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EKO: evolution kernel operators

Authors :
Alessandro Candido
Felix Hekhorn
Giacomo Magni
Source :
European Physical Journal C: Particles and Fields, Vol 82, Iss 10, Pp 1-18 (2022)
Publication Year :
2022
Publisher :
SpringerOpen, 2022.

Abstract

Abstract We present a new QCD evolution library for unpolarized parton distribution functions: EKO. The program solves DGLAP equations up to next-to-next-to-leading order. The unique feature of EKO is the computation of solution operators, which are independent of the boundary condition, can be stored and quickly applied to evolve several initial PDFs. The EKO approach combines the power of N-space solutions with the flexibility of a x-space delivery, that allows for an easy interface with existing codes. The code is fully open source and written in Python, with a modular structure in order to facilitate usage, readability and possible extensions. We provide a set of benchmarks with similar available tools, finding good agreement.

Details

Language :
English
ISSN :
14346052
Volume :
82
Issue :
10
Database :
Directory of Open Access Journals
Journal :
European Physical Journal C: Particles and Fields
Publication Type :
Academic Journal
Accession number :
edsdoj.2aa3aceec5a143878d3b1034e36ab61d
Document Type :
article
Full Text :
https://doi.org/10.1140/epjc/s10052-022-10878-w