BOOST 2024 - 16th International Workshop on Boosted Object Phenomenology, Reconstruction, Measurements, and Searches at Colliders

Probing the Supersymmetric Standard Model at the Large Hadron Collider through Vector Boson Fusion Processes and Machine Learning

31 Jul 2024, 09:40

20m

Palazzo Ducale (Genova, Italy)

Talk BSM BSM

Speaker

Umar Sohail Qureshi (Vanderbilt University)

Description

We present a phenomenology study probing the Supersymmetric Standard Model (SSM) at the Large Hadron Collider for a previously unexplored region of the parameter space.
In particular, we consider proton-proton collisions at $\sqrt{s}=13$ and $\sqrt{s}=14$ TeV and investigate the production of GeV-scale first and second-generation neutralinos ${\tilde{\chi }}_1^0$ and ${\tilde{\chi }}_2^0$, and first-generation charginos ${\tilde{\chi }}_1^{\pm }$. This is done by employing a novel $pp\to \text{ewkino}\text{ewkino}jj$ vector boson fusion (VBF) topology. The analysis is performed using machine learning algorithms i.e. gradient boosting and deep learning methods, over traditional methods, to maximize the signal sensitivity with integrated luminosities of of $150,300$, and $3000$ fb${}^{-1}$.
We expect that our methodology extends LHC constraints to the SSM with $\ge 5\sigma$ signal significance throughout this parameter space, traditionally considered difficult to probe due to SM backgrounds and small SSM cross sections.

Presentation materials

Final_VBF_SUSY_Poster_BOOST.pdf

VBF_SUSY_BOOST_Slides.pdf