Related papers: Sampling NNLO QCD phase space with normalizing flo…
In this talk results from a new QCD analysis in leading (LO) and next--to--leading (NLO) order are presented. New parametrizations of the polarized quark and gluon densities are derived together with parametrizations of their fully…
We introduce neural particle smoothing, a sequential Monte Carlo method for sampling annotations of an input string from a given probability model. In contrast to conventional particle filtering algorithms, we train a proposal distribution…
This article is devoted to the construction of new numerical methods for the semiclassical Schr\"odinger equation. A phase-amplitude reformulation of the equation is described where the Planck constant epsilon is not a singular parameter.…
In this work, we briefly report on the current status of an alternative subtraction scheme which is based on the splitting kernels of an improved parton shower prescription. Our focus is here on more recent developments as well as generic…
Normalizing flows are an essential alternative to GANs for generative modelling, which can be optimized directly on the maximum likelihood of the dataset. They also allow computation of the exact latent vector corresponding to an image…
Neural implicit representations have become a popular choice for modeling surfaces due to their adaptability in resolution and support for complex topology. While previous works have achieved impressive reconstruction quality by training on…
We construct predictions for top quark pair differential distributions at hadron colliders that combine state-of-the-art NNLO QCD calculations with double resummation at NNLL' accuracy of threshold logarithms arising from soft gluon…
Computations at next-to-leading order in the Standard Model offer new technical challenges in presence of higher dimensional operators. We introduce a framework that, starting from the top-quark effective field theory at dimension six,…
We calculate the next-to-leading order inclusive total cross sections for the associated production processes $pp\to \tilde{t}_i\tilde{\chi}_k^-+X$ in the Minimal Supersymmetric Standard Model at the CERN LHC. Our results provide the…
The problem of heterogeneous clients in federated learning has recently drawn a lot of attention. Spectral model sharding, i.e., partitioning the model parameters into low-rank matrices based on the singular value decomposition, has been…
We present a new subtraction scheme for next-to-leading order QCD calculations, where the momentum mapping and the splitting functions have been derived in the context of an improved parton shower formulation. A main advantage of our scheme…
I present results for the resummation of soft-gluon contributions to QCD hard-scattering cross sections at next-to-next-to-leading logarithm accuracy. A key ingredient is the calculation of two-loop soft anomalous dimensions for the…
In many scientific applications, the target probability distribution cannot be evaluated in closed form or sampled from directly. Instead, it can often be decomposed into multiple components, some of which are accessible only through…
Physical observables, such as the scattering phase shifts and the binding energies, calculated from the non-local HAL QCD potential do not depend on the sink operators used to define the potential. This is called the scheme independence of…
The semi-inclusive production of identified hadrons in deeply inelastic lepton scattering on polarized nucleons allows to probe the spin structure of the nucleon target in a more detailed level than through fully inclusive processes. We…
Ptychography is an imaging technique which involves a sample being illuminated by a coherent, localized probe of illumination. When the probe interacts with the sample, the light is diffracted and a diffraction pattern is detected. Then the…
The aim of this paper is to introduce a new Monte Carlo method based on importance sampling techniques for the simulation of stochastic differential equations. The main idea is to combine random walk on squares or rectangles methods with…
We perform a NLO QCD analysis of deep-inelastic scattering data, in which we account for absorptive corrections. These corrections are determined from a simultaneous analysis of diffractive deep-inelastic data. The absorptive effects are…
Sequential Monte Carlo Samplers are a class of stochastic algorithms for Monte Carlo integral estimation w.r.t. probability distributions, which combine elements of Markov chain Monte Carlo methods and importance sampling/resampling…
The possibility of an improvement of current NLO Monte Carlo event generators by means of choosing a suitable factorization scheme is studied. The optimal factorization scheme for combining initial state parton showers and NLO hard…