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Acta Numerica

Material type:

Continuing resourcePublication details: CambridgeISSN:

1474-0508

Subject(s):

Mathematics

LOC classification:

https://www.cambridge.org/core/journals/acta-numerica

Summary: Acta Numerica is the top-cited journal for the last two years in MathSciNet. Its annual collection of review articles includes survey papers by leading researchers in numerical analysis and scientific computing. The papers present overviews of recent advances and provide state-of-the-art techniques and analysis. Covering the breadth of numerical analysis, articles are written in a style accessible to researchers at all levels and can serve as advanced teaching aids. Broad subject areas for inclusion are computational methods in linear algebra, optimization, ordinary and partial differential equations, approximation theory, stochastic analysis and nonlinear dynamical systems, as well as the application of computational techniques in science and engineering and the mathematical theory underlying numerical methods.

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Holdings
Cover image	Item type	Current library	Home library	Collection	Shelving location	Call number	Materials specified	Vol info	URL	Copy number	Status	Notes	Date due	Barcode	Item holds	Item hold queue priority	Course reserves
	Electronic Resource	Main Library Serials				HTTPS://WWW.CAMBRIDGE.ORG (Browse shelf(Opens below))			Link to resource	1	Available			050811992
	Electronic Resource	Main Library Serials				HTTPS://WWW.CAMBRIDGE.ORG (Browse shelf(Opens below))				2	Available			0508272018

Acta Numerica is the top-cited journal for the last two years in MathSciNet. Its annual collection of review articles includes survey papers by leading researchers in numerical analysis and scientific computing. The papers present overviews of recent advances and provide state-of-the-art techniques and analysis. Covering the breadth of numerical analysis, articles are written in a style accessible to researchers at all levels and can serve as advanced teaching aids. Broad subject areas for inclusion are computational methods in linear algebra, optimization, ordinary and partial differential equations, approximation theory, stochastic analysis and nonlinear dynamical systems, as well as the application of computational techniques in science and engineering and the mathematical theory underlying numerical methods.

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