Multi-jet cross sections at NLO with BlackHat and Sherpa

In this talk, we report on a recent next-to-leading order QCD calculation of the production of a W boson in association with three jets at hadron colliders. The computation is performed by combining two programs, BlackHat for the computation of the virtual one-loop matrix elements and Sherpa for the real emission part.Comment: 4 pages, contribution to the proceedings of the XLIIIth Rencontres de Moriond (QCD

Next-to-Leading Order Jet Physics with BlackHat

We present several results obtained using the BlackHat next-to-leading order QCD program library, in conjunction with SHERPA. In particular, we present distributions for vector boson plus 1,2,3-jet production at the Tevatron and at the asymptotic running energy of the Large Hadron Collider, including new Z+3-jet distributions. The Z+2-jet predictions for the second-jet P_T distribution are compared to CDF data. We present the jet-emission probability at NLO in W+2-jet events at the LHC, where the tagging jets are taken to be the ones furthest apart in pseudorapidity. We analyze further the large left-handed W polarization, identified in our previous study, for W bosons produced at high P_T at the LHC.Comment: Presented at RADCOR 2009 - 9th International Symposium on Radiative Corrections (Applications of Quantum Field Theory to Phenomenology), October 25 - 30 2009, Ascona, Switzerland}, 12 pages, 9 figures, LaTeX, v2 updated small correction to polarization effect plo

Towards W b bbar + j at NLO with an automatized approach to one-loop computations

We present results for the O(alpha_s) virtual corrections to q g -> W b bbar q' obtained with a new automatized approach to the evaluation of one-loop amplitudes in terms of Feynman diagrams. Together with the O(alpha_s) corrections to q q' -> W b bbar g, which can be obtained from our results by crossing symmetry, this represents the bulk of the next-to-leading order virtual QCD corrections to W b bbar + j and W b + j hadronic production, calculated in a fixed-flavor scheme with four light flavors. Furthermore, these corrections represent a well defined and independent subset of the 1-loop amplitudes needed for the NNLO calculation of W b bbar. Our approach was tested against several existing results for NLO amplitudes including selected O(alpha_s) one-loop corrections to W + 3 j hadronic production. We discuss the efficiency of our method both with respect to evaluation time and numerical stability.Comment: 14 pages, 3 figure

Automation of one-loop QCD corrections

We present the complete automation of the computation of one-loop QCD corrections, including UV renormalization, to an arbitrary scattering process in the Standard Model. This is achieved by embedding the OPP integrand reduction technique, as implemented in CutTools, into the MadGraph framework. By interfacing the tool so constructed, which we dub MadLoop, with MadFKS, the fully automatic computation of any infrared-safe observable at the next-to-leading order in QCD is attained. We demonstrate the flexibility and the reach of our method by calculating the production rates for a variety of processes at the 7 TeV LHC.Comment: 64 pages, 12 figures. Corrected the value of m_Z in table 1. In table 2, corrected the values of cross sections in a.4 and a.5 (previously computed with mu=mtop/2 rather than mu=mtop/4). In table 2, corrected the values of NLO cross sections in b.3, b.6, c.3, and e.7 (the symmetry factor for a few virtual channels was incorrect). In sect. A.4.3, the labeling of the four-momenta was incorrec

