Anna Horváth, Emese Forgács-Dajka, Gergely Gábor Barnaföldi (2024.12.01 - 2025.03.31)

Publication: The effect of multiple extra dimensions on the maximal mass of compact stars in Kaluza-Klein space-time

Abstract: Compact stars in the Kaluza-Klein space-time are investigated, with multiple additional compactified spatial dimensions (d). Within the extended phenomenological model, a static, spherically symmetric solution is considered, with the equation of state provided by a zero temperature, interacting multi-dimensional Fermi gas. The maximal masses of compact stars are calculated for different model parameters. We investigate the effect of the existence of multiple extra compactified dimensions within the Kaluza--Klein compact star structure. We investigate the effect of the number of extra dimensions in comparison with the effect of the excitation number.

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in Orchard Core, we tried to keep things easy by not changing the frontend of the site, even though it's somewhat outdated.

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.

András Biricz, ELTE (2024.11.01 - 2025.03.31)

Abstract: In this study, we developed a highly automated, AI-assisted pipeline for airborne pollen detection using microscopy images digitized from Hirst-type samplers. Our approach significantly reduces the need for manual annotation by using open-world object detection and transformer-based models for training dataset generation. The project used multi-regional datasets from Hungary, Sweden, France, and the Mediterranean region to train and evaluate models under both controlled and real-world conditions. Deep learning models were trained and benchmarked on GPU infrastructure, enabling efficient training of transformer-based object detection models. The final system demonstrated relatively high performance in cross-regional generalization and real-world applicability, contributing to modern, scalable solutions for allergen monitoring and ecological analysis.

Mira Gergácz, Ákos Keresztúri (2023.09.01-12.31.)

Publication: Survey of remnant seasonal ice patches at southern polar Mars

Abstract: The aim of this study is to survey the surface ice condensation periods of Martian ice with automatized methods using a Convolutional Neural Network (CNN) applied to High Resolution Imaging Science Experiment (HiRISE) imagery from the Mars Reconnaissance Orbiter (MRO) mission. Using a CNN trained to distinguish small (diameter ranging from \(1.5-300\) meters) ice patches from other surface forms turned out to be a feasible automatic method for this purpose. The surveyed region is the latitude band between \(-40°\) and \(-60°\) during the solar longitude range of \(0-90°\), before the southern polar cap spreads in the given latitude band.

Anna Horváth [1,2], Gergely Gábor Barnaföldi [1], Emese Forgács-Dajka[2] (2024.09.01-12.31)

[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 several 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. 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.

Örs Legeza (2023.11.01 - 2024.11.30)

Wigner Research Centre for Physics

Publications:
[1] Parallel implementation of the Density Matrix Renormalization Group method achieving a quarter petaFLOPS performance on a single DGX-H100 GPU node
[2] Two-dimensional quantum lattice models via mode optimized hybrid CPU-GPU density matrix renormalization group method
[3] Boosting the effective performance of massively parallel tensor network state algorithms on hybrid CPU-GPU based architectures via non-Abelian symmetries
[4] Massively Parallel Tensor Network State Algorithms on Hybrid CPU-GPU Based Architectures
[5] Cost optimized ab initio tensor network state methods: industrial perspectives

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].

Péter Maller\(^1\), Emese Forgács-Dajka\(^1\), Dániel Berényi\(^2\) (2024.10.01. - 2025.02.28.)

1. Eötvös Loránd University
2. Freelancer

Abstract: The main goal of the project is to parallelize a well-known Babcock-Leighton solar dynamo model, which can be used to study the development of the Sun's global magnetic field, thus solar activity. The prediction of solar activity is still challenging, as a quasi-periodic, stochastic process is in the background. In addition, the dynamo, which describes the underlying physics, is still one of the great unsolved problems of astrophysics. Of course, this does not mean that we do not have ideas or even models regarding the development of the magnetic field, but these models require further investigation and development.

The numerical code we created was based on an earlier Fortran language program, developed several decades ago, the modernization of which was motivated by several things: on the one hand, there are redundancies in the code written by many people over a long period of time, but also parts that are apparently redundant, on the other hand, further development is difficult due to the structure of the code. Thus, our first goal was to optimize and refactor the previous code, for which we chose the C programming language. Next, we want to parallelize the code, for which we use the CUDA framework. The reduction in running time achieved by parallelization enables comprehensive analyses: we can examine the development of several components of the magnetic field at a higher spatial resolution, but we can also map the parameter space of the model. Among our goals is the comparison of different numerical methods, such as ADI (Alternating-Direction Implicit) and FTCS (Forward Time-Centered Space). Overall, during the implementation of the project, we want to explore different options in order to choose the right compromise solution in terms of performance, accuracy and future improvements.

