaptive in the hierarchical basis or via the dimensionally adaptive combination technique. Demonstrating once again the importance of this numerical discretization scheme, the selected articles present recent advances on the numerical analysis of sparse grids as well as efficient data structures. The book also discusses a range of applications, including uncertainty quantification and plasma physics.

Statistical Mechanics

Statistical Mechanics PDF Author: James Sethna
Publisher: OUP Oxford
ISBN: 0191566217
Category : Science
Languages : en
Pages : 374

Book Description
In each generation, scientists must redefine their fields: abstracting, simplifying and distilling the previous standard topics to make room for new advances and methods. Sethna's book takes this step for statistical mechanics - a field rooted in physics and chemistry whose ideas and methods are now central to information theory, complexity, and modern biology. Aimed at advanced undergraduates and early graduate students in all of these fields, Sethna limits his main presentation to the topics that future mathematicians and biologists, as well as physicists and chemists, will find fascinating and central to their work. The amazing breadth of the field is reflected in the author's large supply of carefully crafted exercises, each an introduction to a whole field of study: everything from chaos through information theory to life at the end of the universe.

Solving the Schrodinger Equation

Solving the Schrodinger Equation PDF Author: Paul L. A. Popelier
Publisher: World Scientific
ISBN: 1848167253
Category : Science
Languages : en
Pages : 375

Book Description
The Schrodinger equation is the master equation of quantum chemistry. The founders of quantum mechanics realised how this equation underpins essentially the whole of chemistry. However, they recognised that its exact application was much too complicated to be solvable at the time. More than two generations of researchers were left to work out how to achieve this ambitious goal for molecular systems of ever-increasing size. This book focuses on non-mainstream methods to solve the molecular electronic Schrodinger equation. Each method is based on a set of core ideas and this volume aims to explain these ideas clearly so that they become more accessible. By bringing together these non-standard methods, the book intends to inspire graduate students, postdoctoral researchers and academics to think of novel approaches. Is there a method out there that we have not thought of yet? Can we design a new method that combines the best of all worlds?

Principles of Multiscale Modeling

Principles of Multiscale Modeling PDF Author: Weinan E
Publisher: Cambridge University Press
ISBN: 1107096545
Category : Mathematics
Languages : en
Pages : 485

Book Description
A systematic discussion of the fundamental principles, written by a leading contributor to the field.

Quantum Many-Body Physics of Ultracold Molecules in Optical Lattices

Quantum Many-Body Physics of Ultracold Molecules in Optical Lattices PDF Author: Michael L. Wall
Publisher: Springer
ISBN: 3319142526
Category : Science
Languages : en
Pages : 391

Book Description
This thesis investigates ultracold molecules as a resource for novel quantum many-body physics, in particular by utilizing their rich internal structure and strong, long-range dipole-dipole interactions. In addition, numerical methods based on matrix product states are analyzed in detail, and general algorithms for investigating the static and dynamic properties of essentially arbitrary one-dimensional quantum many-body systems are put forth. Finally, this thesis covers open-source implementations of matrix product state algorithms, as well as educational material designed to aid in the use of understanding such methods.

Machine Learning Meets Quantum Physics

Machine Learning Meets Quantum Physics PDF Author: Kristof T. Schütt
Publisher: Springer Nature
ISBN: 3030402452
Category : Science
Languages : en
Pages : 473

Book Description
Designing molecules and materials with desired properties is an important prerequisite for advancing technology in our modern societies. This requires both the ability to calculate accurate microscopic properties, such as energies, forces and electrostatic multipoles of specific configurations, as well as efficient sampling of potential energy surfaces to obtain corresponding macroscopic properties. Tools that can provide this are accurate first-principles calculations rooted in quantum mechanics, and statistical mechanics, respectively. Unfortunately, they come at a high computational cost that prohibits calculations for large systems and long time-scales, thus presenting a severe bottleneck both for searching the vast chemical compound space and the stupendously many dynamical configurations that a molecule can assume. To overcome this challenge, recently there have been increased efforts to accelerate quantum simulations with machine learning (ML). This emerging interdisciplinary community encompasses chemists, material scientists, physicists, mathematicians and computer scientists, joining forces to contribute to the exciting hot topic of progressing machine learning and AI for molecules and materials. The book that has emerged from a series of workshops provides a snapshot of this rapidly developing field. It contains tutorial material explaining the relevant foundations needed in chemistry, physics as well as machine learning to give an easy starting point for interested readers. In addition, a number of research papers defining the current state-of-the-art are included. The book has five parts (Fundamentals, Incorporating Prior Knowledge, Deep Learning of Atomistic Representations, Atomistic Simulations and Discovery and Design), each prefaced by editorial commentary that puts the respective parts into a broader scientific context.