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Constraining Electroweakinos in the Minimal Dirac Gaugino Model

by Mark D. Goodsell, Sabine Kraml, Humberto Reyes-González, Sophie L. Williamson

Submission summary

As Contributors: Sabine Kraml
Arxiv Link: (pdf)
Date submitted: 2020-07-17 02:00
Submitted by: Kraml, Sabine
Submitted to: SciPost Physics
Discipline: Physics
Subject area: High-Energy Physics - Phenomenology
Approaches: Theoretical, Computational, Phenomenological


Supersymmetric models with Dirac instead of Majorana gaugino masses have distinct phenomenological consequences. In this paper, we investigate the electroweakino sector of the Minimal Dirac Gaugino Supersymmetric Standard Model (MDGSSM) with regards to dark matter (DM) and collider constraints. We delineate the parameter space where the lightest neutralino of the MDGSSM is a viable DM candidate, that makes for at least part of the observed relic abundance while evading constraints from DM direct detection, LEP and lowenergy data, and LHC Higgs measurements. The collider phenomenology of the thus emerging scenarios is characterised by the richer electroweakino spectrum as compared to the Minimal Supersymmetric Standard Model (MSSM) -- 6 neutralinos and 3 charginos instead of 4 and 2 in the MSSM, naturally small mass splittings, and the frequent presence of long-lived particles, both charginos and/or neutralinos. Reinterpreting ATLAS and CMS analyses with the help of SModelS and MadAnalysis 5, we discuss the sensitivity of existing LHC searches for new physics to these scenarios and show which cases can be constrained and which escape detection. Finally, we propose a set of benchmark points which can be useful for further studies, designing dedicated experimental analyses and/or investigating the potential of future experiments.

Current status:
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Submission & Refereeing History

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Submission 2007.08498v1 on 17 July 2020

Reports on this Submission

Anonymous Report 1 on 2020-8-5 Invited Report


The article describes a recast of exisiting experimental LHC studies to derive bounds on supersymmetric models with Dirac gauginos. Specifically, the authors consider the Minimal Dirac Gaugino SUSY Model, which is maybe not the best motivated model from a theoretical point of view, but it may serve as a minimal implementation of the essential features that are shared by a range of supersymmetric Dirac gaugino models. The present work builds on earlier work by the same authors and others. Its main useful conclusions beyond the existing literature are:

It was found that a fast and simplified check of the excluded parameter space from LHC searches using SModelS is mostly adequate, and costly MC simulations are for the most part not needed. This is important since the MDGSSM is only one of many SUSY-like BSM models, and it would be impractical to run MC simulations for a recast of each of these.

The inclusion of LLP constraints has a significant impact on the parameter space that can be probed by LHC experiments. It is not an entirely new insight that LLP bounds are important for probing DM models, but the treatment of these signatures in a mostly automated and efficient computer framework is very useful. I suppose this work can be considered as a demonstration that SModelS can deliver such a framework, which can be adapted by researchers for testing their favorite model.

The authors provide a set of benchmark points which could be helpful for the design of future experimental studies at the LHC experiments. However, the choice of these benchmark points is not fully explained (see below), as some of them appear to offer little incentive for the development for new analysis methods, while on the other hand it is not explained if the 10 proposed points are characteristic of all regions of the full model parameter space.

These items generally meet the SciPost acceptance criteria, since it opens a pathway for future research and its presentation is overall clear and detailed.
However, before the article can be recommended for publication, I ask the authors to consider the following questions:

It is not clear how in what sense Fig.1 displays a comparison to Refs. 92-94. As far as I can see it only shows curves computed in the present work. Also, the meaning of the red curve is not explained.

I'm not sure if I understand the discussion at the end of section 3.2.2. The loop functions x_1 through x_4, when computed explicitly, should reflect the Ward identity relations in (16). Thus when plugging in these loop functions in (17) or in (18), one should manifestly obtain the same result.

Fig.3(b): Contrary to what is written in the text, I cannot see any wino-like points.

What is the meaning of the r_{max} > 0.5 points in Figs. 10 and 11?

The authors use SModelS for the analysis of HSCP limits from Refs.[118,119]. However, they use a different recast code and MC simulations for deriving HSCP limits from [121], requiring significantly more computing resources. Why was it not possible to implement the results from [121] in SModelS?

I do not quite understand the rationale for choosing the benchmark points in section 5. Benchmark points can be very valuable for helping to design experimental studies to extend their coverage and capture previous overlooked signatures. However, points 1 and 6 appear to predict fairly standard signatures that are already pretty well covered by existing LHC searches (and their future extensions to larger data samples). Point 6 will be difficult to probe at LHC simply due to lack of statistics, but otherwise does not require the development of new analysis techniques. Points 7 and 9 both call for a mix of prompt multi-boson and LLP signatures. It is not clear what is the crucial distinction between these two points.

The manuscript fails to cite some well-known previous work on the LHC phenomenology of Dirac gauginos, such as the arXiv numbers
0808.2410, 0902.3795, 1005.0818, 1307.7197, 1803.00624

  • validity: high
  • significance: good
  • originality: ok
  • clarity: high
  • formatting: excellent
  • grammar: excellent

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