Related papers: The Matrix Element Method as a tool for precision …
We illustrate how the Matrix Element Method at Next-to-Leading Order (MEM@NLO) can be used to discriminate between events arising from the production of a Higgs boson, which subsequently decays to a final state consisting of…
One of the key tasks of any particle collider is measurement. In practice, this is often done by fitting data to a simulation, which depends on many parameters. Sometimes, when the effects of varying different parameters are highly…
We apply the Matrix Element Method (MEM) to mass determination of squark pair production with direct decay to quarks and LSP at the LHC, showing that simultaneous mass determination of squarks and LSP is possible. We furthermore propose…
The Matrix Element Method (MEM) is a powerful method to extract information from measured events at collider experiments. Compared to multivariate techniques built on large sets of experimental data, the MEM does not rely on an…
The search for the Higgs boson and for physics beyond the Standard Model are the major motivations behind the LHC experiment. In many scenarios the success of the experiment depends on the knowledge of signal and background event rates at…
We present a method that allows enabling Matrix Element Corrections (MECs) in Pythia8 with MC@NLO matching, without incurring double counting. MECs are an interesting feature that may contribute to the accuracy of theoretical predictions,…
After the recent discovery of a Standard Model Higgs boson-like particle at the LHC, the question of its couplings to known and unknown matter is eminent. In this letter, we present a method that allows for an enhancement in…
A finite element methodology for large classes of variational boundary value problems is defined which involves discretizing two linear operators: (1) the differential operator defining the spatial boundary value problem; and (2) a Riesz…
We study the prospects of measuring the CKM matrix element $\vert V_{ts}\vert$ at the LHC with the top quarks produced in the processes $p p \to t\bar{t}X$ and $p p \to t/\bar{t} X$, and the subsequent decays $t \to W^+s$ and $\bar{t} \to…
The merging of matrix elements and parton showers is an established calculational tool for the description of multi-jet final states at hadron colliders. These methods have recently been promoted to next-to-leading order accuracy in the…
The finite element method has become a preeminent simulation technique in electromagnetics. For problems involving anisotropic media and metamaterials, proper algorithms should be developed. It has been proved that discretizing in quadratic…
The Feynman--Hellmann approach to computing matrix elements in lattice QCD by first adding a perturbing operator to the action is described using the transition matrix and the Dyson expansion formalism. This perturbs the energies in the…
A precision measurement of the top quark mass m_t is obtained using a sample of ttbar events from ppbar collisions at the Fermilab Tevatron with the CDF II detector. Selected events require an electron or muon, large missing transverse…
The prevalence of null results in searches for new physics at the LHC motivates the effort to make these searches as model-independent as possible. We describe procedures for adapting the Matrix Element Method for situations where the…
We report a measurement of the top quark mass, m_t, obtained from ppbar collisions at sqrt(s) = 1.96 TeV at the Fermilab Tevatron using the CDF II detector. We analyze a sample corresponding to an integrated luminosity of 1.9 fb^-1. We…
This article surveys the procedures used for deriving detector transfer functions and normalizing probability densities for the statistical analysis technique known as the "matrix element method" in the context of high energy physics (HEP)…
Finite mixtures of matrix normal distributions are a powerful tool for classifying three-way data in unsupervised problems. The distribution of each component is assumed to be a matrix variate normal density. The mixture model can be…
In the construction of low-rank matrix approximation and maximum element search it is effective to use maxvol algorithm. Nevertheless, even in the case of rank 1 approximation the algorithm does not always converge to the maximum matrix…
Estimating parameters of mixture model has wide applications ranging from classification problems to estimating of complex distributions. Most of the current literature on estimating the parameters of the mixture densities are based on…
In this work, we propose a new randomized algorithm for computing a low-rank approximation to a given matrix. Taking an approach different from existing literature, our method first involves a specific biased sampling, with an element being…