3,872 research outputs found
A multivariate approach to heavy flavour tagging with cascade training
This paper compares the performance of artificial neural networks and boosted
decision trees, with and without cascade training, for tagging b-jets in a
collider experiment. It is shown, using a Monte Carlo simulation of events, that for a b-tagging efficiency of 50%, the light jet
rejection power given by boosted decision trees without cascade training is
about 55% higher than that given by artificial neural networks. The cascade
training technique can improve the performance of boosted decision trees and
artificial neural networks at this b-tagging efficiency level by about 35% and
80% respectively. We conclude that the cascade trained boosted decision trees
method is the most promising technique for tagging heavy flavours at collider
experiments.Comment: 14 pages, 12 figures, revised versio
W-jet Tagging: Optimizing the Identification of Boosted Hadronically-Decaying W Bosons
A method is proposed for distinguishing highly boosted hadronically decaying
W's (W-jets) from QCD-jets using jet substructure. Previous methods, such as
the filtering/mass-drop method, can give a factor of ~2 improvement in
S/sqrt(B) for jet pT > 200 GeV. In contrast, a multivariate approach including
new discriminants such as R-cores, which characterize the shape of the W-jet,
subjet planar flow, and grooming-sensitivities is shown to provide a much
larger factor of ~5 improvement in S/sqrt(B). For longitudinally polarized W's,
such as those coming from many new physics models, the discrimination is even
better. Comparing different Monte Carlo simulations, we observe a sensitivity
of some variables to the underlying event; however, even with a conservative
estimates, the multivariate approach is very powerful. Applications to
semileptonic WW resonance searches and all-hadronic W+jet searches at the LHC
are also discussed. Code implementing our W-jet tagging algorithm is publicly
available at http://jets.physics.harvard.edu/wtagComment: Version to appear in PR
Three-dimensional track reconstruction for directional Dark Matter detection
Directional detection of Dark Matter is a promising search strategy. However,
to perform such detection, a given set of parameters has to be retrieved from
the recoiling tracks : direction, sense and position in the detector volume. In
order to optimize the track reconstruction and to fully exploit the data of
forthcoming directional detectors, we present a likelihood method dedicated to
3D track reconstruction. This new analysis method is applied to the MIMAC
detector. It requires a full simulation of track measurements in order to
compare real tracks to simulated ones. We conclude that a good spatial
resolution can be achieved, i.e. sub-mm in the anode plane and cm along the
drift axis. This opens the possibility to perform a fiducialization of
directional detectors. The angular resolution is shown to range between
20 to 80, depending on the recoil energy, which is however
enough to achieve a high significance discovery of Dark Matter. On the
contrary, we show that sense recognition capability of directional detectors
depends strongly on the recoil energy and the drift distance, with small
efficiency values (50%-70%). We suggest not to consider this information either
for exclusion or discovery of Dark Matter for recoils below 100 keV and then to
focus on axial directional data.Comment: 27 pages, 20 figure
Multivariate discrimination and the Higgs + W/Z search
A systematic method for optimizing multivariate discriminants is developed
and applied to the important example of a light Higgs boson search at the
Tevatron and the LHC. The Significance Improvement Characteristic (SIC),
defined as the signal efficiency of a cut or multivariate discriminant divided
by the square root of the background efficiency, is shown to be an extremely
powerful visualization tool. SIC curves demonstrate numerical instabilities in
the multivariate discriminants, show convergence as the number of variables is
increased, and display the sensitivity to the optimal cut values. For our
application, we concentrate on Higgs boson production in association with a W
or Z boson with H -> bb and compare to the irreducible standard model
background, Z/W + bb. We explore thousands of experimentally motivated,
physically motivated, and unmotivated single variable discriminants. Along with
the standard kinematic variables, a number of new ones, such as twist, are
described which should have applicability to many processes. We find that some
single variables, such as the pull angle, are weak discriminants, but when
combined with others they provide important marginal improvement. We also find
that multiple Higgs boson-candidate mass measures, such as from mild and
aggressively trimmed jets, when combined may provide additional discriminating
power. Comparing the significance improvement from our variables to those used
in recent CDF and DZero searches, we find that a 10-20% improvement in
significance against Z/W + bb is possible. Our analysis also suggests that the
H + W/Z channel with H -> bb is also viable at the LHC, without requiring a
hard cut on the W/Z transverse momentum.Comment: 41 pages, 5 tables, 29 figure
Electron-hadron shower discrimination in a liquid argon time projection chamber
By exploiting structural differences between electromagnetic and hadronic showers in a multivariate analysis we present an efficient Electron-Hadron discrimination algorithm for liquid argon time projection chambers, validated using Geant4 simulated data
A new analysis strategy for detection of faint gamma-ray sources with Imaging Atmospheric Cherenkov Telescopes
A new background rejection strategy for gamma-ray astrophysics with
stereoscopic Imaging Atmospheric Cherenkov Telescopes (IACT), based on Monte
Carlo (MC) simulations and real background data from the H.E.S.S. [High Energy
Stereoscopic System, see [1].] experiment, is described. The analysis is based
on a multivariate combination of both previously-known and newly-derived
discriminant variables using the physical shower properties, as well as its
multiple images, for a total of eight variables. Two of these new variables are
defined thanks to a new energy evaluation procedure, which is also presented
here. The method allows an enhanced sensitivity with the current generation of
ground-based Cherenkov telescopes to be achieved, and at the same time its main
features of rapidity and flexibility allow an easy generalization to any type
of IACT. The robustness against Night Sky Background (NSB) variations of this
approach is tested with MC simulated events. The overall consistency of the
analysis chain has been checked by comparison of the real gamma-ray signal
obtained from H.E.S.S. observations with MC simulations and through
reconstruction of known source spectra. Finally, the performance has been
evaluated by application to faint H.E.S.S. sources. The gain in sensitivity as
compared to the best standard Hillas analysis ranges approximately from 1.2 to
1.8 depending on the source characteristics, which corresponds to an economy in
observation time of a factor 1.4 to 3.2.Comment: 26 pages, 13 figure
Single Top production at CMS
A first measurement of the cross section of single top quark production in
the t channel in pp collision at sqrt(s)=7 TeV is presented. The measurement is
performed on a data sample corresponding to an integrated luminosity of 35.9
pb^-1 recorded at the LHC with the CMS detector. Leptonic decay channels with
an electron or a muon in the final state are considered. After a selection
optimized for the t-channel mode, two different and complementary analyses have
been performed. Both analyses confirm the Tevatron's observation of single top,
and their combination measures a cross section of sigma = 83.6 +/-
29.8(stat.+syst.) +/- 3.3 (lumi.) pb, which is consistent with the Standard
Model prediction.Comment: 7 pages, 3 figures, Proceedings of the DPF-2011 Conference,
Providence, RI, August 8-13, 201
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