Abstract: We present a new numerical program, HTurbo, which provides fast and numerically precise predictions for Higgs boson production cross sections. The present version of the code implements the perturbative QCD expansion up to the next-to-next-to-leading order also combined with the resummation of the large logarithmic corrections at small transverse momenta up to next-to-next-to-leading logarithmic accuracy and it includes the Higgs boson production through gluon fusion and decay in two photons with the full dependence on the final-state kinematics. Arbitrary kinematical cuts can be applied to the final states in order to obtain fiducial cross sections and associated kinematical distributions. We present a benchmark comparison with the predictions obtained with the numerical programs HRes and HNNLO programs for which HTurbo represents an improved reimplementation.

Abstract: We consider the radiation of a soft gluon (g) and a soft quark-antiquark (qq & macr;) pair in QCD hard scattering. In the soft limit the scattering amplitude has a singular behaviour that is factorized and controlled by a soft current, which has a process-independent structure in colour space. We evaluate the soft gqq & macr; current at the tree level for an arbitrary multiparton scattering process. The irreducible correlation component of the current includes strictly nonabelian terms and also terms with an abelian character. Analogous abelian correlations appear for soft photon-lepton- antilepton emission in QED. The squared current for soft gqq & macr; emission produces colour dipole and colourtripole interactions between the hard-scattering partons. The colour tripole interactions are odd under charge conjugation and lead to charge asymmetry effects. We consider the specific applications to processes with two and three hard partons, and we discuss the structure of the corresponding charge asymmetry contributions. We also generalize our QCD results to the cases of QED and mixed QCD x QED radiative corrections.

Abstract: Clustering is one of the most frequent problems in many domains, in particular, in particle physics where jet reconstruction is central in experimental analyses. Jet clustering at the CERN's Large Hadron Collider (LHC) is computationally expensive and the difficulty of this task will increase with the upcoming High-Luminosity LHC (HL-LHC). In this paper, we study the case in which quantum computing algorithms might improve jet clustering by considering two novel quantum algorithms which may speed up the classical jet clustering algorithms. The first one is a quantum subroutine to compute a Minkowski-based distance between two data points, whereas the second one consists of a quantum circuit to track the maximum into a list of unsorted data. The latter algorithm could be of value beyond particle physics, for instance in statistics. When one or both of these algorithms are implemented into the classical versions of well-known clustering algorithms (K-means, affinity propagation, and k(T) -jet) we obtain efficiencies comparable to those of their classical counterparts. Even more, exponential speed-up could be achieved, in the first two algorithms, in data dimensionality and data length when the distance algorithm or the maximum searching algorithm are applied.