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Extraction of quantifiable information from complex systems

In April 2007, the  Deutsche Forschungsgemeinschaft (DFG) approved the  Priority Program 1324 “Mathematical Methods for Extracting Quantifiable Information from Complex Systems.” This volume presents a comprehensive overview of the most important results obtained over the course of the program.   Ma...

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Autores principales: Dahlke, Stephan, Dahmen, Wolfgang, Griebel, Michael, Hackbusch, Wolfgang, Ritter, Klaus, Schneider, Reinhold, Schwab, Christoph, Yserentant, Harry
Lenguaje:eng
Publicado: Springer 2014
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-08159-5
http://cds.cern.ch/record/1973540
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author Dahlke, Stephan
Dahmen, Wolfgang
Griebel, Michael
Hackbusch, Wolfgang
Ritter, Klaus
Schneider, Reinhold
Schwab, Christoph
Yserentant, Harry
author_facet Dahlke, Stephan
Dahmen, Wolfgang
Griebel, Michael
Hackbusch, Wolfgang
Ritter, Klaus
Schneider, Reinhold
Schwab, Christoph
Yserentant, Harry
author_sort Dahlke, Stephan
collection CERN
description In April 2007, the  Deutsche Forschungsgemeinschaft (DFG) approved the  Priority Program 1324 “Mathematical Methods for Extracting Quantifiable Information from Complex Systems.” This volume presents a comprehensive overview of the most important results obtained over the course of the program.   Mathematical models of complex systems provide the foundation for further technological developments in science, engineering and computational finance.  Motivated by the trend toward steadily increasing computer power, ever more realistic models have been developed in recent years. These models have also become increasingly complex, and their numerical treatment poses serious challenges.   Recent developments in mathematics suggest that, in the long run, much more powerful numerical solution strategies could be derived if the interconnections between the different fields of research were systematically exploited at a conceptual level. Accordingly, a deeper understanding of the mathematical foundations as well as the development of new and efficient numerical algorithms were among the main goals of this Priority Program.   The treatment of high-dimensional systems is clearly one of the most challenging tasks in applied mathematics today. Since the problem of high-dimensionality appears in many fields of application, the above-mentioned synergy and cross-fertilization effects were expected to make a great impact. To be truly successful, the following issues had to be kept in mind: theoretical research and practical applications had to be developed hand in hand; moreover, it has proven necessary to combine different fields of mathematics, such as numerical analysis and computational stochastics. To keep the whole program sufficiently focused, we concentrated on specific but related fields of application that share common characteristics and, as such, they allowed us to use closely related approaches.  
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spelling cern-19735402021-04-21T20:41:36Zdoi:10.1007/978-3-319-08159-5http://cds.cern.ch/record/1973540engDahlke, StephanDahmen, WolfgangGriebel, MichaelHackbusch, WolfgangRitter, KlausSchneider, ReinholdSchwab, ChristophYserentant, HarryExtraction of quantifiable information from complex systemsMathematical Physics and MathematicsIn April 2007, the  Deutsche Forschungsgemeinschaft (DFG) approved the  Priority Program 1324 “Mathematical Methods for Extracting Quantifiable Information from Complex Systems.” This volume presents a comprehensive overview of the most important results obtained over the course of the program.   Mathematical models of complex systems provide the foundation for further technological developments in science, engineering and computational finance.  Motivated by the trend toward steadily increasing computer power, ever more realistic models have been developed in recent years. These models have also become increasingly complex, and their numerical treatment poses serious challenges.   Recent developments in mathematics suggest that, in the long run, much more powerful numerical solution strategies could be derived if the interconnections between the different fields of research were systematically exploited at a conceptual level. Accordingly, a deeper understanding of the mathematical foundations as well as the development of new and efficient numerical algorithms were among the main goals of this Priority Program.   The treatment of high-dimensional systems is clearly one of the most challenging tasks in applied mathematics today. Since the problem of high-dimensionality appears in many fields of application, the above-mentioned synergy and cross-fertilization effects were expected to make a great impact. To be truly successful, the following issues had to be kept in mind: theoretical research and practical applications had to be developed hand in hand; moreover, it has proven necessary to combine different fields of mathematics, such as numerical analysis and computational stochastics. To keep the whole program sufficiently focused, we concentrated on specific but related fields of application that share common characteristics and, as such, they allowed us to use closely related approaches.  Springeroai:cds.cern.ch:19735402014
spellingShingle Mathematical Physics and Mathematics
Dahlke, Stephan
Dahmen, Wolfgang
Griebel, Michael
Hackbusch, Wolfgang
Ritter, Klaus
Schneider, Reinhold
Schwab, Christoph
Yserentant, Harry
Extraction of quantifiable information from complex systems
title Extraction of quantifiable information from complex systems
title_full Extraction of quantifiable information from complex systems
title_fullStr Extraction of quantifiable information from complex systems
title_full_unstemmed Extraction of quantifiable information from complex systems
title_short Extraction of quantifiable information from complex systems
title_sort extraction of quantifiable information from complex systems
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-319-08159-5
http://cds.cern.ch/record/1973540
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