Balázs Kacskovics\(^{1,2}\), Dániel Barta\(^{1}\) (2024.01.01 - 05.31)

\(^{1}\) HUN-REN Wigner Research Centre for Physics
\(^{2}\) Pécs University

Publication: Comparing eccentric waveform models based on post-Newtonian and effective-one-body approaches

Abstract: In the framework of this project, we compare two numerical models, namely CBWaves and SEOBNRE, which use the post-Newtonian and effective one-body approaches to model eccentric binaries. To explore the discrepancy between the two models, 260,000 simulations are performed on a grid stretched by the chosen parameter space - 20,000 for non-spinning configurations and 240,000 for spinning configurations. Each point on this grid, denoted by \(i\), is determined by the mass ratio \(\nu \equiv m_1/m_2\in [0.1,1]\), the gravitational mass \(m_i \in [10M_\odot, 100M_\odot]\), the corresponding spin magnitude \(S_i \in [0,0.6]\) and a constant initial orbital eccentricity \(e_{0}\). We will perform a comprehensive study to determine whether there is a discrepancy between the waveforms generated by the two codes.

Győző Kovács, Péter Kovács, György Wolf (2023.01.01 - 11.30)

Wigner Research Centre for Physics

Grant: NKFIH FK 131982

Publication: Phenomenology of isospin-symmetry breaking with vector mesons

Abstract: The extended linear sigma model (eLSM) is an advanced quarkmeson model that can be used to study meson phenomenology at zero temperature and the QCD phase diagram at finite temperature and/or baryon chemical potential. In order to make predictions, parameters of the model should be determined by fitting calculated physical quantities (like masses and decay widths) to their experimental values. The best fit and global minimum can be found by choosing some random starting points in the k-dimensional parameter space (in our case \(k > 14\)) and run a \(\chi^2\) multiparametric minimization. This procedure is numerically quite expensive and time-consuming. However, a large number of starting points (\(n ∼ 10^7\) ) is required to achieve a reasonable statistics and resolution in the parameter values. In order to gain a good understanding of the model, its parameter dependence, and parameterization, it is also necessary to perform the fitting also under variation of the physical quantities involved.

Győző Kovács [1], Péter Kovács [1], György Wolf [1], Pok Man Lo [2] (2023.01.01 - 11.30)

[1] Wigner Research Centre for Physics
[2] University of Wroclaw, Wroclaw

Grant: NKFIH FK 131982

Publication: Sensitivity of finite size effects to the boundary conditions and the vacuum term

Abstract: The effect of finite size/volume in effective field theory models is usually accounted for by some form of constrain in the momentum space, for example by low momentum cut-off or discretization. The latter results in a summation for momentum modes depending on the boundary condition used, rather than integrals. We study the size dependence of the baryon fluctuations in and around the critical endpoint in an improved quark-meson model, with particular attention to how they are affected by different modifications of the momentum space and the inclusion of the vacuum contribution. To determine the cumulant ratios describing the fluctuations, the higher order derivatives of the pressure are calculated. For this purpose, the finite difference method can be used, but this requires solving the field equations at several points for the derivative at only one point. This demands considerable computational power if the phase diagram and the size dependence are to be computed densely enough. On the other hand these calculations can be easily parallelised.

Emese Forgács-Dajka*, István Ballai** (2021.05.01-2021.12.31)

* Eötvös University, Dept. of Astronomy
** Solar Physics and Space Plasma Research Centre (SP2RC), Department of Applied Mathematics, The University of Sheffield

Publication: Parametric resonance of Alfvén waves driven by ionization-recombination waves in the weakly ionized solar atmosphere

Abstract: We investigate the nature and properties of shock waves propagating in an oblique direction to the ambient magnetic field in a partially ionised plasma modelling the plasma of solar prominences. In particular, we aim to analyse the observational signature of these shocks and investigate how our results can explain the recent observations of propagating bright blobs in solar prominences by Lin et al. (2012).

The equations of compressional single-fluid magnetohydrodynamic (MHD) equations are reduced with the help of a multiple scaling method to a well-known Burgers equation whose coefficients depend on the propagation angle of shock waves, plasma-β and the ionisation degree of the plasma. Our model is well-adapted for the separate discussion of shock waves arising from the nonlinear steepening of slow or fast magnetoacoustic waves. Using the standard jump conditions across the shock front (assuming a weak dissipation) we determine the jump in thermodynamic quantities that will be useful for comparison with observations.

Using the Cole-Hopf transform we solve the governing equation as an initial value problem of a diffusion-like equation and investigate the time necessary for a Gaussian initial wave profile to evolve into a shock, whose thickness is of the order of a few ion mean free path.

