82 citations · 493 across the 25 of their papers we have counts for
26 papers
Strengthening Anomaly Awareness
Adam Banda, Charanjit K. Khosa, Veronica Sanz
We present a refined version of the Anomaly Awareness framework for enhancing unsupervised anomaly detection. Our approach introduces minimal supervision into Variational Autoencod…
A simple guide from Machine Learning outputs to statistical criteria
Charanjit K. Khosa, Veronica Sanz, Michael Soughton
In this paper we propose ways to incorporate Machine Learning training outputs into a study of statistical significance. We describe these methods in supervised classification task…
Identification of b-jets using QCD-inspired observables
Oleh Fedkevych, Charanjit K. Khosa, Simone Marzani +1
We study the issue of separating hadronic jets that contain bottom quarks (-jets) from jets featuring light partons only. We develop a novel approach to -tagging that exploit…
Tagging the Higgs boson decay to bottom quarks with colour-sensitive observables and the Lund jet plane
Luca Cavallini, Andrea Coccaro, Charanjit K. Khosa +6
We study the problem of distinguishing -jets stemming from the decay of a colour singlet, such as the Higgs boson, from those originating from the abundant QCD background. In pa…
Constraining new physics with SModelS version 2
Gaël Alguero, Jan Heisig, Charanjit Khosa +6
We present version 2 of SModelS, a program package for the fast reinterpretation of LHC searches for new physics on the basis of simplified model results. The major novelty of the…
Lund jet plane for Higgs tagging
Charanjit K. Khosa
We study the boosted Higgs tagging using the Lund jet plane. The convolutional neural network is used for the Lund images data set to classify hadronically decaying Higgs from the…
Higgs boson tagging with the Lund jet plane
Charanjit K. Khosa, Simone Marzani
We construct a procedure to separate boosted Higgs bosons decaying into hadrons, from the background due to strong interactions. We employ the Lund jet plane to obtain a theoretica…
On the impact of the LHC Run2 data on general Composite Higgs scenarios
Charanjit K. Khosa, Veronica Sanz
We study the the impact of Run2 LHC data on general Composite Higgs scenarios, where non-linear effects, mixing with additional scalars and new fermionic degrees of freedom could s…
The LHC Olympics 2020: A Community Challenge for Anomaly Detection in High Energy Physics
Gregor Kasieczka, Benjamin Nachman, David Shih +44
A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. I…
New developments in SModelS
Gaël Alguero, Jan Heisig, Charanjit K. Khosa +7
SModelS is an automatized tool enabling the fast interpretation of simplified model results from the LHC within any model of new physics respecting a symmetry. In th…
Anomaly Awareness
Charanjit K. Khosa, Veronica Sanz
We present a new algorithm for anomaly detection called Anomaly Awareness. The algorithm learns about normal events while being made aware of the anomalies through a modification o…
SModelS database update v1.2.3
Charanjit K. Khosa, Sabine Kraml, Andre Lessa +2
We present an update of the SModelS database with simplified model results from 13 ATLAS and 10 CMS searches for supersymmetry at Run 2. This includes 5 ATLAS and 1 CMS analyses fo…
Reinterpretation of LHC Results for New Physics: Status and Recommendations after Run 2
Waleed Abdallah, Shehu AbdusSalam, Azar Ahmadov +139
We report on the status of efforts to improve the reinterpretation of searches and measurements at the LHC in terms of models for new physics, in the context of the LHC Reinterpret…
Convolutional Neural Networks for Direct Detection of Dark Matter
Charanjit K. Khosa, Lucy Mars, Joel Richards +1
The XENON1T experiment uses a time projection chamber (TPC) with liquid Xenon to search for Weakly Interacting Massive Particles (WIMPs), a proposed Dark Matter particle, via direc…
Using Machine Learning to disentangle LHC signatures of Dark Matter candidates
C. K. Khosa, V. Sanz, M. Soughton
We study the prospects of characterising Dark Matter at colliders using Machine Learning (ML) techniques. We focus on the monojet and missing transverse energy (MET) channel and pr…
Exploring SMEFT in VH with Machine Learning
Felipe F. Freitas, Charanjit K. Khosa, Verónica Sanz
In this paper we study the use of Machine Learning techniques to exploit kinematic information in VH, the production of a Higgs in association with a massive vector boson. We param…
Boosted Top quark polarization
Rohini Godbole, Monoranjan Guchait, Charanjit K. Khosa +3
In top quark production, the polarization of top quarks, decided by the chiral structure of couplings, is likely to be modified in the presence of any new physics contribution to t…
Probing CP nature of a mediator in associated production of dark matter with single top quark
Genevieve Belanger, Rohini M. Godbole, Charanjit K. Khosa +1
We consider associated production of dark matter with single top quark, in a simplified dark matter model with spin-0 mediators. The produced top quark is polarized and the polariz…
Predicting , and fermion mass ratios from flavour GUTs with CSD2
Stefan Antusch, Christian Hohl, Charanjit K. Khosa +1
Constrained Sequential neutrino Dominance of type 2 (referred to as CSD2) is an attractive building block for flavour Grand Unified Theories (GUTs) because it predicts a non-zero l…
Measuring the trilinear neutral Higgs boson couplings in the MSSM at colliders
Charanjit K. Khosa, P. N. Pandita
We consider the measurement of the trilinear couplings of the neutral Higgs bosons~() in the minimal supersymmetric standard model~(MSSM) at a high energy lin…
Higgs mass from neutrino-messenger mixing
Pritibhajan Byakti, Charanjit K Khosa, V. S. Mummidi +1
The discovery of the Higgs particle at 125 GeV has put strong constraints on minimal messenger models of gauge mediation, pushing the stop masses into the multi-TeV regime. Extensi…
Measuring the trilinear neutral Higgs boson couplings in the minimal supersymmetric standard model at colliders in the light of the discovery of a Higgs boson
Charanjit K. Khosa, P. N. Pandita
We consider the measurement of the trilinear couplings of the neutral Higgs bosons in the Minimal Supersymmetric Standard Model~(MSSM) at a high energy linear collider in…
Alternative search strategies for a BSM resonance fitting ATLAS diboson excess
Biplob Bhattacherjee, Pritibhajan Byakti, Charanjit K. Khosa +2
We study an s-channel resonance as a viable candidate to fit the diboson excess reported by ATLAS. We compute the contribution of the TeV resonance to semileptonic…
NMSGUT emergence and Trans-Unification RG flows
Charanjit S. Aulakh, Ila Garg, Charanjit K. Khosa
Consistency of trans-unification RG evolution is used to discuss the domain of definition of the New Minimal Supersymmetric SO(10) GUT (NMSGUT). We compute the 1-loop RGE funct…