Mathematical methods for molecular science : Theory and applications, visualizations and narrative
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- New York : University Science Books, 2022.
- 534 pages: ill col ; 26 cm
Includes bibliographical references (pages 529-530) and index.
Functions and coordinate systems -- Complex numbers and logarithms -- Differentiation in one and many dimensions -- Scalars, vectors, and vector algebra -- Scalar and vector operators -- Extremizing functions of many variables -- Sequences, series, and expansions -- Integration in one and many dimensions -- Fundamentals of probability and statistics -- Ordinary differential equations -- More ordinary differential equations -- Partial differential equations -- Fourier series, Fourier transforms, and harmonic analysis -- Matrices and matrix algebra -- Eigenvalues and eigenvectors -- Geometric transforms and molecular symmetry.
"Mastery of key ideas in quantum mechanics requires knowledge of operators, differential equations, multidimensional integration, vector algebra, and functions of complex numbers. Statistical thermodynamics and kinetics require facility with partial differentiation, extremizing functions subject to constraints, and knowledge of differential equations. However, a treatment of these topics through specialized courses offered by mathematics departments is prohibitively time consuming for many molecular science majors in the fields of chemistry, biochemistry, biophysics, and materials science. Mathematical Methods for Molecular Science is designed to support a one-semester course that builds on the introductory calculus sequence and covers critical topics in multivariate calculus, ordinary and partial differential equations, and linear algebra"--