Abstract
We discuss the current minimisation strategies adopted by research projects involving the determination of parton distribution functions (PDFs) and fragmentation functions (FFs) through the training of neural networks. We present a short overview of a proton PDF determination obtained using the covariance matrix adaptation evolution strategy (CMA-ES) optimisation algorithm. We perform comparisons between the CMA-ES and the standard nodal genetic algorithm (NGA) adopted by the NNPDF collaboration.
| Original language | English |
|---|---|
| Article number | 052007 |
| Pages (from-to) | 1-5 |
| Number of pages | 5 |
| Journal | Journal of Physics : Conference Series |
| Volume | 1085 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 18 Oct 2018 |
| Event | 18th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, ACAT 2017 - Seattle, United States Duration: 21 Aug 2017 → 25 Aug 2017 |
Funding
S. C. is supported by the HICCUP ERC Consolidator grant (614577) and by the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant agreement n◦ 740006). N. H. is supported by an European Research Council Starting Grant “PDF4BSM”.
| Funders | Funder number |
|---|---|
| HICCUP ERC | |
| Horizon 2020 Framework Programme | |
| Seventh Framework Programme | 614577, 740006 |
| European Research Council |
