相关论文: Signal mixture estimation for degenerate heavy Hig…
We consider, in the context of the Large Hadron Collider, the signals of the Type-X two Higgs doublet model (2HDM) in the parameter region answering to the best possible solution to the muon $(g-2)$ data within this framework. The analysis…
For large masses, the two heavy neutral Higgs bosons are nearly degenerate in many 2--Higgs doublet models, and particularly in supersymmetric models. In such a scenario the mixing between the states can be very large if the theory is…
We apply deep learning techniques to the late-time turbulent regime in a post-inflationary model where a real scalar inflaton field and the standard model Higgs doublet interact with renormalizable couplings between them. After inflation,…
Particle identification is one of the core tasks in the data analysis pipeline at the Large Hadron Collider (LHC). Statistically, this entails the identification of rare signal events buried in immense backgrounds that mimic the properties…
The space-based gravitational wave detector LISA will observe mergers of massive black hole binary systems (MBHBs) to cosmological distances, as well as inspiralling stellar-origin (or stellar-mass) binaries (SBHBs) years before they enter…
We study lepton-flavor-violating (LFV) decays of a heavy Higgs boson, $H \to \mu\tau$, in the Type-III two-Higgs-doublet model by recasting the CMS search at $\sqrt{s} = 13$ TeV with 35.9 fb$^{-1}$ using fast detector simulation in the mass…
Deep Neural Networks (DNN) have been successful in en- hancing noisy speech signals. Enhancement is achieved by learning a nonlinear mapping function from the features of the corrupted speech signal to that of the reference clean speech…
A broad class of models in which electroweak symmetry breaking originates from dynamics in a singlet dark sector, and is transferred to the Standard Model via the Higgs portal, predicts in general strongly suppressed Higgs boson mixing with…
Testing the properties of the Higgs particle discovered at the LHC and searching for new physics signals, are some of the most important tasks of Particle Physics today. Current measurements of the Higgs couplings to fermions and gauge…
The scenario of two mass-degenerate Higgs bosons within the general two-Higgs-doublet model (2HDM) is revisited. We focus on the global picture when two $CP$-even Higgs bosons of $h$ and $H$ are nearly mass-degenerate. A global fit to the…
We study the LHC search prospects for a model in which the neutrinos obtain Dirac masses from couplings to a second Higgs doublet with tiny vacuum expectation value. The model contains a charged Higgs boson that decays to l nu with…
The analysis of the Higgs boson data by the ATLAS and CMS Collaborations appears to exhibit an excess of h --> gamma\gamma events above the Standard Model (SM) expectations; whereas no significant excess is observed in h --> ZZ* --> {four…
Estimating heterogeneous treatment effect is an important task in causal inference with wide application fields. It has also attracted increasing attention from machine learning community in recent years. In this work, we reinterpret the…
This paper presents a deep learning-based estimation of the intensity component of MultiSpectral bands by considering joint multiplication of the neighbouring spectral bands. This estimation is conducted as part of the component…
In this paper, we study an application of deep learning to the advanced LIGO and advanced Virgo coincident detection of gravitational waves (GWs) from compact binary star mergers. This deep learning method is an extension of the Deep…
The shape of the Higgs potential is modified by the presence of additional scalar fields, as predicted in many Beyond-Standard-Model (BSM) scenarios. In such cases, deviations in the Higgs self-interactions, in particular the trilinear…
Autonomous synthesis and characterization of inorganic materials requires the automatic and accurate analysis of X-ray diffraction spectra. For this task, we designed a probabilistic deep learning algorithm to identify complex multi-phase…
We study deep neural networks for classification of images with quality distortions. We first show that networks fine-tuned on distorted data greatly outperform the original networks when tested on distorted data. However, fine-tuned…
We predict an unconventional background free signal of the Higgs boson in $R$-parity violating nonminimal supersymmetric models at the Large Hadron Collider (LHC). The signal comprises dilepton plus four hadronic jets and two large…
We demonstrate how the transverse tau tau spin correlations can be used to determine whether a decaying Higgs boson is a mixed CP eigenstate, thereby directly probe the presence of CP violation in the neutral Higgs boson sector. We…