EKO: evolution kernel operators
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 stor...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2022-10-01
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| Series: | European Physical Journal C: Particles and Fields |
| Online Access: | https://doi.org/10.1140/epjc/s10052-022-10878-w |
| _version_ | 1798044494456684544 |
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| author | Alessandro Candido Felix Hekhorn Giacomo Magni |
| author_facet | Alessandro Candido Felix Hekhorn Giacomo Magni |
| author_sort | Alessandro Candido |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T23:04:53Z |
| format | Article |
| id | doaj.art-2aa3aceec5a143878d3b1034e36ab61d |
| institution | Directory Open Access Journal |
| issn | 1434-6052 |
| language | English |
| last_indexed | 2024-04-11T23:04:53Z |
| publishDate | 2022-10-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | European Physical Journal C: Particles and Fields |
| spelling | doaj.art-2aa3aceec5a143878d3b1034e36ab61d2022-12-22T03:58:02ZengSpringerOpenEuropean Physical Journal C: Particles and Fields1434-60522022-10-01821011810.1140/epjc/s10052-022-10878-wEKO: evolution kernel operatorsAlessandro Candido0Felix Hekhorn1Giacomo Magni2Tif Lab, Dipartimento di Fisica, Università di Milano and INFN, Sezione di MilanoTif Lab, Dipartimento di Fisica, Università di Milano and INFN, Sezione di MilanoDepartment of Physics and Astronomy, Vrije UniversiteitAbstract 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.https://doi.org/10.1140/epjc/s10052-022-10878-w |
| spellingShingle | Alessandro Candido Felix Hekhorn Giacomo Magni EKO: evolution kernel operators European Physical Journal C: Particles and Fields |
| title | EKO: evolution kernel operators |
| title_full | EKO: evolution kernel operators |
| title_fullStr | EKO: evolution kernel operators |
| title_full_unstemmed | EKO: evolution kernel operators |
| title_short | EKO: evolution kernel operators |
| title_sort | eko evolution kernel operators |
| url | https://doi.org/10.1140/epjc/s10052-022-10878-w |
| work_keys_str_mv | AT alessandrocandido ekoevolutionkerneloperators AT felixhekhorn ekoevolutionkerneloperators AT giacomomagni ekoevolutionkerneloperators |