相关论文: Linear vs non-linear QCD evolution: from HERA data…
We present a determination of the parton distribution functions of the proton in which NLO and NNLO fixed-order calculations are supplemented by NLLx small-x resummation. Deep inelastic structure functions are computed consistently at…
A search for physics beyond the Standard Model in neutral current deep inelastic scattering at high negative four-momentum transfer squared Q^2 is performed in e^{\pm}p collisions at HERA. The differential cross section ds/dQ^2, measured…
The evolution of the linear and scale independent bias, based on the most popular dark matter bias models within the $\Lambda$CDM cosmology, is confronted to that of the Dark Energy Survey (DES) Luminous Red Galaxies (LRGs). Applying a…
Closed expressions are presented for the contributions to QCD non-singlet forward evolution kernels $P(z)$ for the DGLAP equation and to $V(x,y)$ for non-forward (ER-BL) evolution equation for a certain class of diagrams which include…
Deep learning-based Computer-Aided Diagnosis (CAD) has attracted appealing attention in academic researches and clinical applications. Nevertheless, the Convolutional Neural Networks (CNNs) diagnosis system heavily relies on the…
The possibility to reanalyse data taken by the HERA experiments offers the chance to study modern QCD jet and event-shape observables in deep-inelastic scattering production. In this contribution we present resummed and matched predictions…
We perform analysis of the small x non-linear evolution equation formulated in momentum space supplemented by higher order terms. The equation is defined in wide range of transverse momentum and longitudinal momentum fraction extending…
We study the effects of the sequence on the propagation of nonlinear excitations in simple models of DNA in which we incorporate actual DNA sequences obtained from human genome data. We show that kink propagation requires forces over a…
We investigate enhancing the sensitivity of new physics searches at the LHC by machine learning in the case of background dominance and a high degree of overlap between the observables for signal and background. We use two different models,…
Accurate models are essential for design, performance prediction, control, and diagnostics in complex engineering systems. Physics-based models excel during the design phase but often become outdated during system deployment due to changing…
We present a fitting formula for the non-linear evolution of the bispectrum in CDM models, obtained from measurements in high resolution numerical simulations. The formula interpolates between the perturbative and highly non-linear regimes,…
This paper develops a unified framework for the identification, estimation, and uniform inference of local treatment effects (LTEs) in sharp regression kink designs (RKDs). These LTEs quantify the effect of a marginal change in the…
We investigate small-x effects in forward-jet production at HERA in the two-hard-scale region kT ~ Q>>Lambda_QCD. We show that, despite describing different energy regimes, both a BFKL parametrization and saturation parametrizations…
Robustness in dissipative light-matter systems has recently been associated with resonance conditions or geodesic evolution. We show that, in the nonlinear Jaynes-Cummings model, these conditions are necessary but not sufficient. Using a…
The analysis of Type Ia supernova data over the past decade has been a notable success story in cosmology. These standard candles offer us an unparalleled opportunity of studying the cosmological expansion out to a redshift of ~1.5. The…
High-dimensional biological data often exhibit a severe mismatch between feature dimensionality and sample size, making reliable classification difficult in extremely small-data regimes. In these settings, kernel methods can lose…
Selected recent data from collider experiments pertaining to the understanding of QCD at low Bjorken-x are reviewed. The status of QCD and Regge factorisation in hard diffractive interactions is discussed in terms of data from HERA and the…
Many of the existing machine learning algorithms, both supervised and unsupervised, depend on the quality of the input characteristics to generate a good model. The amount of these variables is also important, since performance tends to…
The $Q^2$ dependence of the ratios of the cross sections of deep inelastic lepton--nucleus scattering is studied in the framework of leading twist, lowest order perturbative QCD. The $\log Q^2$ slope of the ratio $F_2^{\rm Sn}/F_2^{\rm C}$…
We consider strata of curves carrying a residueless meromorphic differential inducing a spin structure on the curve. The cohomology classes of the closures of these strata, weighted by the parity of the spin structures, form a partial…