A Higgsino in supersymmetric standard models can play the role of a dark matter particle. In conjunction with the naturalness criterion, the Higgsino mass parameter is expected to be around the electroweak scale. In this work, we explore the potential of probing the nearly degenerate light Higgsinos with machine learning at the LHC. By analyzing jet images and other jet substructure information, we use the convolutional neural network to enhance the signal significance. We find that our deep learning jet image method can improve the previous result based on the conventional cut flow by about a factor of 2 at the High-Luminosity LHC.

• Received 15 April 2022
• Accepted 9 August 2022

DOI:https://doi.org/10.1103/PhysRevD.106.055008

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Funded by SCOAP³.

Published by the American Physical Society