REVIEW 2 cited by
Expansion of hypergeometric functions in terms of polylogarithms with nontrivial variable change
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
Hypergeometric functions of one and many variables play an important role in various branches of modern physics and mathematics. Often we have hypergeometric functions with indices linear dependent on a small parameter with respect to which one needs to perform Laurent expansions. Moreover such expansions are desirable to be expressed in terms of well known functions which can be evaluated with arbitrary precision. To solve this problem we use the differential equation method and the reduction of corresponding differential systems to canonical basis. Specifically we will be interested in the generalized hypergeometric functions of one variable together with Appell and Lauricella functions and their expansions in terms of Goncharov polylogarithms. Particular attention will be given to the case of rational indices of considered hypergeometric functions when the reduction to canonical basis involves nontrivial variable change. The article comes with a Mathematica package Diogenes, which provides algorithmic implementation of the required steps.
Forward citations
Cited by 2 Pith papers
-
High-precision numerical evaluation of Lauricella functions
A Mathematica package computes high-precision epsilon-expansions of Lauricella functions using one-dimensional Frobenius series and interpolation.
-
$\texttt{PrecisionLauricella}$: package for numerical computation of Lauricella functions depending on a parameter
PrecisionLauricella is a Mathematica package that computes epsilon-expansions of Lauricella F_A, F_B, and F_D functions for n up to 3 using Frobenius-series analytic continuation.
Discussion (0). Continue with ORCID to comment.