| |
Author |
Title |
Year |
Publication |
Volume  |
Pages |
Links |
|
|
Khosa, C.K.; Sanz, V.; Soughton, M. |
Using machine learning to disentangle LHC signatures of Dark Matter candidates |
2021 |
Scipost Physics |
10 |
151 - 26pp |
|
|
|
LHC BSM Reinterpretation Forum (Abdallah, W. et al); Mitsou, V.A.; Sanz, V. |
Reinterpretation of LHC results for new physics: status and recommendations after run 2 |
2020 |
Scipost Physics |
9 |
022 - 45pp |
|
|
|
Cepedello, R.; Esser, F.; Hirsch, M.; Sanz, V. |
Mapping the SMEFT to discoverable models |
2022 |
Journal of High Energy Physics |
09 |
229 - 34pp |
|
|
|
Cepedello, R.; Esser, F.; Hirsch, M.; Sanz, V. |
SMEFT goes dark: Dark Matter models for four-fermion operators |
2023 |
Journal of High Energy Physics |
09 |
081 - 47pp |
|
|
|
Esser, F.; Madigan, M.; Sanz, V.; Ubiali, M. |
On the coupling of axion-like particles to the top quark |
2023 |
Journal of High Energy Physics |
09 |
063 - 39pp |
|
