EKO: evolution kernel operators
European Physical Journal C, ISSN: 1434-6052, Vol: 82, Issue: 10
2022
- 24Citations
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Article Description
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.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85140966530&origin=inward; http://dx.doi.org/10.1140/epjc/s10052-022-10878-w; https://link.springer.com/10.1140/epjc/s10052-022-10878-w; https://dx.doi.org/10.1140/epjc/s10052-022-10878-w; https://link.springer.com/article/10.1140/epjc/s10052-022-10878-w
Springer Science and Business Media LLC
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