One-loop amplitudes for W+3 jet production in hadron collisions

We employ the recently developed method of generalized $D$-dimensional unitarity to compute one-loop virtual corrections to all scattering amplitudes relevant for the production of a $W$ 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