b-Initiated processes at the LHC: a reappraisal

Several key processes at the LHC in the standard model and beyond that involve $b$ quarks, such as single-top, Higgs, and weak vector boson associated production, can be described in QCD either in a 4-flavor or 5-flavor scheme. In the former, $b$ quarks appear only in the final state and are typically considered massive. In 5-flavor schemes, calculations include $b$ quarks in the initial state, are simpler and allow the resummation of possibly large initial state logarithms of the type $\log \frac{{\cal Q}^2}{m_b^2}$ into the $b$ parton distribution function (PDF), ${\cal Q}$ being the typical scale of the hard process. In this work we critically reconsider the rationale for using 5-flavor improved schemes at the LHC. Our motivation stems from the observation that the effects of initial state logs are rarely very large in hadron collisions: 4-flavor computations are pertubatively well behaved and a substantial agreement between predictions in the two schemes is found. We identify two distinct reasons that explain this behaviour, i.e., the resummation of the initial state logarithms into the $b$-PDF is relevant only at large Bjorken $x$ and the possibly large ratios ${\cal Q}^2/m_b^2$'s are always accompanied by universal phase space suppression factors. Our study paves the way to using both schemes for the same process so to exploit their complementary advantages for different observables, such as employing a 5-flavor scheme to accurately predict the total cross section at NNLO and the corresponding 4-flavor computation at NLO for fully exclusive studies.Comment: Fixed typo in Eq. (A.10) and few typos in Eq. (C.2) and (C.3

Estimation of liveweight from chest circumference in double purpose crossbred calves during growth as a function of sex and racial group in the Maracaibo Lake basin

With the objective of estimating live weight (LW) as a function of racial group and sex and calculating its relationship to chest circumference (CC) in growing crossbred double purpose calves under tropical conditions, 589 measurements were taken of animals in three herds distributed in the Maracaibo Lake basin and grouped by predominant race (indicus or Taurus) and sex. General analysis of the data yielded a correlation between LW and CC (P <0.001) with R2 = 0.96. The corresponding exponential (quadratic) general regression equation was LW = 115.10 + (-2.83 × CC) + (0.03 × CC2); LW in kg and CC in cm. Sex had a highly significant effect (P<0.001) on both LW and CC, but the racial group did not. According to these results, CC is a good indicator of LW in double purpose cattle during growth. The data were used to prepare a table presenting the variations of LW and CC, which can be used on farms not possessing a weight scale to estimate LW changes in the animals

Predicción de peso de carcasa a la edad de beneficio en cuyes del genotipo Cieneguilla con base a una síntesis de medidas corporales

The objective of the present study was to predict carcass weight (PC) in guinea pigs (Cavia porcellus) at the age of slaughtering (16±2 weeks), considering their biometric measurements. The following measures and weights were taken before and after the slaughter of 150 male guinea pigs of the Cieneguilla genotype: live body weight (PV), body length (LC), head length (LCA), head width (AC), loin length (LL), loin width (AL), chest girth (PT), thigh perimeter (PM), thigh length (LM), arm perimeter (PB), arm length (LB), and rump middle square (CMG), as well as the carcass weight (PC). The data were analyzed to determine the best regression equation and to establish the best predictive linear model of carcass weight. The «Step-Wise Regression» process of the SAS statistical package was used. The combinations of independent variables in the model revealed that the variables PV, PT, AC, and LL give a better explanation of the CP at the benefit age (R2=0.71; Cp-Mallows=1.63).El objetivo del presente estudio fue predecir el peso de carcasa (PC) en cuyes (Cavia porcellus) a la edad de beneficio (16 ± 2 semanas), tomando como referencia sus medidas biométricas. Se tomaron las siguientes medidas y pesos antes y después del beneficio a 150 cuyes machos del genotipo Cieneguilla: peso vivo al beneficio (PV), largo de cuerpo (LC), largo de cabeza (LCA), ancho de cabeza (AC), largo de lomo (LL), ancho de lomo (AL), perímetro torácico (PT), perímetro de muslo (PM), largo de muslo (LM), perímetro de brazuelo (PB), largo de brazuelo (LB) y cuadrado medio de la grupa (CMG), así como el peso de carcasa (PC). Los datos fueron analizados para determinar la mejor ecuación de regresión y establecer el mejor modelo lineal predictivo del peso de carcasa. Se utilizó el proceso «Step-Wise Regression» del paquete estadístico SAS. Las combinaciones de variables independientes en el modelo revelaron que las variables PV, PT, AC y LL dan una mejor explicación del PC a la edad de beneficio (R2 =0.71; Cp-Mallows=1.63)