Related papers: The Elusive p-air Cross Section
In big data analysis, a simple task such as linear regression can become very challenging as the variable dimension $p$ grows. As a result, variable screening is inevitable in many scientific studies. In recent years, randomized algorithms…
Motivated by the expectation that new physics may manifest itself in the form of very heavy new particles, most of the operation time of the LHC is devoted to $pp$ collisions at the highest achievable energies and collision rates. The large…
In the present investigation we study the leading and subleading high-energy behavior of hadron-hadron total cross sections using a best-fit analysis of hadronic scattering data. The parametrization used for the hadron-hadron total cross…
Using a simple eikonal approach to the treatment of Coulomb-nuclear interference and form-factors effects and taking into account the curvature effects in high-energy $pp$ and $\bar{p}p$ scattering, we determine the basic parameters $B$,…
Simultaneous $\chi^{2}$ analyses are performed for elastic scattering and fusion cross section data for the $^{12}$C+$^{208}$Pb system at near-Coulomb-barrier energies by using the extended optical model approach in which the polarization…
The LO hadronic vacuum polarization (VP) contribution to the muon anomalous magnetic moment $a_\mu$ is obtained as the integral as a function of energy of an expression that involves the ratio of the $e^+e^- \rightarrow \mathrm{hadron}$…
Genetic algorithms are a widely used method in chemometrics for extracting variable subsets with high prediction power. Most fitness measures used by these genetic algorithms are based on the ordinary least-squares fit of the resulting…
We present an efficient algorithm for the least squares parameter fitting optimized for component separation in multi-frequency CMB experiments. We sidestep some of the problems associated with non-linear optimization by taking advantage of…
Making use of a derivative dispersion approach, we investigate the behavior of the the total cross section and the rho parameter for pp and p(bar)p scattering from accelerator to cosmic ray energies. The discrepancies in the cosmic ray…
We present details of the calculation of the $pp\to W(\to l\nu) \gamma$ process at next-to-next-to-leading order in QCD, calculated using the jettiness slicing method. The calculation is based entirely on analytic amplitudes. Because of the…
This work presents the results of a revised analysis of the low-energy (pion laboratory kinetic energy T(sub pi) < 100 MeV) pi+ p data using recently obtained electromagnetic corrections. The measurements are analyzed assuming extended…
We report the results of a phase-shift analysis (PSA) of the low-energy $\pi^\pm p$ elastic-scattering data. Following the method which we had set forth in our previous PSA (Matsinos et al., 2006), we first investigate the self-consistency…
Simultaneous $\chi^{2}$ analyses previously made for elastic scattering and fusion cross section data for the $^{6}$Li+$^{208}$Pb system is extended to the $^{7}$Li+$^{208}$Pb system at near-Coulomb-barrier energies based on the extended…
The smart grid vision is to build an intelligent power network with an unprecedented level of situational awareness and controllability over its services and infrastructure. This paper advocates statistical inference methods to robustify…
Double-differential dijet cross sections measured in pp collisions at the LHC with a 7 TeV centre-of-mass energy are presented as functions of dijet mass and rapidity separation of the two highest-pT jets. These measurements are obtained…
The latest experimental and theoretical developments in the high-precision determination of the strong coupling $\alpha_s$ are briefly reviewed. Six groups of observables: (i) lattice QCD data, (ii) hadronic $\tau$ decays, (iii)…
An exploit of the Sequential Importance Sampling (SIS) algorithm using Differential Algebra (DA) techniques is derived to develop an efficient particle filter. The filter creates an original kind of particles, called scout particles, that…
In order to retrieve cosmological parameters from photometric surveys, we need to estimate the distribution of the photometric redshift in the sky with excellent accuracy. We use and apply three different machine learning methods to…
We propose using neural networks to detect data departures from a given reference model, with no prior bias on the nature of the new physics responsible for the discrepancy. The virtues of neural networks as unbiased function approximants…
The final results on the combination of all inclusive deep-inelastic scattering cross section data from the H1 and ZEUS experiments at HERA are reviewed. The parton distribution functions (PDFs) extracted from these data (HERAPDF2.0) and…