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MPSolve (Multiprecision Polynomial Solver) is a package for the approximation of the roots of a univariate polynomial. It uses the Aberth method, [1] combined with a careful use of multiprecision. [2] "Mpsolve takes advantage of sparsity, and has special hooks for polynomials that can be evaluated efficiently by straight-line programs" [3]
The complex conjugate root theorem states that if the coefficients of a polynomial are real, then the non-real roots appear in pairs of the form (a + ib, a – ib).. It follows that the roots of a polynomial with real coefficients are mirror-symmetric with respect to the real axis.
Symbolic Math Toolbox MathWorks: 1989 2008 9.4(2018a) 2018: $3,150 (Commercial), $99 (Student Suite), $700 (Academic), $194 (Home) including required Matlab: Proprietary: Provides tools for solving and manipulating symbolic math expressions and performing variable-precision arithmetic. SymPy: Ondřej Čertík 2006 2007 1.13.2: 11 August 2024: Free
the roots of this irreducible polynomial can be calculated as [5] 1 ± 2 1 / 6 , 1 ± − 1 ± 3 i 2 1 / 3 . {\displaystyle 1\pm 2^{1/6},1\pm {\frac {\sqrt {-1\pm {\sqrt {3}}i}}{2^{1/3}}}.} Even in the case of quartic polynomials , where there is an explicit formula for the roots, solving using the decomposition often gives a simpler form.
MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages. Although MATLAB is intended primarily for numeric computing, an optional toolbox uses the MuPAD symbolic engine allowing access to symbolic computing abilities.
Xcas/Giac is an open-source project developed at the Joseph Fourier University of Grenoble since 2000. Written in C++, maintained by Bernard Parisse's et al. and available for Windows, Mac, Linux and many others platforms. It has a compatibility mode with Maple, Derive and MuPAD software and TI-89, TI-92 and Voyage 200 calculators.
An illustration of Newton's method. In numerical analysis, the Newton–Raphson method, also known simply as Newton's method, named after Isaac Newton and Joseph Raphson, is a root-finding algorithm which produces successively better approximations to the roots (or zeroes) of a real-valued function.
The two square roots of a negative number are both imaginary numbers, and the square root symbol refers to the principal square root, the one with a positive imaginary part. For the definition of the principal square root of other complex numbers, see Square root § Principal square root of a complex number.