571 research outputs found
One-loop amplitudes for W+3 jet production in hadron collisions
We employ the recently developed method of generalized -dimensional
unitarity to compute one-loop virtual corrections to all scattering amplitudes
relevant for the production of a boson in association with three jets in
hadronic collisions, treating all quarks as massless.Comment: 26 pages, 5 figures, v2 to agree with published versio
The t-tbar cross-section at 1.8 and 1.96 TeV: a study of the systematics due to parton densities and scale dependence
We update the theoretical predictions for the t-tbar production cross-section
at the Tevatron, taking into account the most recent determinations of
systematic uncertainties in the extraction of the proton parton densities.Comment: 12 pages, 1 figure, Late
Jet Investigations Using the Radial Moment
We define the radial moment, , for jets produced in hadron-hadron
collisions. It can be used as a tool for studying, as a function of the jet
transverse energy and pseudorapidity, radiation within the jet and the quality
of a perturbative description of the jet shape. We also discuss how
non-perturbative corrections to the jet transverse energy affect .Comment: 14 pages, LaTeX, 6 figure
The Vincia Parton Shower
We summarize recent developments in the VINCIA parton shower. After a brief
review of the basics of the formalism, the extension of VINCIA to hadron
collisions is sketched. We then turn to improvements of the efficiency of
tree-level matching by making the shower history unique and by incorporating
identified helicities. We conclude with an overview of matching to one-loop
matrix elements.Comment: 6 pages, to appear in the proceedings of DIS 201
Stability of NLO Global Analysis and Implications for Hadron Collider Physics
The phenomenology of Standard Model and New Physics at hadron colliders
depends critically on results from global QCD analysis for parton distribution
functions (PDFs). The accuracy of the standard next-to-leading-order (NLO)
global analysis, nominally a few percent, is generally well matched to the
expected experimental precision. However, serious questions have been raised
recently about the stability of the NLO analysis with respect to certain
inputs, including the choice of kinematic cuts on the data sets and the
parametrization of the gluon distribution. In this paper, we investigate this
stability issue systematically within the CTEQ framework. We find that both the
PDFs and their physical predictions are stable, well within the few percent
level. Further, we have applied the Lagrange Multiplier method to explore the
stability of the predicted cross sections for W production at the Tevatron and
the LHC, since W production is often proposed as a standard candle for these
colliders. We find the NLO predictions on sigma_W to be stable well within
their previously-estimated uncertainty ranges.Comment: 24 pages, 11 figures. Minor changes in response to JHEP referee
repor
Neural Network Parametrization of Deep-Inelastic Structure Functions
We construct a parametrization of deep-inelastic structure functions which
retains information on experimental errors and correlations, and which does not
introduce any theoretical bias while interpolating between existing data
points. We generate a Monte Carlo sample of pseudo-data configurations and we
train an ensemble of neural networks on them. This effectively provides us with
a probability measure in the space of structure functions, within the whole
kinematic region where data are available. This measure can then be used to
determine the value of the structure function, its error, point-to-point
correlations and generally the value and uncertainty of any function of the
structure function itself. We apply this technique to the determination of the
structure function F_2 of the proton and deuteron, and a precision
determination of the isotriplet combination F_2[p-d]. We discuss in detail
these results, check their stability and accuracy, and make them available in
various formats for applications.Comment: Latex, 43 pages, 22 figures. (v2) Final version, published in JHEP;
Sect.5.2 and Fig.9 improved, a few typos corrected and other minor
improvements. (v3) Some inconsequential typos in Tab.1 and Tab 5 corrected.
Neural parametrization available at http://sophia.ecm.ub.es/f2neura
Implications of Hadron Collider Observables on Parton Distribution Function Uncertainties
Standard parton distribution function sets do not have rigorously quantified
uncertainties. In recent years it has become apparent that these uncertainties
play an important role in the interpretation of hadron collider data. In this
paper, using the framework of statistical inference, we illustrate a technique
that can be used to efficiently propagate the uncertainties to new observables,
assess the compatibility of new data with an initial fit, and, in case the
compatibility is good, include the new data in the fit.Comment: 22 pages, 5 figure
Jet photoproduction and the structure of the photon
Various jet observables in photoproduction are studied and compared to data
from HERA. The feasibility of using a dijet sample for constraining the parton
distributions in the photon is then studied. For the current data the
experimental and theoretical uncertainties are comparable to the variation due
to changing the photon parton distribution set.Comment: 20 pages including 11 figures. Latex using revtex and psfig macros.
Several references added. Submitted to Phys. Rev.
Multi-gluon one-loop amplitudes using tensor integrals
An efficient numerical algorithm to evaluate one-loop amplitudes using tensor
integrals is presented. In particular, it is shown by explicit calculations
that for ordered QCD amplitudes with a number of external legs up to 10, its
performance is competitive with other methods.Comment: 25 pages, results for quark loops added, accuracy analysis extended,
mistakes corrected, reference adde
Multivariate Fitting and the Error Matrix in Global Analysis of Data
When a large body of data from diverse experiments is analyzed using a
theoretical model with many parameters, the standard error matrix method and
the general tools for evaluating errors may become inadequate. We present an
iterative method that significantly improves the reliability of the error
matrix calculation. To obtain even better estimates of the uncertainties on
predictions of physical observables, we also present a Lagrange multiplier
method that explores the entire parameter space and avoids the linear
approximations assumed in conventional error propagation calculations. These
methods are illustrated by an example from the global analysis of parton
distribution functions.Comment: 13 pages, 5 figures, Latex; minor clarifications, fortran program
made available; Normalization of Hessian matrix changed to HEP standar
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