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Extending the reach of LHC searches using displaced dimuons

Extending the reach of LHC searches using displaced dimuons

Wolfgang Adam (ORCID: )
  • Grant DOI 10.55776/P33693
  • Funding program Principal Investigator Projects
  • Status ended
  • Start December 1, 2020
  • End November 30, 2024
  • Funding amount € 395,042

Disciplines

Physics, Astronomy (100%)

Keywords

    LHC, CMS, Long lived particles, Displaced muons, BSM physics, Dark photons

Abstract Final report

The discovery of a new particle, the Higgs boson, at the Large Hadron Collider (LHC) and the following measurements of its properties have been a success of the LHC and of the theory called standard model of particle physics. At the same time, this standard theory seems incomplete since it fails at providing an explanation to a number of fundamental questions in particle physics. In an attempt to answer some of these important questions theorists try to extend it and predict yet undiscovered particles and forces. We therefore want to search for signs of new particles in the available data and the data we will take in following years. Many of these extended theories predict new particles which would only very feebly interact with the known particles. This implies that they will need more time to decay back to the known particles after their creation in LHC collisions. In consequence, they might travel centimeters or even meters before decaying to detectable particles. This type of experimental signature is challenging and until now has only been sparsely covered. Using techniques never tried before, we aim to enable searches for new long-lived particles in data to be taken with the CMS experiment in the next run of the LHC. We target a prominent, spectacular, theoretically well motivated and yet very little investigated signature: muon pairs emerging from decays of such new particles up to several meters from the collision point. These muons can be detected and reconstructed using muon detectors located in the outermost layers of CMS. The analysis of the already collected data revealed several limitations, notably in the trigger system defining which collisions are recorded, currently preventing the exploration of long-lived particles with large lifetimes and/or low masses. We plan to exploit a newly developed processor to be introduced in the hardware part of CMS trigger which will use algorithms specifically aiming at finding displaced particle tracks in muon detector signals. Building on this improvement, we will powerfully extend the sensitivity of our search for long-lived particles decaying to displaced muon pairs and allow CMS to explore a very attractive uncharted new physics territory in the data to be collected in next few years.

The Standard Model of particle physics successfully describes a vast array of measurements of properties of fundamental constituents of matter from CERN's Large Hadron Collider (LHC) and other experiments. However, it does not account for certain key phenomena, such as the evidence for dark matter in our universe. Many proposed extensions of the standard model predict new particles that interact only feebly with known matter, some of which could be linked to dark matter. This project aimed to search for such elusive particles in high-energy proton-proton collisions recorded by the CMS experiment at the LHC. These weakly interacting, neutral particles could travel undetected through much of the detector before decaying into Standard Model particles. The study focused on events where such "displaced" decays would produce a pair of oppositely charged muons at a macroscopic distance from the primary collision point - our "signal". Detecting these events is particularly challenging, as the LHC detectors were originally designed and optimized for particles produced near the collision point. A crucial aspect of the project was improving the first stage of the selection process, implemented in custom-designed electronics, as only a small fraction of collision events can be recorded for further analysis. At this stage, standard algorithms underestimated the momentum of displaced muons, causing many signal events to be missed. The project developed and deployed new, more sophisticated algorithms that removed this bias, more than tripling the efficiency of capturing potential signals at large displacements. Another challenge was making optimal use of the partial information available for muon reconstruction, as - depending on their displacement - signal muons miss some or all measurements in CMS's inner tracker. The study analyzed data from 2022, the first year of LHC's third running period, and successfully released the first direct search results from any major LHC experiment using this dataset - just 9 months after the data were recorded. The observed event counts were found to be consistent with background expectations from Standard Model processes, muons from cosmic radiation, and detector effects. The results were used to constrain parameters of two proposed extensions of the standard model, achieving sensitivity comparable to previous studies despite using 2.5 times less data. In combination, world-leading limits were placed on one of the models that features a "dark photon". The results were documented in a doctoral thesis, published in a journal, and presented at major international conferences. Beyond these specific interpretations, the experimental results will be a basis for the community to probe new models in the future. The project also identified directions for further optimization for the most effective use of the full LHC Run-3 dataset.

Research institution(s)
  • Österreichische Akademie der Wissenschaften - 100%

Research Output

  • 6 Publications
  • 1 Datasets & models
  • 5 Disseminations
  • 1 Scientific Awards
  • 1 Fundings
Publications
  • 2025
    Title Dark sector searches with the CMS experiment
    DOI 10.1016/j.physrep.2024.09.013
    Type Journal Article
    Journal Physics Reports
  • 2024
    Title Exploring Long-Lived Particles decaying into Displaced Dimuons with the CMS experiment
    Type Other
    Author Sonawane
    Link Publication
  • 2024
    Title Exploring Long-Lived Particles decaying into Displaced Dimuons with the CMS experiment
    Type PhD Thesis
    Author Mangesh Sonawane
    Link Publication
  • 2024
    Title Search for long-lived particles decaying to final states with a pair of muons in proton-proton collisions at $$ \sqrt{s} $$ = 13.6 TeV
    DOI 10.1007/jhep05(2024)047
    Type Journal Article
    Author Hayrapetyan A
    Journal Journal of High Energy Physics
  • 2024
    Title Searches in CMS for long-lived particles and other non-conventional signatures
    DOI 10.22323/1.476.0246
    Type Conference Proceeding Abstract
    Author Escalante Del Valle A
    Pages 246
  • 2022
    Title Search for long-lived particles decaying to a pair of muons in proton-proton collisions at s = 13 TeV
    Type Conference Proceeding Abstract
    Author Sonawane
    Conference Rencontres de Moriond 2022: ElectroWeak Session
    Pages 425
    Link Publication
Datasets & models
  • 2024 Link
    Title HepData entry
    DOI 10.17182/hepdata.146759.v2
    Type Database/Collection of data
    Public Access
    Link Link
Disseminations
  • 2023 Link
    Title CERN news
    Type Engagement focused website, blog or social media channel
    Link Link
  • 2022
    Title Dark matter day
    Type A talk or presentation
  • 2023
    Title International masterclass / CMS data
    Type Participation in an activity, workshop or similar
  • 2023 Link
    Title Physics briefing
    Type Engagement focused website, blog or social media channel
    Link Link
  • 2022 Link
    Title HEPHY news
    Type Engagement focused website, blog or social media channel
    Link Link
Scientific Awards
  • 2022
    Title Large Hadron Collider Physics conference
    Type Personally asked as a key note speaker to a conference
    Level of Recognition Continental/International
Fundings
  • 2023
    Title Atracción de Talento de la Comunidad de Madrid
    Type Research grant (including intramural programme)
    Start of Funding 2023
    Funder Comunidad de Madrid

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