Molecular Dynamics: Probability and Uncertainty by Coveney, Peter V.

Molecular Dynamics: Probability and Uncertainty (Hardcover) (ISBN-13: 9780198893417)

Vendor: Peter V. Coveney
Product type: Books
Format: Hardcover
$70.00
$70.00
$70.00
Subtotal: $70.00
Molecular Dynamics: Probability and Uncertainty by Coveney, Peter V.

Molecular Dynamics: Probability and Uncertainty

$70.00
Molecular Dynamics: Probability and Uncertainty by Coveney, Peter V.

Molecular Dynamics: Probability and Uncertainty

$70.00
Format: Hardcover
Description
Description
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Embark on a fascinating exploration of molecular dynamics, which combines the authors' new probabilistic interpretation with cutting-edge simulations, some of which are performed on the largest supercomputers on our planet. From fundamental principles to innovative applications, this book covers the rich tapestry of molecular dynamics and its intersections with biological and medical sciences, materials science and engineering, and artificial intelligence, alongside uncertainty quantification. This enables the authors to highlight the critical role of molecular dynamics in delivering actionable outcomes for drug discovery, materials design and beyond.

Beginning with a solid introduction to the intricate world of molecular dynamics, the book goes on to describe its modern probabilistic formulation. It investigates ensemble-based molecular dynamics simulations and free energies, uncovering both the way that ensemble techniques revolutionize simulation methodologies and how they empower researchers to generate new insights. Further, the book explores the exciting realm of simulations for advanced materials and discusses verification, validation and uncertainty quantification, illuminating the synergies between molecular dynamics and artificial intelligence and their potential for transformative breakthroughs.

Whether you are a seasoned researcher seeking to expand your knowledge or a curious student eager to investigate the complexities of molecular dynamics, this book serves as an indispensable resource, challenging conventional approaches, offering fresh perspectives and unlocking new insights into real-world problems in this captivating field.

Author: Peter V. Coveney, Shunzhou Wan
ISBN-10: 0198893418
ISBN-13: 9780198893417
Publisher: Oxford University Press
Language: English
Published: 08/15/2025
Pages: 256
Format: Hardcover
By Peter V. Coveney
By Peter V. Coveney
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Peter V. Coveney, Director of the Centre for Computational Science and Professor of Physical Chemistry, University College London, Shunzhou Wan, Senior Research Fellow, Department of Chemistry, University College London

At University College London, Professor Peter V. Coveney holds a chair in Physical Chemistry, is Director of the Centre for Computational Science, is an Associate Director in the Centre of Advanced Research Computing, and is an Honorary Professor in Computer Science. He is a Professor in Applied High Performance Computing and Quantum Computing at the University of Amsterdam and Professor Adjunct at Yale University School of Medicine. Coveney is active in a broad area of interdisciplinary research including computational science, high performance computing, quantum computing, condensed matter physics and chemistry, materials science, and life and medical sciences. He has published more than 500 scientific papers and co-authored three best-selling books. He is a Fellow of the Royal Academy of Engineering and a Member of the Academia Europaea.

Dr Shunzhou Wan is a research fellow in the Centre for Computational Science (CCS) at University College London (UCL). He completed his PhD in Physics at the University of Science and Technology of China (USTC). After his PhD, he worked as a post-doctoral researcher in Martin Karplus's group at Université Louis Pasteur, Strasbourg, France. His research focusses on molecular dynamics simulations and free energy calculations. His recent work involves developing ensemble-based protocols for rapid and accurate free energy calculations, advancing scientific methods for drug discovery through computer simulations integrated with machine learning techniques, and exploring uncertainty quantification in molecular dynamics simulations.

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