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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This primer describes the general model independent searches for new physics phenomena beyond the Standard Model of particle physics. First, the motivation for performing general model independent experimental searches for new physics is presented by giving an overview of the current theoretical understanding of particle physics in terms of the Standard Model of particle physics and its shortcomings. Then, the concept and features of general model independent search for new physics at collider based experiments is explained. This is followed by an overview of such searches performed in past high energy physics experiments and the current status of such searches, particularly in the context of the experiments at the LHC. Finally, the future prospects of such general model independent searches, with possible improvements using new tools such as machine learning techniques, is discussed.…

240 Seiten mit vielen Abbildungen Sauber und gut erhaltener Band ohne Gebrauchsspuren.-Aussagekräftige Bebilderung, Sprache: Deutsch Gewicht in Gramm: 1210 4°,farbig illustrierter Originalpappeinband.

Paperback/ broschiert. Zustand: Gut. 125 S. Mathematikwissenschaften Algebra Algorithmen Brownish cover and paper. Guter Zustand/ Good. Ex-Library., leichte Gebrauchsspuren ha1070202 Sprache: Englisch Gewicht in Gramm: 250.

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Zustand: New. pp. 382.

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Hardback. Zustand: New. Reprint 2024. No detailed description available for "Modern Algorithms for Large Sparse Eigenvalue Problems".

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Zustand: New. pp. 428 1st ed. 2019 edition NO-PA16APR2015-KAP.

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Taschenbuch. Zustand: Neu. Advanced Finite Element Methods with Applications | Selected Papers from the 30th Chemnitz Finite Element Symposium 2017 | Thomas Apel (u. a.) | Taschenbuch | Lecture Notes in Computational Science and Engineering | xxii | Englisch | 2020 | Springer | EAN 9783030142469 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Highperformancecomputinghaschangedthewayinwhichscienceprogresses. During the last 20 years the increase in computing power, the development of e ective algorithms, and the application of these tools in the area of physics and engineering has been decisive in the advancement of our technological world. These abilities have allowed to treat problems with a complexity which had been out of reach for analytical approaches. While the increase in perf- mance of single processes has been immense the increase of massive parallel computing as well as the advent of clustercomputershas opened up the pos- bilities to study realistic systems. This book presents major advances in high performance computing as well as major advances due to high performance computing. The progress made during the last decade rests on the achie- ments in three distinct science areas. Openandpressingproblemsinphysicsandmechanicalengineeringarethe drivingforcebehindthedevelopmentofnewtoolsandnewapproachesinthese science areas. The treatment of complex physical systems with frustration and disorder, the analysis of the elastic and non-elastic movement of solids as well as the analysis of coupled uid systems, pose problems which are open to a numerical analysis only with state of the art computing power and algorithms. The desire of scienti c accuracy and quantitative precision leads to an enormous demand in computing power. Asking the right questions in these areas lead to new insights which have not been available due to other means like experimental measurements. Thesecondareawhichisdecisivefore ectivehighperformancecomputing is a realm of e ective algorithms.…

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Hardback. Zustand: New. Reprint 2024. No detailed description available for "Modern Algorithms for Large Sparse Eigenvalue Problems".

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - No detailed description available for 'Modern Algorithms for Large Sparse Eigenvalue Problems'.