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LHC data interpretation within the 2HDM type II via a new analysis toolkit

LHC data interpretation within the 2HDM type II via a new analysis toolkit
LHC data interpretation within the 2HDM type II via a new analysis toolkit
We review the status of the 2-Higgs doublet model (2HDM) type-II, in the light of the current experimental results and various theoretical consistency conditions. Compared to the existing literature, in this paper, we apply for the first time a new method that can improve the standard procedure for setting bounds on the 2HDM parameter space, as no experimental evidence has been found so far. Our new numerical framework, called Magellan, and statistical techniques can be applied to any beyond the Standard Model (BSM) scenario. Here, we take as testing ground the 2HDM, particularly as it is physically interesting and moreover characterized by a far from trivial multidimensional parameter space where the effectiveness of the new methods can be proved. Magellan uses a Markov chain Monte Carlo technique for scanning the parameter space and leverages the use of data processing and visualisation methods, allowing the user to perform inference on the model in a complete and efficient way. The novelty of the proposed method is that the parameter space of any BSM theory can be projected onto any bidimensional plane while still retaining all underlying attributes of those points, so that it is possible to investigate the associations between the properties of the various lower dimensional subspaces of the complete parameter space. The Magellan’s website interactive dashboards can be accessed via a public link. Through this website, the user can explore the full parameter space and exploit the phenomenological features of a BSM model with ease.
2470-0010
Byers, Ciara
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Englert, David
b3773c02-ec26-4802-85ba-9b64d319f766
Hays, J
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Moretti, Stefano
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Accomando, Elena
8ebc75d7-bd92-4f70-a974-7bc15ebf088f
Byers, Ciara
0e7c62f5-222e-4c65-9edf-0d5315cfc78c
Englert, David
b3773c02-ec26-4802-85ba-9b64d319f766
Hays, J
16790487-d8b5-4288-9bab-1419d93842df
Moretti, Stefano
b57cf0f0-4bc3-4e02-96e3-071255366614
Accomando, Elena
8ebc75d7-bd92-4f70-a974-7bc15ebf088f

Byers, Ciara, Englert, David, Hays, J, Moretti, Stefano and Accomando, Elena (2022) LHC data interpretation within the 2HDM type II via a new analysis toolkit. Physical Review D, 105 (11), [115004].

Record type: Article

Abstract

We review the status of the 2-Higgs doublet model (2HDM) type-II, in the light of the current experimental results and various theoretical consistency conditions. Compared to the existing literature, in this paper, we apply for the first time a new method that can improve the standard procedure for setting bounds on the 2HDM parameter space, as no experimental evidence has been found so far. Our new numerical framework, called Magellan, and statistical techniques can be applied to any beyond the Standard Model (BSM) scenario. Here, we take as testing ground the 2HDM, particularly as it is physically interesting and moreover characterized by a far from trivial multidimensional parameter space where the effectiveness of the new methods can be proved. Magellan uses a Markov chain Monte Carlo technique for scanning the parameter space and leverages the use of data processing and visualisation methods, allowing the user to perform inference on the model in a complete and efficient way. The novelty of the proposed method is that the parameter space of any BSM theory can be projected onto any bidimensional plane while still retaining all underlying attributes of those points, so that it is possible to investigate the associations between the properties of the various lower dimensional subspaces of the complete parameter space. The Magellan’s website interactive dashboards can be accessed via a public link. Through this website, the user can explore the full parameter space and exploit the phenomenological features of a BSM model with ease.

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PhysRevD.105.115004 - Version of Record
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More information

Accepted/In Press date: 12 April 2022
e-pub ahead of print date: 1 June 2022

Identifiers

Local EPrints ID: 472275
URI: http://eprints.soton.ac.uk/id/eprint/472275
ISSN: 2470-0010
PURE UUID: ab01d4ba-c0d0-4dd0-8b9b-a3aa19327110
ORCID for Stefano Moretti: ORCID iD orcid.org/0000-0002-8601-7246

Catalogue record

Date deposited: 30 Nov 2022 17:43
Last modified: 01 Dec 2022 02:38

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Contributors

Author: Ciara Byers
Author: David Englert
Author: J Hays
Author: Stefano Moretti ORCID iD
Author: Elena Accomando

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