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  • 1
    Online-Ressource
    Online-Ressource
    Singapore :Springer Nature Singapore :
    UID:
    almahu_9949986186102882
    Umfang: XXIV, 620 p. 68 illus., 22 illus. in color. , online resource.
    Ausgabe: 2nd ed. 2025.
    ISBN: 9789819601004
    Inhalt: This book provides a well-balanced and comprehensive picture based on clear physics, solid mathematical formulation, and state-of-the-art useful numerical methods in deterministic, stochastic, deep neural network machine learning approaches for computer simulations of electromagnetic and transport processes in biology, microwave and optical wave devices, and nano-electronics. Computational research has become strongly influenced by interactions from many different areas including biology, physics, chemistry, engineering, etc. A multifaceted approach addressing the interconnection among mathematical algorithms and physical foundation and application is much needed to prepare graduate students and researchers in applied mathematics and sciences and engineering for innovative advanced computational research in many applications areas, such as biomolecular solvation in solvents, radar wave scattering, the interaction of lights with plasmonic materials, plasma physics, quantum dots, electronic structure, current flows in nano-electronics, and microchip designs, etc.
    Anmerkung: Dielectric constant and fluctuation formulae for molecular dynamics -- Poisson-Boltzmann electrostatics and analytical approximations -- Numerical methods for Poisson-Boltzmann equations -- Random walk stochastic methods for boundary value problems -- Deep Neural Network for Solving PDEs -- Fast algorithms for long-range interactions -- Fast multipole methods for long-range interactions in layered media -- Maxwell equations, potentials, and physical/artificial boundary conditions -- Dyadic Green's functions in layered media -- High-order methods for surface electromagnetic integral equations -- High-order hierarchical N´ed´elec edge elements -- Time-domain methods - discontinuous Galerkin method and Yee scheme -- Scattering in periodic structures and surface plasmons -- Schr¨ odinger equations for waveguides and quantum dots -- Quantum electron transport in semiconductors -- Non-equilibrium Green's function (NEGF) methods for transport -- Numerical methods for Wigner quantum transport -- Hydrodynamic electron transport and finite difference methods -- Transport models in plasma media and numerical methods.
    In: Springer Nature eBook
    Weitere Ausg.: Printed edition: ISBN 9789819600991
    Weitere Ausg.: Printed edition: ISBN 9789819601011
    Weitere Ausg.: Printed edition: ISBN 9789819601028
    Sprache: Englisch
    URL: Volltext  (URL des Erstveröffentlichers)
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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  • 2
    Online-Ressource
    Online-Ressource
    Singapore : Springer | Beijing : Science Press
    UID:
    gbv_1918984484
    Umfang: 1 Online-Ressource (XXIV, 620 Seiten)
    Ausgabe: Second edition
    ISBN: 9789819601004
    Inhalt: This book provides a well-balanced and comprehensive picture based on clear physics, solid mathematical formulation, and state-of-the-art useful numerical methods in deterministic, stochastic, deep neural network machine learning approaches for computer simulations of electromagnetic and transport processes in biology, microwave and optical wave devices, and nano-electronics. Computational research has become strongly influenced by interactions from many different areas including biology, physics, chemistry, engineering, etc. A multifaceted approach addressing the interconnection among mathematical algorithms and physical foundation and application is much needed to prepare graduate students and researchers in applied mathematics and sciences and engineering for innovative advanced computational research in many applications areas, such as biomolecular solvation in solvents, radar wave scattering, the interaction of lights with plasmonic materials, plasma physics, quantum dots, electronic structure, current flows in nano-electronics, and microchip designs, etc.
    Anmerkung: Dielectric constant and fluctuation formulae for molecular dynamics -- Poisson–Boltzmann electrostatics and analytical approximations -- Numerical methods for Poisson–Boltzmann equations -- Random walk stochastic methods for boundary value problems -- Deep Neural Network for Solving PDEs -- Fast algorithms for long-range interactions -- Fast multipole methods for long-range interactions in layered media -- Maxwell equations, potentials, and physical/artificial boundary conditions -- Dyadic Green’s functions in layered media -- High-order methods for surface electromagnetic integral equations -- High-order hierarchical N´ed´elec edge elements -- Time-domain methods – discontinuous Galerkin method and Yee scheme -- Scattering in periodic structures and surface plasmons -- Schr¨ odinger equations for waveguides and quantum dots -- Quantum electron transport in semiconductors -- Non-equilibrium Green’s function (NEGF) methods for transport -- Numerical methods for Wigner quantum transport -- Hydrodynamic electron transport and finite difference methods -- Transport models in plasma media and numerical methods.
    Weitere Ausg.: ISBN 9789819600991
    Weitere Ausg.: ISBN 9789819601011
    Weitere Ausg.: ISBN 9789819601028
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe Cai, Wei Deterministic, stochastic, and deep learning methods for computational electromagnetics Cham : Springer Nature, 2025 ISBN 9789819600991
    Sprache: Englisch
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
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