Antal Jakovác, Anna Horváth, Bence Dudás
Abstract: Environmental sound sample analysis using artificial intelligence methods for applied research.
Neelkamal Mallick [1], Suraj Prasad [1], Aditya Nath Mishra [2,4], Raghunath Sahoo [1] and Gergely Gábor Barnaföldi [3] (2024.05.01 - 2024.08.31)
[1] Department of Physics, Indian Institute of Technology Indore [2] Department of Physics, School of Applied Sciences, REVA University [3] Wigner Research Center for Physics [4] Department of Physics, University Centre For Research & Development (UCRD), Chandigarh University
Abstract: A nucleus having 4n number of nucleons, such as 8Be, 12C, 16O, etc., is theorized to possess clusters of α particles (4He nucleus). In this study, we exploit the anisotropic flow coefficients to discern the effects of an \(\alpha\)-clustered nuclear geometry w.r.t. a Woods-Saxon nuclear distribution at \(\sqrt{s_{NN}} = 7\) TeV LHC energy.
Zoltán Lehóczky, Márk Bartha (2024.01.01 - 05.31)
Lombiq Ltd.
Link: GPU Day Chase Study
Abstract: GPU Day is a conference organized by the Wigner Scientific Computational Laboratory that focuses on massively parallel computing, visualization, and data analysis in both scientific and industrial applications. We also presented our Hastlayer .NET hardware accelerator project many times there too.
The website serves as an information hub for these annual conferences. It was initially running on Orchard 1 DotNest, but now it was time to migrate it to Orchard Core. While these migrations always come with certain challenges due to the new features introduced in Orchard Core, we tried to keep things easy by not changing the frontend of the site, even though it's somewhat outdated.
Szabó, Vencel (ELTE); Barbola, Milán Gábor (ELTE); Méhes, Máté (ELTE); Gábor Papp (ELTE), Bíró, Gábor (Wigner); Jólesz, Zsófia (ELTE-Wigner); Dudás, Bence (ELTE-Wigner) (2024.03.01 - 2024.06.30)
Abstract: Proton Computer Tomography (pCT) differs from the "normal" photon-based CT, since the basic reaction with matter differs: while in pCT the small angle Coulomb scattering is the dominant process, in (photon) CT the incoming photon is absorbed. That makes pCT a much harder problem.
During the project the students generate input data for the pCT algorithm, running massively the GATE simulation software on different phantoms. Evaluating the inputs with the Richardson-Lucy algorithm we determine the number of runs at different positions and angles to obtain az accetable resolution of the image. Futher plans involve the optimization of the Richardson-Lucy algorithm on GPU cluster to speed up the calculations. Furthermore, they also try to reconstruct the pCT input data from the detector outputs.
Örs Legeza (2023.11.01 - 2024.04.30)
Wigner Research Centre for Physics
Abstract: Numerical simulation of quantum systems in which correlations between electrons are strong, i.e., they cannot be described by perturbation theory is in the focus of modern physics and chemistry. This, however, poses major challenge as the computational complexity usually scales exponentially with system size. Therefore, those algorithms in which such scaling can be reduced to polynomial form is subject of intense research.
The density matrix renormalization group (DMRG) method fulfills such criteria. In addition, the related matrix and tensor algebra can be organized into millions of independent subtaks, that makes the method ideal for massive parallelization. Using our code, during the first phase of the project (2021-2022) we have already performed large scale simulations on various quantum systems which lead to two publications accessible on arXiv:
[1] Massively Parallel Tensor Network State Algorithms on Hybrid CPU-GPU Based Architectures, Andor Menczer, Örs Legeza, arXiv:2305.05581 (2023)
[2] Boosting the effective performance of massively parallel tensor network state algorithms on hybrid CPU-GPU based architectures via non-Abelian symmetries, Andor Menczer, Örs Legeza, arXiv:2309.16724 (2023)
The GPU Laboratory is explicitly cited in the acknowledgement in Ref.[1] as part of the results were generated via project phase-1. In the second phase of the project we aim to further test our simulations using A100 GPU based infrastructure. Depending on the results we intend to update or extend results reported in Ref.[2].
