Analytic polynomial roots within JAX
JIT-compatible fully analytic variant of jax.numpy.roots for small-degree polynomials
Overview
radiax.roots is a drop-in replacement for jax.numpy.roots for polynomials of up to the third degree1. It is fully analytic, with support for complex roots and coefficients. It is JIT-compatible2 and has been benchmarked to be around 15x faster than jax.numpy.roots for cubic polynomials3.
Installation
pip install radiax
Usage
import jax.numpy as jnp
from radiax import roots
# Coefficients of the polynomial: x**3 - 6*x**2 + 11*x - 6
coeffs = jnp.array([1, -6, 11, -6])
# Find the roots of the polynomial
r = roots(coeffs)
print(r)
Footnotes
1 Support for degree 4 (quartic) polynomials has not been implemented yet.
2 Just like with jax.numpy.roots, the optional keyword argument strip_zeros must be set to False for JIT-compatibility.
3 radiax 0.1.0 running on an Intel Core i7-14700 CPU (JAX 0.11.1, Python 3.14.7, Ubuntu 24.04.4).
1 maintainer
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