EKO: Evolution Kernel Operators
Alessandro Candido, Felix Hekhorn, Giacomo Magni

TL;DR
EKO is an open-source Python library that efficiently solves QCD DGLAP evolution equations for unpolarized parton distribution functions, enabling fast, flexible, and accurate evolution with a modular design.
Contribution
It introduces a novel approach to compute solution operators for DGLAP equations, independent of boundary conditions, enhancing flexibility and speed in PDF evolution.
Findings
Good agreement with existing tools in benchmarks
Solution operators are reusable and boundary-condition independent
Flexible interface with existing QCD evolution codes
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 -space solutions with the flexibility of a -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.
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Taxonomy
TopicsAdvanced Data Storage Technologies · Computational Physics and Python Applications · Particle physics theoretical and experimental studies
