相关论文: Neural Networks for Analysis of Top Quark Producti…
The reconstruction of top-quark pair-production ($t\bar{t}$) events is a prerequisite for many top-quark measurements. We use a deep neural network, trained with Monte-Carlo simulated events, to reconstruct $t\bar{t}$ decays in the…
We show that Neural Nets can be useful for top analysis at Tevatron. The main features of $t\bar t$ and background events on a mixed sample are projected in a single output, which controls the efficiency and purity of the $t\bar t$ signal.
We report on measurements of the ttbar production cross section at a center-of-mass energy of 1.96 TeV at the D0 experiment during Run II of the Fermilab Tevatron collider. We use candidate events in lepton+jets and dilepton final states.…
A simpler neural-network approach is presented for the analysis of the top quark non-leptonic decay channel in events of the D0 Collaboration. Results for the top quark signal are comparable to those found by the D0 Collaboration by a more…
The application of Neural Networks in High Energy Physics to the separation of signal from background events is studied. A variety of problems usually encountered in this sort of analyses, from variable selection to systematic errors, are…
The top quark plays an important role in the grand scheme of particle physics, and is also interesting on its own merits. We present recent results from CDF on top-quark physics based on 100-200/pb of p-pbar collision data. We have measured…
We describe three recent results from D0 related to the top quark: a preliminary measurement of the t-tbar spin correlation in top quark pair production, a search for top quark decays into charged Higgs bosons, and an improved cross section…
A precise measurement of the top quark mass, a fundamental parameter of the Standard Model, is among the most important goals of top quark studies at the Large Hadron Collider. Apart from the standard methods, numerous new observables and…
We present a search for electroweak production of single top quarks in the s-channel (p-pbar -> t bbar + X) and t-channel (p-pbar -> tq bbar + X) modes. We have analyzed 230 pb^(-1) of data collected with the D0 detector at the Fermilab…
In the top quark pair production in association with the Higgs boson decaying to a b quark pair t-tbar H (b-bbar), the final state has an irreducible nonresonant background from the production of a top quark pair in association with a b…
In differential measurements of the $t\bar{t}b\bar{b}$ process, observables related to the b jets not originating from top quark decays are of special interest to probe the multi-scale QCD nature of the $t\bar{t}b\bar{b}$ process, and the…
Tensor networks (TNs) and neural networks (NNs) are two fundamental data modeling approaches. TNs were introduced to solve the curse of dimensionality in large-scale tensors by converting an exponential number of dimensions to polynomial…
We study the impact of different theoretical descriptions of top quark pair production on top quark mass measurements in the di-lepton channel. To this aim, the full NLO corrections to $pp\rightarrow W^+W^-b\bar b\rightarrow (e^+…
The use of machine learning methods to tackle challenging physical layer signal processing tasks has attracted significant attention. In this work, we focus on the use of neural networks (NNs) to perform pilot-assisted channel estimation in…
Recent results on top quark physics with the D0 experiment in pbar-p collisions at sqrt(s) = 1.8 TeV for an integrated luminosity of 125 pb**-1 are reported. The direct measurement of the top quark mass uses single lepton and dilepton…
The use of neural networks for signal vs.~background discrimination in high-energy physics experiment has been investigated and has compared favorably with the efficiency of traditional kinematic cuts. Recent work in top quark…
In this proceedings we briefly report on the state-of-the-art NLO QCD computation for the $pp\to t\bar{t}\gamma$ process in the di-lepton channel. We describe higher-order corrections to the $e^+\nu_e \, \mu^- \bar{\nu}_\mu \,…
An overview of top quark production measurements using the ATLAS detector at the LHC is presented. Using 35 pb^-1 of data, we measured the ttbar cross-section in the lepton+jets channel to 13% precision and set limits on the cross-section…
Deep neural networks have rightfully won the place of one of the most accurate analysis tools in high energy physics. In this paper we will cover several methods of improving the performance of a deep neural network in a classification task…
The top quark antiquark production system in the dilepton decay channel is described by a set of equations which is nonlinear in the unknown neutrino momenta. Its most precise and least time consuming solution is of major importance for…