Related papers: Progress on NNLO subtraction
Subsampling is an effective approach to alleviate the computational burden associated with large-scale datasets. Nevertheless, existing subsampling estimators incur a substantial loss in estimation efficiency compared to estimators based on…
Using non-relativistic effective theories, new next-to-next-to-leading order (NNLO) QCD corrections to the total $t\bar t$ production cross section at the Linear Collider have been calculated recently. In this article the NNLO calculations…
We present a new method to compute higher-order corrections to physical cross-sections, at Next-to-Leading Order and beyond. This method, based on the Loop Tree Duality, leads to locally integrable expressions in four dimensions. By…
The antenna subtraction method has been successfully applied to a wide range of processes relevant for the Large Hadron Collider at next-to-next-to-leading order in $\alpha_s$ (NNLO). We propose an algorithm for building antenna functions…
We discuss the combination of NNLO standard QCD evolution and scheme-invariant analysis for unpolarized DIS structure functions data as a method to reduce the theoretical errors on the determination of $\alpha_s(M_Z^2)$ to $\sim 1$% in…
Accurate determination of fusion-evaporation reaction cross section is important in experimental nuclear physics studies. In this study, by using artificial neural network (ANN) method, we have estimated the cross section values for…
We present analytic evaluations of some integrals needed to give explicitly the integrated real-virtual integrated counterterms, based on a recently proposed subtraction scheme for next-to-next-to-leading order (NNLO) jet cross sections.…
We propose a new subtraction scheme for next-to-leading order QCD calculations. Our scheme is based on the momentum mapping and on the splitting functions derived in the context of an improved parton shower formulation. Compared to standard…
Uncertainties in the NLO calculation of the inclusive jet cross section due to the choice of renormalization scale, parton distribution functions and clustering algorithm are explored. These are found to be similar in size to the current…
Four years ago, one of us introduced a novel subtraction scheme for the evaluation of double-real radiation contributions to cross sections at next-to-next-to-leading order (NNLO) in QCD. This approach, named SecToR Improved Phase sPacE for…
As a popular channel pruning method for convolutional neural networks (CNNs), network slimming (NS) has a three-stage process: (1) it trains a CNN with $\ell_1$ regularization applied to the scaling factors of the batch normalization…
Improved uniform error bounds on time-splitting methods are rigorously proven for the long-time dynamics of the weakly nonlinear Dirac equation (NLDE), where the nonlinearity strength is characterized by a dimensionless parameter…
The area of sublinear algorithms have recently received a lot of attention. In this setting, one has to choose specific access model for the input, as the algorithm does not have time to pre-process or even to see the whole input. A…
The choice of unfolding method for a cross-section measurement is tightly coupled to the model dependence of the efficiency correction and the overall impact of cross-section modeling uncertainties in the analysis. A key issue is the…
Statistically correcting measured cross sections for detector effects is an important step across many applications. In particle physics, this inverse problem is known as unfolding. In cases with complex instruments, the distortions they…
In this talk we examine how one-loop soft and collinear splitting functions occur in the calculation of next-to-next-to-leading order (NNLO) corrections to production rates, and we present the one-loop gluon soft and splitting functions,…
We review the theoretical ideas and tools required to arrive at a next-to-next-to-leading order (NNLO) description of the heavy quark-antiquark production cross section in $e^+e^-$ annihilation for the case that the center of mass kinetic…
In this paper, we present an algorithm to construct the qT distribution at NLO accuracy to arbitrary power precision, including the assembly of suitable zero-bin subtrahends, in a mathematically well-defined way for a generic choice of…
Semantic segmentation and instance level segmentation made substantial progress in recent years due to the emergence of deep neural networks (DNNs). A number of deep architectures with Convolution Neural Networks (CNNs) were proposed that…
We present a new method for the recognition of digital straight lines based on the slope. This method combines the Freeman's chain coding scheme and new discovered properties of the digital slope introduced in this paper. We also present…