The galois library is a Python 3 package that extends NumPy arrays to operate over finite fields.

The user creates a FieldArray subclass using GF = galois.GF(p**m). GF is a subclass of numpy.ndarray and its constructor x = GF(array_like) mimics the signature of numpy.array(). The FieldArray x is operated on like any other NumPy array except all arithmetic is performed in \(\mathrm{GF}(p^m)\), not \(\mathbb{R}\).

Internally, the finite field arithmetic is implemented by replacing NumPy ufuncs. The new ufuncs are written in pure Python and just-in-time compiled with Numba. The ufuncs can be configured to use either lookup tables (for speed) or explicit calculation (for memory savings).


The algorithms implemented in the NumPy ufuncs are not constant-time, but were instead designed for performance. As such, the library could be vulnerable to a side-channel timing attack. This library is not intended for production security, but instead for research & development, reverse engineering, cryptanalysis, experimentation, and general education.


  • Supports all Galois fields \(\mathrm{GF}(p^m)\), even arbitrarily-large fields!

  • Faster than native NumPy! GF(x) * GF(y) is faster than (x * y) % p for \(\mathrm{GF}(p)\).

  • Seamless integration with NumPy – normal NumPy functions work on FieldArray instances.

  • Linear algebra over finite fields using normal numpy.linalg functions.

  • Linear transforms over finite fields, such as the FFT with numpy.fft.fft() and the NTT with ntt().

  • Functions to generate irreducible, primitive, and Conway polynomials.

  • Univariate polynomials over finite fields with Poly.

  • Forward error correction codes with BCH and ReedSolomon.

  • Fibonacci and Galois linear-feedback shift registers over any finite field with FLFSR and GLFSR.

  • Various number theoretic functions.

  • Integer factorization and accompanying algorithms.

  • Prime number generation and primality testing.


  • Elliptic curves over finite fields

  • Galois ring arrays

  • GPU support


The galois library is an extension of, and completely dependent on, NumPy. It also heavily relies on Numba and the LLVM just-in-time compiler for optimizing performance of the finite field arithmetic.

Frank Luebeck’s compilation of Conway polynomials and Wolfram’s compilation of primitive polynomials are used for efficient polynomial lookup, when possible.

Sage is used extensively for generating test vectors for finite field arithmetic and polynomial arithmetic. SymPy is used to generate some test vectors. Octave is used to generate test vectors for forward error correction codes.

This library would not be possible without all of the other libraries mentioned. Thank you to all their developers!


If this library was useful to you in your research, please cite us. Following the GitHub citation standards, here is the recommended citation.

   title = {{Galois: A performant NumPy extension for Galois fields}},
   author = {Hostetter, Matt},
   month = {11},
   year = {2020},
   url = {https://github.com/mhostetter/galois},
Hostetter, M. (2020). Galois: A performant NumPy extension for Galois fields [Computer software]. https://github.com/mhostetter/galois

Last update: May 18, 2022