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Computational Mathematics with SageMath [Zimmermann]
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Computational Mathematics with SageMath (2018), by Paul Zimmermann and numerous contributors, is a comprehensive introduction to using SageMath, an open-source mathematical system built around Python. The book’s central aim is to connect mathematical theory with actual computation, showing students, teachers, researchers, and engineers how to use a computer without losing the underlying mathematical reasoning. It begins with fundamental Sage operations, symbolic and numerical calculations, programming, data structures, and graphics, before moving into computational domains, number theory, polynomials, linear algebra, and systems of polynomial equations. 

The later chapters expand into more advanced computational mathematics: differential equations, floating-point arithmetic, nonlinear equations, numerical linear algebra, numerical integration, combinatorics, graph theory, and linear and mixed-integer programming. A particularly important theme is the interaction between exact mathematics and numerical computation—for example, symbolic linear algebra over integers or finite fields is treated separately from floating-point numerical methods, while Gröbner bases are introduced for multivariable polynomial systems. Overall, the book functions both as a practical SageMath manual and as a mathematical textbook demonstrating how computation can be used to explore, solve, visualize, and experimentally investigate mathematical problems. 

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