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dc.contributor.authorSundnes, Joakim
dc.date.accessioned2023-11-13T16:42:26Z
dc.date.available2023-11-13T16:42:26Z
dc.date.issued2024
dc.identifierONIX_20231113_9783031467684_32
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/85081
dc.description.abstractThis open access volume explains the foundations of modern solvers for ordinary differential equations (ODEs). Formulating and solving ODEs is an essential part of mathematical modeling and computational science, and numerous solvers are available in commercial and open source software. However, no single ODE solver is the best choice for every single problem, and choosing the right solver requires fundamental insight into how the solvers work. This book will provide exactly that insight, to enable students and researchers to select the right solver for any ODE problem of interest, or implement their own solvers if needed. The presentation is compact and accessible, and focuses on the large and widely used class of solvers known as Runge-Kutta methods. Explicit and implicit methods are motivated and explained, as well as methods for error control and automatic time step selection, and all the solvers are implemented as a class hierarchy in Python.
dc.languageEnglish
dc.relation.ispartofseriesSimula SpringerBriefs on Computing
dc.subject.otherOrdinary differential equations
dc.subject.otherRunge-Kutta methods
dc.subject.otherscientific programming
dc.subject.otherPython programming
dc.subject.otherobject-oriented programming
dc.subject.otherdifference equations
dc.subject.otheradaptive time step methods
dc.titleSolving Ordinary Differential Equations in Python
dc.typebook
oapen.identifier.doi10.1007/978-3-031-46768-4
oapen.relation.isPublishedBy6c6992af-b843-4f46-859c-f6e9998e40d5
oapen.relation.isFundedByeb9ac1c9-bf74-4c3a-b0a2-e945a77d7280
oapen.relation.isbn9783031467684
oapen.relation.isbn9783031467677
oapen.imprintSpringer Nature Switzerland
oapen.series.number15
oapen.pages114
oapen.place.publicationCham
oapen.grant.number[...]


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