Related papers: Symbolic Classification-Enabled LHC Limits Online …
One of the assumptions of simplified models is that there are a few new particles and interactions accessible at the LHC and all other new particles are heavy and decoupled. The effective field theory (EFT) method provides a consistent…
The absence of supersymmetry or other new physics at the Large Hadron Collider (LHC) has lead many to question naturalness arguments. With Bayesian statistics, we argue that natural models are most probable and that naturalness is not…
Previous studies have shown that the Hidden Local Symmetry (HLS) Model, supplied with appropriate symmetry breaking mechanisms, provides an Effective Lagrangian (BHLS) which encompasses a large number of processes within a unified…
This thesis presents a theoretical analysis of the properties of the Higgs bosons in the Standard Model (SM) and the minimal supersymmetric extension (MSSM), which can be investigated at the LHC and $e^+e^-$ linear colliders. The final goal…
We discuss various phenomenological aspects of supersymmetric models beyond the MSSM. A particular focus is on models which can correctly explain neutrino data and the possiblities of LHC to identify the underlying scenario.
A Hidden Markov Model (HMM) is a common statistical model which is widely used for analysis of biological sequence data and other sequential phenomena. In the present paper we show how HMMs can be extended with side-constraints and present…
The motivation for introduction of supersymmetry in high energy physics as well as a possibility for supersymmetry discovery at LHC (Large Hadronic Collider) are discussed. The main notions of the Minimal Supersymmetric Standard Model…
In this review, we discuss methods of parsing direct and indirect information from collider experiments regarding the Higgs boson and describe simple ways in which experimental likelihoods can be consistently reconstructed and interfaced…
The Next-to-Minimal Supersymmetric Standard Model (NMSSM), the singlet extension of the MSSM which fixes many of the MSSM's shortcomings, is shown to be within reach of the upcoming runs of the Large Hadron Collider (LHC). A systematic…
Provided that Supersymmetry (SUSY) is realized, the Large Hadron Collider (LHC) and the future International Linear Collider (ILC) may provide a wealth of precise data from SUSY processes. An important task will be to extract the Lagrangian…
Concept-based explanation methods, such as concept bottleneck models (CBMs), aim to improve the interpretability of machine learning models by linking their decisions to human-understandable concepts, under the critical assumption that such…
We consider machine learning techniques associated with the application of a Boosted Decision Tree (BDT) to searches at the Large Hadron Collider (LHC) for pair-produced lepton partners which decay to leptons and invisible particles. This…
After the LHC Run 1, the standard model (SM) of particle physics has been completed. Yet, despite its successes, the SM has shortcomings vis-\`{a}-vis cosmological and other observations. At the same time, while the LHC restarts for Run 2…
We discuss the potential impacts on the CMSSM of future LHC runs and possible electron-positron and higher-energy proton-proton colliders, considering searches for supersymmetry via MET events, precision electroweak physics, Higgs…
The use of the SMEFT Lagrangian to quantify possible Beyond the Standard Model (BSM) effects is standard in LHC and future collider studies. One of the usual assumptions is to truncate the expansion with the dimension-$6$ operators. The…
Fastlim is a tool to calculate conservative limits on extensions of the Standard Model from direct LHC searches without performing any Monte Carlo event generation. The program reconstructs the visible cross sections from pre-calculated…
We use the framework of the p19MSSM to perform a fit to the mild excesses over the Standard Model background recently observed in three bins of the ATLAS 1-lepton + (b-)jets + MET search. We find a few types of spectra that can fit the…
The "golden region'' in the MSSM parameter space is the region where the experimental constraints are satisfied and the amount of fine-tuning is minimized. In this region, the stop trilinear soft term is large, leading to a significant mass…
We introduce 'Class Symbolic Regression' (Class SR) a first framework for automatically finding a single analytical functional form that accurately fits multiple datasets - each realization being governed by its own (possibly) unique set of…
We perform a first global exploration of the Constrained Next-to-Minimal Supersymmetric Standard Model using Bayesian statistics. We derive several global features of the model and find that, in some contrast to initial expectations, they…