Mpmath is a pure-Python library for arbitrary-precision floating-point arithmetic. It implements the standard functions from Python’s math and cmath modules (exp, log, sin, etc.), plus a few nonelementary special functions (gamma, zeta, etc.), and has utilities for arbitrary-precision numerical differentiation, integration, root-finding, and interval arithmetic. It supports unlimited exponent sizes, has full support for complex numbers, and offers better performance than Python’s standard decimal library. Mpmath is lightweight and easy to install or include in other software due to being written entirely in Python with no additional dependencies. (Source:

References in zbMATH (referenced in 31 articles )

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  1. Akbary, Amir; Francis, Forrest J.: Euler’s function on products of primes in a fixed arithmetic progression (2020)
  2. Johansson, Fredrik: Computing the Lambert W function in arbitrary-precision complex interval arithmetic (2020)
  3. Chen, Hao: Minimal twin surfaces (2019)
  4. Codenotti, Luca; Lewicka, Marta: Visualization of the convex integration solutions to the Monge-Ampère equation (2019)
  5. Comsa, Iulia M.; Firsching, Moritz; Fischbacher, Thomas: SO(8) supergravity and the magic of machine learning (2019)
  6. Fasi, Massimiliano; Higham, Nicholas J.: An arbitrary precision scaling and squaring algorithm for the matrix exponential (2019)
  7. Herbach, Ulysse: Stochastic gene expression with a multistate promoter: breaking down exact distributions (2019)
  8. Johansson, Fredrik; Blagouchine, Iaroslav V.: Computing Stieltjes constants using complex integration (2019)
  9. Steven G. Murray, Francis J. Poulin: hankel: A Python library for performing simple and accurate Hankel transformations (2019) arXiv
  10. Fasi, Massimiliano; Higham, Nicholas J.: Multiprecision algorithms for computing the matrix logarithm (2018)
  11. Johansson, Fredrik: Numerical integration in arbitrary-precision ball arithmetic (2018)
  12. Navas-Palencia, Guillermo: Fast and accurate algorithm for the generalized exponential integral (E_\nu(x)) for positive real order (2018)
  13. Navas-Palencia, Guillermo: High-precision computation of the confluent hypergeometric functions via Franklin-Friedman expansion (2018)
  14. Asghar, Hassan Jameel; Kaafar, Mohamed Ali: When are identification protocols with sparse challenges safe? The case of the Coskun and Herley attack (2017)
  15. Garunkštis, Ramūnas; Tamošiūnas, Rokas: Symmetry of zeros of Lerch zeta-function for equal parameters (2017)
  16. Gates, Alexander J.; Ahn, Yong-Yeol: The impact of random models on clustering similarity (2017)
  17. Hokanson, Jeffrey M.: Projected nonlinear least squares for exponential Fitting (2017)
  18. Platt, David J.: Isolating some non-trivial zeros of zeta (2017)
  19. Candy, J.; Belli, E. A.; Bravenec, R. V.: A high-accuracy Eulerian gyrokinetic solver for collisional plasmas (2016)
  20. Navas-Palencia, Guillermo; Arratia, Argimiro: On the computation of confluent hypergeometric functions for large imaginary part of parameters (b) and (z) (2016)

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