Zobrazeno 1 - 10
of 2 594
pro vyhledávání: '"Pata , Joosep"'
Tau leptons serve as an important tool for studying the production of Higgs and electroweak bosons, both within and beyond the Standard Model of particle physics. Accurate reconstruction and identification of hadronically decaying tau leptons is a cr
Externí odkaz:
http://arxiv.org/abs/2407.06788
Autor:
Pata, Joosep, Wulff, Eric, Mokhtar, Farouk, Southwick, David, Zhang, Mengke, Girone, Maria, Duarte, Javier
Publikováno v:
Commun Phys 7, 124 (2024)
Efficient and accurate algorithms are necessary to reconstruct particles in the highly granular detectors anticipated at the High-Luminosity Large Hadron Collider and the Future Circular Collider. We study scalable machine learning models for event r
Externí odkaz:
http://arxiv.org/abs/2309.06782
Autor:
Põder, Sven, Benito, María, Pata, Joosep, Kipper, Rain, Ramler, Heleri, Hütsi, Gert, Kolka, Indrek, Thomas, Guillaume F.
Publikováno v:
A&A, 676 (2023) A134
Our goal is to calculate the circular velocity curve of the Milky Way, along with corresponding uncertainties that quantify various sources of systematic uncertainty in a self-consistent manner. The observed rotational velocities are described as cir
Externí odkaz:
http://arxiv.org/abs/2309.02895
Publikováno v:
Comput.Phys.Commun. 298 (2024) 109095
Identifying and reconstructing hadronic $\tau$ decays ($\tau_{\textrm{h}}$) is an important task at current and future high-energy physics experiments, as $\tau_{\textrm{h}}$ represent an important tool to analyze the production of Higgs and electrow
Externí odkaz:
http://arxiv.org/abs/2307.07747
Autor:
Lewicki, Marek, Müürsepp, Kristjan, Pata, Joosep, Vasar, Martin, Vaskonen, Ville, Veermäe, Hardi
We study the impact of the ambient fluid on the evolution of collapsing false vacuum bubbles by simulating the dynamics of a coupled bubble-particle system. A significant increase in the mass of the particles across the bubble wall leads to a buildup
Externí odkaz:
http://arxiv.org/abs/2305.07702
Autor:
Mokhtar, Farouk, Pata, Joosep, Duarte, Javier, Wulff, Eric, Pierini, Maurizio, Vlimant, Jean-Roch
Publikováno v:
ACAT 2022: 21st International Workshop on Advanced Computing and Analysis Techniques in Physics Research
The particle-flow (PF) algorithm, which infers particles based on tracks and calorimeter clusters, is of central importance to event reconstruction in the CMS experiment at the CERN LHC, and has been a focus of development in light of planned Phase-2
Externí odkaz:
http://arxiv.org/abs/2303.17657
The abundance of dark matter (DM) subhalos orbiting a host galaxy is a generic prediction of the cosmological framework, and is a promising way to constrain the nature of DM. In this paper, we investigate the use of machine learning-based tools to qu
Externí odkaz:
http://arxiv.org/abs/2203.08161
In the European Center of Excellence in Exascale computing "Research on AI- and Simulation-Based Engineering at Exascale" (CoE RAISE), researchers develop novel, scalable AI technologies towards Exascale. This work exercises High Performance Computin
Externí odkaz:
http://arxiv.org/abs/2203.01112
Autor:
Pata, Joosep, Duarte, Javier, Mokhtar, Farouk, Wulff, Eric, Yoo, Jieun, Vlimant, Jean-Roch, Pierini, Maurizio, Girone, Maria
Publikováno v:
J. Phys.: Conf. Ser. 2438, 012100 (2023)
We provide details on the implementation of a machine-learning based particle flow algorithm for CMS. The standard particle flow algorithm reconstructs stable particles based on calorimeter clusters and tracks to provide a global event reconstruction
Externí odkaz:
http://arxiv.org/abs/2203.00330
Autor:
Mokhtar, Farouk, Kansal, Raghav, Diaz, Daniel, Duarte, Javier, Pata, Joosep, Pierini, Maurizio, Vlimant, Jean-Roch
The particle-flow (PF) algorithm is used in general-purpose particle detectors to reconstruct a comprehensive particle-level view of the collision by combining information from different subdetectors. A graph neural network (GNN) model, known as the
Externí odkaz:
http://arxiv.org/abs/2111.12840