Search for Black Holes and Sphalerons Using Novel MachineLearning Techniques at CMS

Authors

DOI:

https://doi.org/10.31526/PHEP.2026.21

Keywords:

pp collisions, Beyond standard model, Black holes and sphalerons, Phase space distance, Machine learning

Abstract

A comprehensive search for microscopic black holes and electroweak sphalerons is presented, using proton-proton collision data collected by the CMS detector during 2016–2018, corresponding to an inte-
grated luminosity of 138 fb−1. A novel tool has been developed to identify collider events with distinct
kinematic features, based on the phase space distance between events. In the context of models with large
extra dimensions, semiclassical black holes with masses below 9.0-11.4 TeV are excluded by this search,
significantly extending previous sensitivity. Additionally, a dedicated search for electroweak sphaleron
transitions has been performed. An upper limit of 0.0025 is set at 95% confidence level on the fraction of
quark-quark interactions with center-of-mass energy above the nominal threshold of 9 TeV that result in
sphaleron transitions.

Author Biographies

  • Tamas Almos Vami, Department of Physics, University of California Santa Barbara, Santa Barbara, CA 93106, USA

    Postdoctoral scholar, Department of Physics, University of California Santa Barbara

  • Danyi Zhang, Department of Physics, University of California Santa Barbara, Santa Barbara, CA 93106, USA

    Graduate student, Department of Physics, University of California Santa Barbara

Downloads

Published

2026-05-05

Issue

Volume 2026

Section

BSM 2025 Conference Proceeding

How to Cite

Search for Black Holes and Sphalerons Using Novel MachineLearning Techniques at CMS. (2026). Progress in High Energy Physics PHEP, 2026(1). https://doi.org/10.31526/PHEP.2026.21