David Hyde and Alex Pothen introduce the Special Issue on Quantum Computing and survey some exciting technical developments.
Quantum algorithms can be understood through linear algebra and offer different tradeoffs than classical algorithms.
The fusion of machine learning and quantum computing has created an unprecedented avenue for innovation.
Quantum computing promises enormous computing power at low costs, marking a new chapter for financial mathematics.
It is quite difficult to fully harness the potential of quantum computers and outperform classical computers.
The High School Mathematical Contest in Modeling tasked students with two open-ended, real-world problems.
The Hackathon encouraged participants to tackle questions about worldwide energy data availability and solar resource potential.
Mark Levi draws connections between the conformal equivalence and electrical resistance of annular regions.
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2018 / xvi + 570 pages / softcover / ISBN 978-1-611975-09-3 / List Price $89.00 / SIAM Member Price $62.30 / Order Code: CS18
Keywords: conservation laws, monotone schemes, high-order methods, WENO/ENO methods, discontinuous Galerkin methids, spectral methods
Contents Preface Index
Conservation laws are the mathematical expression of the principles of conservation and provide effective and accurate predictive models of our physical world. Although intense research activity during the last decades has led to substantial advances in the development of powerful computational methods for conservation laws, their solution remains a challenge and many questions are left open; thus it is an active and fruitful area of research.
Numerical Methods for Conservation Laws: From Analysis to Algorithms
Code and other supplemental material will be available online at publication.
Audience This book is intended for graduate students in computational mathematics and researchers seeking a comprehensive introduction to modern methods for solving conservation laws. Students and researchers in applied sciences and engineering will benefit from the book’s emphasis on algorithmic aspects of complex algorithms. The text also includes extensive references which allows researchers to pursue advanced research and results. About the Author Jan S. Hesthaven is Dean of Basic Sciences, Professor of Mathematics, and holds the Chair of Computational Mathematics and Simulation Science at Ecole Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. Prior to joining EPFL in 2013, he was Professor of Applied Mathematics at Brown University. He has worked for more than two decades on the development, analysis, and application of modern computational methods for linear and nonlinear wave problems, with an emphasis on high-order accurate methods. He is an Alfred P. Sloan Fellow (2001), an NSF Career award winner (2002), and a SIAM Fellow (2014).
ISBN 9781611975093
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