Speaker
Description
"Semi-visible jets (SVJs) provide a characteristic collider signature of strongly interacting dark sectors, in which the key model parameter rinv controls the fraction of dark hadrons decaying to dark matter candidates. Dedicated searches for SVJs have been performed at the LHC. Both CMS and ATLAS have probed resonant s-channel SVJ production and set constraints on the corresponding signal models [1, 2], while ATLAS has also searched for non-resonant t-channel production using the characteristic correlation between jets and missing transverse momentum [3].
A previous ISR-assisted study by Liu and Pedro showed that an energetic photon or jet provides additional kinematic information for SVJ events and introduced an analytical estimator for the invisible fraction under a collinear approximation [4]. In this work, a regression model is developed to reconstruct rinv in SVJ events produced in association with an energetic photon. The model uses information from high-level physics objects only, and the training procedure is optimized to ensure applicability. The performance is found to be robust against varying signal parameters, and rinv can be reconstructed with improved precision compared with the previously developed analytical method. It offers a new approach to conduct SVJ searches that can potentially unify both s-channel and t-channel production, enhancing the sensitivity.
References
[1] CMS collaboration, Search for resonant production of strongly coupled dark matter in
proton-proton collisions at 13 TeV, JHEP 06 (2022) 156.
[2] ATLAS collaboration, Search for new physics in final states with semivisible jets or
anomalous signatures using the ATLAS detector, Phys. Rev. D 112 (2025) 012021.
[3] ATLAS collaboration, Search for non-resonant production of semi-visible jets using Run 2
data in ATLAS, Phys. Lett. B 848 (2024) 138324.
[4] B. Liu and K. Pedro, Semi-visible jets + X: illuminating dark showers with radiation, JHEP
12 (2024) 105"
