相关论文: Probing Higgs exotic decay at the LHC with machine…
At the CERN Large Hadron Collider experiment, the non-resonant double Higgs production via vector-boson fusion represents a unique mean to probe the VVHH (V=Z, W$^{\pm}$) Higgs self-coupling at the current center of mass energies. Such a…
Deep neural networks (DNNs) are efficient solvers for ill-posed problems and have been shown to outperform classical optimization techniques in several computational imaging problems. DNNs are trained by solving an optimization problem…
We conduct a detailed exploration of charged Higgs boson masses $M_{H^{\pm}}$ within the range of $100-190~GeV$. This investigation is grounded in the benchmark points that comply with experimental constraints, allowing us to systematically…
At the High Luminosity LHC, selecting important physics processes such as (di-) Higgs production will be a high priority. The Phase-2 Upgrade of the CMS Level-1 Trigger will reconstruct particle candidates and use pileup mitigation for the…
The possibility of searching for the Higgs boson in channels with multiple non-resonant leptons is evaluated in light of recent advances in multi-lepton search techniques at the LHC. The total multi-lepton Higgs signal exceeds the four…
Neural Networks (NN), although successfully applied to several Artificial Intelligence tasks, are often unnecessarily over-parametrised. In edge/fog computing, this might make their training prohibitive on resource-constrained devices,…
We apply gradient boosting machine learning techniques to the problem of hadronic jet substructure recognition using classical subjettiness variables available within a common parameterized detector simulation package DELPHES. Per-jet…
A galaxy's morphological features encode details about its gas content, star formation history, and feedback processes, which play important roles in regulating its growth and evolution. We use deep convolutional neural networks (CNNs) to…
We investigate the possibility to detect the scalar Higgs boson decay $H\to b\bar b$ in the associated $Z$ and $b\bar b$ production at the LHC using the $k_T$-factorization QCD approach. Our consideration is based on the off-shell (i.e.…
We investigate the signature of a heavy charged Higgs boson of the Minimal Supersymmetric Standard Model in the lepton plus multi-jet channel at the Large Hadron Collider with four $b$-tags. The signal is the gluon-gluon fusion process…
We investigate di-Higgs production in the $b\bar{b}\gamma\gamma$ final state at the LHC, focusing on scenarios where the gluon fusion process is enhanced by new colored scalars, which could be identified as squarks or leptoquarks. We…
We study the indirect effects of New Physics in the Higgs decay into four charged leptons, using an Effective Field Theory (EFT) approach to Higgs interactions. We evaluate the deviations induced by the EFT dimension-six operators in…
Jet tagging is a classification problem in high-energy physics experiments that aims to identify the collimated sprays of subatomic particles, jets, from particle collisions and tag them to their emitter particle. Advances in jet tagging…
Jet identification is one of the fields in high energy physics that machine learning has begun to make an impact. More often than not, convolutional neural networks are used to classify jet images with the benefit that essentially no…
Jet production from hadronic Higgs decays at future lepton colliders will have significantly different phenomenological implications than jet production via off-shell photon and $Z$-boson decays, owing to the fact that Higgs bosons decay to…
The application of machine learning (ML) in high energy physics (HEP), specifically in heavy-flavor jet tagging at Large Hadron Collider (LHC) experiments, has experienced remarkable growth and innovation in the past decade. This review…
One of the cleanest signatures of a heavy Higgs boson in models with vectorlike leptons is $H\to e_4^\pm \ell^\mp \to h\ell^+\ell^-$ which, in two Higgs doublet model type-II, can even be the dominant decay mode of heavy Higgses. Among the…
A precise measurement of the Higgs boson couplings to bottom and top quarks is of paramount importance during the upcoming LHC runs. We present a comprehensive analysis for the Higgs production process in association with a…
We apply both cut-based and machine learning techniques using the same inputs to the challenge of hadronic jet substructure recognition, utilizing classical subjettiness variables within the Delphes parameterized detector simulation…
We present a systematic study of Tensor Network (TN) models $\unicode{x2013}$ Matrix Product States (MPS) and Tree Tensor Networks (TTN) $\unicode{x2013}$ for real-time jet tagging in high-energy physics, with a focus on low-latency…