GPU Day 2022

Session

Session VI

21 Jun 2022, 11:00

Hotel Mercure Budapest Castle Hill

48. Studying hadronization with Machine Learning techniques

Gabor Biro (MTA Wigner FK)

21/06/2022, 11:00

Lecture

Hadronization is a non-perturbative process, which theoretical description can not be deduced from first principles. Modeling hadron formation, requires several assumptions and various phenomenological approaches. Utilizing state-of-the-art Computer Vision and Deep Learning algorithms, it is eventually possible to train neural networks to learn non-linear and non-perturbative features of the...

37. Polynomial speedup in exact Torontonian calculation by a scalable recursive algorithm

Ágoston Kaposi

21/06/2022, 11:20

Evaluating the Torontonian function is a central computational challenge in the simulation of Gaussian Boson Sampling (GBS) with threshold detection.
During the calculation of this matrix function exponentially large number of determinants have to be computed.
We proposed a recursive algorithm providing a polynomial speedup in the exact calculation of the Torontonian compared to...

69. Machine learning Hadron Spectral Functions in Lattice QCD

Feiyi Liu (Eötvös Loránd University & Central China Normal University)

21/06/2022, 11:40

Lecture

We study the inverse problem of reconstructing spectral functions from Euclidean correlation functions via machine learning. We propose a novel neural network, SVAE, which is based on the variational autoencoder (VAE) and can be naturally applied to the inverse problem. The prominent feature of the SVAE is that a Shannon-Jaynes entropy term having the ground truth values of spectral functions...

45. Exploring SARS-CoV-2 receptor binding domain variants

Ákos Gellért

21/06/2022, 12:00

Lecture

The COVID-19 epidemic created an extraordinary situation for the whole humanity, claiming millions of lives and causing a significant economic setback. At the same time, the international research community has rapidly generated an order of magnitude larger data set than ever before, which can contribute to understanding the evolution and dynamics of the epidemic, to its containment and to the...