Unearthing large pseudoscalar Yukawa couplings with machine learning
Abstract With the Large Hadron Collider’s Run 3 in progress, the 125GeV Higgs boson couplings are being examined in greater detail, while searching for additional scalars. Multi-Higgs frameworks allow Higgs couplings to significantly deviate from Standard Model values, enabling indirect probes of ex...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-07-01
|
| Series: | Journal of High Energy Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/JHEP07(2025)268 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849767569175609344 |
|---|---|
| author | Fernando Abreu de Souza Rafael Boto Miguel Crispim Romão Pedro N. Figueiredo Jorge C. Romão João P. Silva |
| author_facet | Fernando Abreu de Souza Rafael Boto Miguel Crispim Romão Pedro N. Figueiredo Jorge C. Romão João P. Silva |
| author_sort | Fernando Abreu de Souza |
| collection | DOAJ |
| description | Abstract With the Large Hadron Collider’s Run 3 in progress, the 125GeV Higgs boson couplings are being examined in greater detail, while searching for additional scalars. Multi-Higgs frameworks allow Higgs couplings to significantly deviate from Standard Model values, enabling indirect probes of extra scalars. We consider the possibility of large pseudoscalar Yukawa couplings in the softly-broken ℤ2 × ℤ2′ three-Higgs doublet model with CP violating coefficients. To explore the parameter space of the model, we employ a Machine Learning algorithm that significantly enhances sampling efficiency. Using it, we find new regions of parameter space and observable consequences, not found with previous techniques. This method leverages an Evolutionary Strategy to quickly converge towards valid regions with an additional Novelty Reward mechanism. We use this model as a prototype to illustrate the potential of the new techniques, applicable to any Physics Beyond the Standard Model scenario. |
| format | Article |
| id | doaj-art-3b5e6b03b0a54d74b68fcc95a2172cd0 |
| institution | DOAJ |
| issn | 1029-8479 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of High Energy Physics |
| spelling | doaj-art-3b5e6b03b0a54d74b68fcc95a2172cd02025-08-20T03:04:08ZengSpringerOpenJournal of High Energy Physics1029-84792025-07-012025712610.1007/JHEP07(2025)268Unearthing large pseudoscalar Yukawa couplings with machine learningFernando Abreu de Souza0Rafael Boto1Miguel Crispim Romão2Pedro N. Figueiredo3Jorge C. Romão4João P. Silva5LIP — Laboratório de Instrumentação e Física Experimental de Partículas, Escola de Ciências, Campus de Gualtar, Universidade do MinhoDepartamento de Física and CFTP, Instituto Superior Técnico, Universidade de LisboaLIP — Laboratório de Instrumentação e Física Experimental de Partículas, Escola de Ciências, Campus de Gualtar, Universidade do MinhoDepartamento de Física and CFTP, Instituto Superior Técnico, Universidade de LisboaDepartamento de Física and CFTP, Instituto Superior Técnico, Universidade de LisboaDepartamento de Física and CFTP, Instituto Superior Técnico, Universidade de LisboaAbstract With the Large Hadron Collider’s Run 3 in progress, the 125GeV Higgs boson couplings are being examined in greater detail, while searching for additional scalars. Multi-Higgs frameworks allow Higgs couplings to significantly deviate from Standard Model values, enabling indirect probes of extra scalars. We consider the possibility of large pseudoscalar Yukawa couplings in the softly-broken ℤ2 × ℤ2′ three-Higgs doublet model with CP violating coefficients. To explore the parameter space of the model, we employ a Machine Learning algorithm that significantly enhances sampling efficiency. Using it, we find new regions of parameter space and observable consequences, not found with previous techniques. This method leverages an Evolutionary Strategy to quickly converge towards valid regions with an additional Novelty Reward mechanism. We use this model as a prototype to illustrate the potential of the new techniques, applicable to any Physics Beyond the Standard Model scenario.https://doi.org/10.1007/JHEP07(2025)268Multi-Higgs ModelsSpecific BSM Phenomenology |
| spellingShingle | Fernando Abreu de Souza Rafael Boto Miguel Crispim Romão Pedro N. Figueiredo Jorge C. Romão João P. Silva Unearthing large pseudoscalar Yukawa couplings with machine learning Journal of High Energy Physics Multi-Higgs Models Specific BSM Phenomenology |
| title | Unearthing large pseudoscalar Yukawa couplings with machine learning |
| title_full | Unearthing large pseudoscalar Yukawa couplings with machine learning |
| title_fullStr | Unearthing large pseudoscalar Yukawa couplings with machine learning |
| title_full_unstemmed | Unearthing large pseudoscalar Yukawa couplings with machine learning |
| title_short | Unearthing large pseudoscalar Yukawa couplings with machine learning |
| title_sort | unearthing large pseudoscalar yukawa couplings with machine learning |
| topic | Multi-Higgs Models Specific BSM Phenomenology |
| url | https://doi.org/10.1007/JHEP07(2025)268 |
| work_keys_str_mv | AT fernandoabreudesouza unearthinglargepseudoscalaryukawacouplingswithmachinelearning AT rafaelboto unearthinglargepseudoscalaryukawacouplingswithmachinelearning AT miguelcrispimromao unearthinglargepseudoscalaryukawacouplingswithmachinelearning AT pedronfigueiredo unearthinglargepseudoscalaryukawacouplingswithmachinelearning AT jorgecromao unearthinglargepseudoscalaryukawacouplingswithmachinelearning AT joaopsilva unearthinglargepseudoscalaryukawacouplingswithmachinelearning |