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Maxima (/ ˈ m æ k s ɪ m ə /) is a powerful software package for performing computer algebra calculations in mathematics and the physical sciences. It is written in Common Lisp and runs on all POSIX platforms such as macOS , Unix , BSD , and Linux , as well as under Microsoft Windows and Android .
In 1998, Schelter obtained permission to release Maxima as open-source software under the GNU General Public license and the source code was released later that year. Since his death in 2001, a group of Maxima enthusiasts have continued to provide technical support.
Xcas can solve differential equations. Xcas is a user interface to Giac , which is an open source [ 2 ] computer algebra system (CAS) for Windows , macOS and Linux among many other platforms. Xcas is written in C++ . [ 3 ]
The calculus of variations (or variational calculus) is a field of mathematical analysis that uses variations, which are small changes in functions and functionals, to find maxima and minima of functionals: mappings from a set of functions to the real numbers.
In numerical analysis, a quasi-Newton method is an iterative numerical method used either to find zeroes or to find local maxima and minima of functions via an iterative recurrence formula much like the one for Newton's method, except using approximations of the derivatives of the functions in place of exact derivatives.
Elementary algebra, calculus, complex number and polynomial manipulations. Maxima: MIT Project MAC and Bill Schelter et al. 1967 1998 5.46.0 [21] 13 April 2022: Free GNU GPL: General purpose CAS. Continuation of Macsyma; new releases occur approximately two times per year. MuMATH: Soft Warehouse 1970s 1980 MuMATH-83: Discontinued Proprietary ...
SageMath (previously Sage or SAGE, "System for Algebra and Geometry Experimentation" [3]) is a computer algebra system (CAS) with features covering many aspects of mathematics, including algebra, combinatorics, graph theory, group theory, differentiable manifolds, numerical analysis, number theory, calculus and statistics.
In mathematical optimization, the method of Lagrange multipliers is a strategy for finding the local maxima and minima of a function subject to equation constraints (i.e., subject to the condition that one or more equations have to be satisfied exactly by the chosen values of the variables). [1]