PreprintCC BY 4.0HAL
Search for dark matter produced in association with a low-multiplicity jet in proton-proton collisions at √s = 13 TeV
Abstract
A search for dark matter particles is presented using events with large missing transverse momentum and a single energetic jet containing few constituents. The analysis uses proton-proton collision data recorded by the CMS experiment at a center-of-mass energy of 13 TeV. This corresponds to an integrated luminosity of 138 fb−1, recorded during the 2016−2018 LHC data-taking period. This is the first search at the LHC to employ the low-multiplicity jet signature. Supervised machine learning is used to maximize sensitivity to potential signals in this challenging final state. No excess of events over the standard model background prediction is observed. The results are used to set upper limits on the dark matter production cross section at 95% confidence level (CL) within simplified models featuring vector and axial-vector mediators. For a dark matter particle mass of approximately 150 (550) GeV, mediator masses up to 4250 (3500) GeV are excluded at 95% CL.
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- Feasibility of a collider-based detector search for upward-going fermions produced from gravitationally-bound dark matter within the Earth
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BibTeX
@misc{hayrapetyan2026search,
title = {{Search for dark matter produced in association with a low-multiplicity jet in proton-proton collisions at $\sqrts$ = 13 TeV}},
author = {Aram Hayrapetyan and Vladimir Makarenko and Armen Tumasyan and Wolfgang Adam and Janik Walter Andrejkovic and Lisa Benato and Thomas Bergauer and Marko Dragicevic and Cristina Giordano and Priya Sajid Hussain and Manfred Jeitler and Natascha Krammer and Ang Li and Dietrich Liko and Mark Nicholas Matthewman and Ivan Mikulec and Jochen Schieck and Dennis Schwarz and Robert Schoefbeck and Maryam Shooshtari and Mangesh Sonawane and Wolfgang Waltenberger and Claudia Wulz and Tahys Janssen and Hyejin Kwon and Daniel Ocampo Henao and Thomas van Laer and Pierre van Mechelen and Jas Bierkens and Nordin Breugelmans and Jorgen d'Hondt and Soumya Dansana and Alexandre de Moor and Martin Delcourt and Felix Johannes Heyen and Yanwen Hong and Pavlo Kashko and Steven Lowette and Inna Makarenko and Denise Muller and Juhee Song and Stefaan Tavernier and Michael Tytgat and Gerrit van Onsem and Senne van Putte and David Vannerom and Bugra Bilin and Barbara Clerbaux and Aloke Kumar Das and Isabelle de Bruyn and Gilles de Lentdecker and Hugues Evard and Laurent Favart and Paris Gianneios and Ali Khalilzadeh and Fakhri Alam Khan and Andrea Malara and Muhammad Aamir Shahzad and Laurent Thomas and Max Vanden Bemden},
howpublished = {HAL},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.00995},
eprint = {2610.00995},
archivePrefix = {arXiv},
url = {https://hal.science/hal-05820872v1},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Search for dark matter produced in association with a low-multiplicity jet in proton-proton collisions at √s = 13 TeV
AU - Aram Hayrapetyan
AU - Vladimir Makarenko
AU - Armen Tumasyan
AU - Wolfgang Adam
AU - Janik Walter Andrejkovic
AU - Lisa Benato
AU - Thomas Bergauer
AU - Marko Dragicevic
AU - Cristina Giordano
AU - Priya Sajid Hussain
AU - Manfred Jeitler
AU - Natascha Krammer
AU - Ang Li
AU - Dietrich Liko
AU - Mark Nicholas Matthewman
AU - Ivan Mikulec
AU - Jochen Schieck
AU - Dennis Schwarz
AU - Robert Schoefbeck
AU - Maryam Shooshtari
AU - Mangesh Sonawane
AU - Wolfgang Waltenberger
AU - Claudia Wulz
AU - Tahys Janssen
AU - Hyejin Kwon
AU - Daniel Ocampo Henao
AU - Thomas van Laer
AU - Pierre van Mechelen
AU - Jas Bierkens
AU - Nordin Breugelmans
AU - Jorgen d'Hondt
AU - Soumya Dansana
AU - Alexandre de Moor
AU - Martin Delcourt
AU - Felix Johannes Heyen
AU - Yanwen Hong
AU - Pavlo Kashko
AU - Steven Lowette
AU - Inna Makarenko
AU - Denise Muller
AU - Juhee Song
AU - Stefaan Tavernier
AU - Michael Tytgat
AU - Gerrit van Onsem
AU - Senne van Putte
AU - David Vannerom
AU - Bugra Bilin
AU - Barbara Clerbaux
AU - Aloke Kumar Das
AU - Isabelle de Bruyn
AU - Gilles de Lentdecker
AU - Hugues Evard
AU - Laurent Favart
AU - Paris Gianneios
AU - Ali Khalilzadeh
AU - Fakhri Alam Khan
AU - Andrea Malara
AU - Muhammad Aamir Shahzad
AU - Laurent Thomas
AU - Max Vanden Bemden
PY - 2026
DA - 2026/10/01
PB - HAL
DO - 10.48550/arxiv.2610.00995
UR - https://hal.science/hal-05820872v1
AB - A search for dark matter particles is presented using events with large missing transverse momentum and a single energetic jet containing few constituents. The analysis uses proton-proton collision data recorded by the CMS experiment at a center-of-mass energy of 13 TeV. This corresponds to an integrated luminosity of 138 fb^−1, recorded during the 2016−2018 LHC data-taking period. This is the first search at the LHC to employ the low-multiplicity jet signature. Supervised machine learning is used to maximize sensitivity to potential signals in this challenging final state. No excess of events over the standard model background prediction is observed. The results are used to set upper limits on the dark matter production cross section at 95% confidence level (CL) within simplified models featuring vector and axial-vector mediators. For a dark matter particle mass of approximately 150 (550) GeV, mediator masses up to 4250 (3500) GeV are excluded at 95% CL.
ER -