Constraining the 3HDM parameter space using active learning

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dc.contributor.author Batra, Nipun
dc.contributor.author Coleppa, Baradhwaj
dc.contributor.author Khanna, Akshat
dc.contributor.author Rai, Santosh Kumar
dc.contributor.author Sarkar, Agnivo
dc.coverage.spatial United States of America
dc.date.accessioned 2025-07-25T11:43:47Z
dc.date.available 2025-07-25T11:43:47Z
dc.date.issued 2025-07
dc.identifier.citation Batra, Nipun; Coleppa, Baradhwaj; Khanna, Akshat; Rai, Santosh Kumar and Sarkar, Agnivo, "Constraining the 3HDM parameter space using active learning", Physical Review D, DOI: 10.1103/t5df-67wh, vol. 112, no. 01, Jul. 2025.
dc.identifier.issn 2470-0010
dc.identifier.issn 2470-0029
dc.identifier.uri https://doi.org/10.1103/t5df-67wh
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/11652
dc.description.abstract One of the standard ways to study scenarios beyond the Standard Model involves extending the Higgs sector. This work examines the three Higgs doublet model (3HDM) in a type-Z or democratic setup, where each Higgs doublet couples exclusively to a specific type of fermion. The particle spectrum of the 3HDM includes four charged Higgs bosons, two 𝐶⁢𝑃-odd scalars, and three 𝐶⁢𝑃-even scalars. This work investigates the allowed mass and coupling parameter space in the type-Z 3HDM after imposing all theoretical and experimental constraints. We extract the allowed parameter space under three distinct alignment-limit conditions or mass hierarchies leveraging machine learning techniques. Specifically, we analyze scenarios where the 125 GeV Higgs is the lightest, an intermediary, or the heaviest 𝐶⁢𝑃-even Higgs boson. Our findings indicate that while a single lighter 𝐶⁢𝑃-even Higgs boson below 125 GeV still remains a possibility, the presence of two lighter Higgses is ruled out.
dc.description.statementofresponsibility by Nipun Batra, Baradhwaj Coleppa, Akshat Khanna, Santosh Kumar Rai and Agnivo Sarkar
dc.format.extent vol. 112, no. 01
dc.language.iso en_US
dc.publisher American Physical Society
dc.title Constraining the 3HDM parameter space using active learning
dc.type Article
dc.relation.journal Physical Review D


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