Related papers: Determination of Collins-Soper kernel from cross-s…
We use a suitable version of the so-called "kernel trick" to devise two-sample (homogeneity) tests, especially focussed on high-dimensional and functional data. Our proposal entails a simplification related to the important practical…
We present an updated extraction of the transversity parton distribution based on the analysis of pion-pair production in deep-inelastic scattering off transversely polarized targets in collinear factorization. Data for proton and deuteron…
We present an updated study of the Collins azimuthal asymmetries for pion-in-jet production in polarized $pp$ collisions. To this aim, we employ a recent extraction of the transversity and Collins fragmentation functions from semi-inclusive…
We introduce CO2, an efficient algorithm to produce convexly-weighted coresets with respect to generic smooth divergences. By employing a functional Taylor expansion, we show a local equivalence between sufficiently regular losses and their…
In this talk we present a perturbative QCD improved parton model calculation for light meson production in high energy heavy ion collisions. In order to describe the experimental data properly, one needs to augment the standard pQCD model…
We perform a global fit of the available polarized Semi-Inclusive Deep Inelastic Scattering (SIDIS), polarized pion-induced Drell-Yan (DY) and $W^\pm/Z$ boson production data at N$^3$LO and NNLO accuracy of the Transverse Momentum Dependent…
We propose a Monte Carlo code for the simulation of the fragmentation process of polarized quarks into pseudoscalar mesons. Such process is generated recursively once the flavour, the energy and the spin density matrix of the initial quark…
Crosscorrelation structures in the Green function retrieval by crosscorrelating wavefields are revealed using rigorous mathematical theory on integral equations. The previous practice on extracting the Green function by crosscorrelating the…
We study photoabsorption reaction and real Compton scattering (RCS) within the color dipole model. We rely on a photon wave function derived in the instanton vacuum model, and on the energy dependent phenomenological elastic dipole…
We evaluate the pion and kaon transverse momentum dependent parton distribution functions (TMDPDFs) in the instanton liquid model (ILM), a model of the QCD vacuum at low resolution. The relevant TMDs are factored into a constituent quark…
Model selection when designing deep learning systems for specific use-cases can be a challenging task as many options exist and it can be difficult to know the trade-off between them. Therefore, we investigate a number of state of the art…
We demonstrate that distributed block coordinate descent can quickly solve kernel regression and classification problems with millions of data points. Armed with this capability, we conduct a thorough comparison between the full kernel, the…
We introduce a general framework to construct multi-emission kernels for parton branching algorithms at the amplitude level and across different soft and collinear limits. We highlight the connection of kinematic parameterizations and…
Compton scattering between electrons and photons plays a crucial role in astrophysical plasmas. Many important aspects of this process can be captured by using the so-called Compton scattering kernel. For isotropic media, exact analytic…
In this paper we use Gaussian processes (kernel methods) to learn mappings between trajectories of distinct differential equations. Our goal is to simplify both the representation and the solution of these equations. We begin by examining…
Comparing differently sized data sets is one main task in model assessment and calibration. This is due to field data being generally sparse compared to simulated model results. We tackled this task by the application of a new…
The formalism for uniform description of Drell-Yan transverse-momentum spectrum is presented in a framework of High-Energy Factorization, which smoothly interpolates between Collins-Soper-Sterman formalism at $|{\bf q}_T|\ll Q$ and usual…
With the emergence of passive and active optical sensors available for geospatial imaging, information fusion across sensors is becoming ever more important. An important aspect of single (or multiple) sensor geospatial image analysis is…
We introduce kernel thinning, a new procedure for compressing a distribution $\mathbb{P}$ more effectively than i.i.d. sampling or standard thinning. Given a suitable reproducing kernel $\mathbf{k}_{\star}$ and $O(n^2)$ time, kernel…
We present simple, user-friendly bounds for the expected operator norm of a random kernel matrix under general conditions on the kernel function $k(\cdot,\cdot)$. Our approach uses decoupling results for U-statistics and the non-commutative…