Ádám Kadlecsik (2023.11.01 - 2024.03.31)
Eötvös Loránd University
Abstract: The observed small, thus usually solid exoplanets in general orbit their central star closely - making them easier to detect with terrestrial and space instruments. This means that they must be tidally locked, meaning their orbit around their central star ("year") and their rotation around their axis ("day") have the same period. Because of the tidally locked orbit the exoplanet shows its same side to the star, thus the planet has a permanent day and night hemisphere. Ergo the flow can be modeled with a rotating layout, where the lateral boundary rotating with the water body simulating the atmosphere has an azimuthal dipole-like heat flux boundary condition. This can be investigated using experimental and simulational methods as well.
Anna Horváth [1,2], Gergely Gábor Barnaföldi [1], Emese Forgács-Dajka [2] (2023.09.01-2023.12.31 )
[1] Wigner Research Centre for Physics
[2] Eötvös Loránd University
Abstract: We are investigating compact stars within a static, spherically symmetric Kaluza-Klein-like theory that encompasses extra compactified spatial dimensions. We produced an equation of state that can be used to model neutron stars together with the Tolman-Oppenheimer-Volkoff equation. Simulating the structure of these objects (calculating their main observables, the mass and the radius) and carrying out a thorough analysis requires us to use computational-heavy programming. Stars with various boundary conditions (such as the central energy density) and theoretical parameters (like the size of the extra dimension) are considered. For this type of calculations it is essentially useful to utilise parallelism, which is best executed on multi-core processors. This project tests theories beyond the standard model of particle physics, with an emphasis on the possibility of giving constraints on the size of one extra compactified spatial dimension.
Ákos Gellért[1,2] , Oz Kilim[1] , Anikó Mentes[1] and István Csabai[1] (2023.02.15 - 2023.12.15)
[1] ELTE Department of Physics of Complex Systems [2] ELKH Veterinary Medical Research Institute
Abstract: The first recorded pandemic of the flu occurred in 1580 and since then, flu pandemics have occurred several times throughout history, with the most severe being the Spanish flu in 1918-1919 which killed millions of people worldwide. In the 20th century, significant progress was made in the understanding of the virus and the development of vaccines, which have greatly reduced the impact of flu pandemics. Despite this progress, the flu continues to be a major public health issue, with millions of cases reported each year and an annual death toll in the tens of thousands.
Hemagglutinin, a surface membrane protein of the Influenza virus plays an important role in the infection process of the virus, as it allows the virus to attach to and penetrate host cells. The flu vaccine is formulated each year based on which strains of the virus are predicted to be most prevalent, and it is designed to stimulate the body's immune response to the hemagglutinin protein on those strains. Many antigenic maps have been constructed this far, which reveal the relationships between different strains of a virus, specifically with regards to the way their antigens [1] (e.g., hemagglutinin) are recognized by the immune system. Experimental Influenza HA deep mutational data [2] are also available for the research community to explore the virus functions.
In this project, we aim to in silico combine antigenic maps and deep mutational scanning data to obtain a more comprehensive understanding of the evolution and functional properties of Influenza virus. For example, combining antigenic map data with deep mutational scanning data can provide information about how different mutations affect the ability of a virus to evade the immune response, as well as which regions of the virus are critical for this evasion. This information can be used to inform the design of vaccines and antiviral drugs that target specific regions of the virus that are critical for its function and evolution. We will use AlphaFold2 [3] and ESMFold2 [4] the fastest AI based and most reliable protein structure prediction applications in the world to generate single and/or multiple mutant structures of various Influenza HA protein.
[1] Antigenic map. [2] Flu HA DMS.. [3] J. Jumper et al., “Highly accurate protein structure prediction with AlphaFold,” Nat. 2021 5967873, vol. 596, no. 7873, pp. 583–589, Jul. 2021, doi: 10.1038/s41586-021-03819-2. [4] ESMFold.