Related papers: Signal mixture estimation for degenerate heavy Hig…
Extensions beyond the Standard Model allow for a gauge singlet scalar to be kinetically coupled with the Higgs. We consider kinetic mixing between a Dark scalar gauge singlet \emph{nearly degenerate} with the Higgs, focusing on the…
Mixup~\cite{zhang2017mixup} is a recently proposed method for training deep neural networks where additional samples are generated during training by convexly combining random pairs of images and their associated labels. While simple to…
Neutrinos, dark matter, and long-lived neutral particles traverse the particle detectors unnoticed, carrying away information about their parent particles and interaction sources needed to reconstruct key variables like resonance peaks in…
In the 2030s, a new era of gravitational-wave (GW) observations will dawn as multiple space-based GW detectors, such as the Laser Interferometer Space Antenna, Taiji and TianQin, open the millihertz window for GW astronomy. These detectors…
We present a new method to approximate posterior probabilities of Bayesian Network using Deep Neural Network. Experiment results on several public Bayesian Network datasets shows that Deep Neural Network is capable of learning joint…
We show that neural network classifiers can be helpful to discriminate Higgs production from background at LHC in the Higgs mass range M= 200 GeV. We employ a common feed-forward neural network trained by the backpropagation algorithm for…
Deep learning models frequently make incorrect predictions with high confidence when presented with test examples that are not well represented in their training dataset. We propose a novel and straightforward approach to estimate…
A prospective analysis for the search of the Standard Model (SM) Higgs boson with the CMS detector is presented in the context of the early LHC data. The aim is to establish an analysis strategy for inclusive production of the Higgs boson…
In scenarios of strongly coupled electroweak symmetry breaking, heavy composite particles of different spin and parity may arise and cause observable effects on signals that appear at loop levels. The recently observed process of Higgs to…
The signal strength of the recently discovered Higgs boson-like particle in the diphoton channel seemingly constrains physics beyond the standard model to a severe degree. However, the reported signal strength is prone to possible…
The LHC has been built to understand the dynamics at the origin of the breaking of the electroweak symmetry. Weakly coupled models with a fundamental Higgs boson have focused most of the attention of the experimental searches. We will…
The Standard Model Higgs suffers from the hierarchy problem, typically implying new states within the reach of the LHC. If the Higgs is very heavy (~500 GeV) the states that cutoff the quadratic divergence may be beyond the reach of the…
A search for a standard model Higgs boson produced in association with a top-quark pair and decaying to bottom quarks is presented. Events with hadronic jets and one or two oppositely charged leptons are selected from a data sample…
In the framework of strongly interacting dynamics for electroweak symmetry breaking, heavy composite particles may arise and cause observable effects, as they should couple strongly to the resulting Higgs boson and affect the signals that…
Using the most recent results of CMS and ATLAS, we study the Higgs decays to $\gamma\gamma$ and $Z\gamma$ in the scenario where the two CP even Higgs predicted by the type II seesaw model (HTM) are close to mass degenerate with a mass near…
We investigate the determination of Higgs boson couplings to gauge bosons and fermions at the LHC from data on Higgs boson production and decay. We demonstrate that very mild theoretical assumptions, which are valid in general multi-Higgs…
Although deep learning has yielded impressive performance for face recognition, many studies have shown that different networks learn different feature maps: while some networks are more receptive to pose and illumination others appear to…
We show how LHC Higgs boson production and decay data can be used to extract the gauge and fermion couplings of the Higgs boson. Incomplete input data leads to parameter degeneracies, which can be lifted by imposing theoretical assumptions.…
We introduce deep learning time-series forecasting for gravitational wave detection of binary neutron star mergers. This method enables the identification of these signals in real advanced LIGO data up to 30 seconds before merger. When…
Environmental sensing can significantly enhance mmWave communications by assisting beam training, yet its benefits must be balanced against the associated sensing costs. To this end, we propose a unified machine learning framework that…