János Takátsy [1] Péter Kovács [1], György Wolf [1], Juergen Schaffner-Bielich [2] (2023.01.01 - 11.30)

[1] Wigner Research Centre for Physics
[2] University of Frankfurt

Grant: NKFIH FK 131982

Publication: What neutron stars tell about the hadron-quark phase transition: A Bayesian study

Abstract: The investigation of the phase diagram of Quantum Chromodynamics (QCD) at high densities is currently only possible through effective theories. Neutron stars are among the densest objects in our universe, possibly containing chirally symmetric matter as well. We calculate neutron star properties from our model with different parameterizations and confront the results with recent astrophysical observations. These astrophysical observations include mass measurements of neutron stars, NICER measurements and tidal deformability measurements of GW170817. We utilize a Bayesian framework to determine the most probable regions of the parameter space of our model, which requires high computing capacities in order to obtain the necessary statistics.

Balázs Szigeti, István Szapudi, Imre Barna, Gergely Gábor Barnaföldi (2024.08.01-2024.10.30.)

Abstract: The Hubble constant \(H_0\) characterizes the rate of the universe's expansion. The discrepancy between the low and high redshift measurements of \(H_0\) is the highest significance tension within the concordance \(\Lambda\)CDM paradigm. We show that a G\"odel inspired slowly rotating dark-fluid variant of the concordance model resolves this tension with an angular velocity today \(\omega_0 \simeq 2\times 10^{-3}\)~Gyr\(^{-1}\). Curiously, this is approximately also the maximal rotation with a tangential velocity less than the speed of light at the horizon.

Aneta Magdalena Wojnar, Anna Horváth, Gergely Gábor Barnaföldi (2024.08.01-2024.10.30.)

Abstract: Heisenberg's uncertainty relation can be modified in strong gravitational field. This study aims to investigate the same theoretical aspects in the 5-dimensional Kaluza--Kleing spacetime.

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

Publication: Anisotropic flow fluctuation as a possible signature of clustered nuclear geometry in O-O collisions at the Large Hadron Collider

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.

Antal Jakovác, Anna Horváth, Bence Dudás (2024.07.01-09.30)

Abstract: Environmental sound sample analysis using artificial intelligence methods for applied research.

Dániel Léber , Mihály Ormos (2024.07.01-09.30)

Abstract: We focus on entropy as a measure of risk and what role it can play in equilibrium asset pricing. Similar to the traditionally used capital asset pricing model (CAPM), the entropy can also be divided into mutual (a measure of the non-diversifiable risk) and conditional (a measure of the comovement with the market portfolio) components. We investigate what is the relationship between these and the conventionally used risk metrics, like standard deviation and Beta. We also propose a better solution to the notorious puzzles of asset pricing. Entropy as a measure of risk has been already described and its advantages in portfolio optimization and risk management are also acknowledged in the economic literature. We use data from the OpenBB database and Kenneth R. French’s data library to calculate daily returns and the various risk measures associated with them. We show the diversification effects of different risk measures and their stability over time. We introduce a new method to separate individual and systemic risks of the assets. We also validate our model using the conventional test of the CAPM model. Our regression-based results are tested both in-sample and out-of-sample. The robustness of our model is evaluated by both cross-validation and the use of the rolling windows over time.

Neelkamal Mallick [1], Suraj Prasad [1], Aditya Nath Mishra [2,4], Raghunath Sahoo [1] and Gergely Gábor Barnaföldi [3] (2023.01.01 - 2023.03.31)

[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

Publication: Deep learning predicted elliptic flow of identified particles in heavy-ion collisions at the RHIC and LHC energies

Abstract Recent developments of a deep learning feed-forward network for estimating elliptic flow \((v_2)\) coefficients in heavy-ion collisions have shown the prediction power of this technique. The success of the model is mainly the estimation of \(v_2\) from final-state particle kinematic information and learning the centrality and transverse momentum \((p_T)\) dependence of \(v_2\). The deep learning model is trained with Pb-Pb collisions at \(\sqrt{s_{NN}} = 5.02 TeV\) minimum bias events simulated with a multiphase transport model. We extend this work to estimate \(v_2\) for light-flavor identified particles such as \(π^\pm\), \(K^\pm\), and \(p + \bar{p}\) in heavy-ion collisions at RHIC and LHC energies. The number-of-constituent-quark scaling is also shown. The evolution of the \(p_T\)-crossing point of \(v_2(p_T)\), depicting a change in baryon-meson elliptic flow at intermediate \(p_T\) , is studied for various collision systems and energies. The model is further evaluated by training it for different \(p_T\) regions. These results are compared with the available experimental data wherever possible.

Antal Jakovác, Anna Horváth, Bence Dudás

Abstract: Infrasound sample analysis using artificial intelligence methods for applied research.