Numerical Approximations of Stochastic Maxwell Equations: via Structure-Preserving Algorithms VJDJXTY782

URI	`m2://res/VJDJXTY782`
Kind	monograph
Creators	Chuchu Chen, Jialin Hong, Lihai Ji
Date	2023
MSC	65-01, 60-01, 65C30, 60H35, 35Q61, 60F99, 65L06, 65P10
Scope	in

Expressions

e1: edition

Language	en
Date	2023
Ids	DOI 10.1007/978-981-99-6686-8, zbl 1542.65001, zbl_id 7795963

m1: print, Springer Nature Singapore, 2023 (record). isbn 9789819966851, isbn 9789819966868

Relations

part_of Lecture Notes in Mathematics

References

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Maxwell’s Equations in Periodic Structures (e1)
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Stochastic Partial Differential Equations: An Introduction (e1)
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Numerical Approximations of Stochastic Maxwell Equations: via Structure-Preserving Algorithms (e1)
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An Introduction to Infinite-Dimensional Analysis (e1)
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Invariant Measures for Stochastic Nonlinear Schrödinger Equations: Numerical Approximations and Symplectic Structures (e1)
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Probability Theory: A Comprehensive Course (e1)
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Optimal Transport (e1)
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Numerical Approximations of Stochastic Maxwell Equations: via Structure-Preserving Algorithms (e1)
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Symplectic Integration of Stochastic Hamiltonian Systems (e1)
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Numerical Approximations of Stochastic Maxwell Equations: via Structure-Preserving Algorithms (e1)
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Strong and Weak Approximation of Semilinear Stochastic Evolution Equations (e1)
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Catalogue records

springer-series: 10.1007/978-981-99-6686-8 (work)
zbmath_search: 7795963 (work)