Items related to Machine Learning Meets Quantum Physics (Lecture Notes...
- PublisherSpringer
- Publication date2020
- ISBN 10 3030402444
- ISBN 13 9783030402440
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages483
- EditorSchütt Kristof T., Chmiela Stefan, Von Lilienfeld O. Anatole, Tkatchenko Alexandre, Tsuda Koji, Müller Klaus-Robert
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Machine Learning Meets Quantum Physics
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Machine Learning Meets Quantum Physics (Lecture Notes in Physics, 968)
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Machine Learning Meets Quantum Physics
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Machine Learning Meets Quantum Physics (Lecture Notes in Physics, 968)
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Machine Learning Meets Quantum Physics
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Springer International Publishing Jun 2020, 2020
ISBN 10: 3030402444
ISBN 13: 9783030402440
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Taschenbuch
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 484 pp. Englisch. Seller Inventory # 9783030402440
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Machine Learning Meets Quantum Physics (Lecture Notes in Physics)
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Machine Learning Meets Quantum Physics
Published by
Springer International Publishing, 2020
ISBN 10: 3030402444
ISBN 13: 9783030402440
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Taschenbuch
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9783030402440
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Machine Learning Meets Quantum Physics
Published by
Springer International Publishing, 2020
ISBN 10: 3030402444
ISBN 13: 9783030402440
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides an in-depth referenced work on the physics-based machine learning techniques that model electronic and atomistic properties of matterHighly interdisciplinary, it focuses on diverse fields of investigation such as physics, chemistry and ma. Seller Inventory # 448681414
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Machine Learning meets Quantum Physics (Lecture Notes in Physics)
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Machine Learning meets Quantum Physics (Lecture Notes in Physics)
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Condition: New. Print on Demand pp. 490. Seller Inventory # 369519449
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