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Dr Gergely Barnafoldi (HUN-REN Wigner Reseach Centre for Physics), Roland Jakab (HUN-REN)28/05/2026, 09:00
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Örs Legeza (Wigner FK)28/05/2026, 09:20
In light of emergent evolution in quantum technology, key industrial players allocate significant parts of their budget and resources to identify a real-world problem where quantum advantage, i.e. exponential increase in computational capacity, is expected to appear. The tense competition between quantum computing and simulations on classical hardware over the past decades has been further...
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Bálint Soproni (StreamHPC)28/05/2026, 09:50
The SYCL specification allows for multiple implementation strategies, in particular SSCP (single-source, single compiler pass) and SMCP (single-source, multiple compiler passes). The default compiler of the AdaptiveCpp SYCL implementation is an SSCP JIT compiler, which has previously been shown to deliver substantial speedups for certain applications, while also reducing compilation times....
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Nara Prasetya (StreamHPC)28/05/2026, 10:50
The performance of a GPU kernel is influenced by many factors, with some easier to change than others. In some cases, however, the resulting performance is beholden to the compiler. In this presentation we will go over a set of kernel optimization techniques that go beyond profiling and reducing memory bottlenecks, but instead focus on the analysis of AMDGCN assembly, reducing register...
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28/05/2026, 11:20
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Geza Odor (HUN-REN Centre for Energy Research)28/05/2026, 11:50Lecture
The critical brain hypothesis has been confirmed experimentally many times since the pioneering electrode experiments. Power law (PL) distributed neuronal avalanches were shown in neuronal recordings, in blood-oxygen-level-dependent signals,in voltage imaging, in calcium-imaging, in MEG and EEG recordings and in neuronal long-range temporal correlation among others. Whole brain simulations,...
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Kristóf Benedek (Budapest University of Technology and Economics)28/05/2026, 12:10Lecture
Power grids are large-scale engineered systems that are indispensable to modern society, yet they remain inherently vulnerable to disturbances. Ongoing transitions in the energy sector—particularly the increasing penetration of renewable sources and inverter-based technologies—introduce new challenges, including reduced system inertia and faster propagation of fluctuations. As many emerging...
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Zsófia Jólesz28/05/2026, 14:00Lecture
The use of hadrons - such as protons, helium, and carbon ions—in radiotherapy requires highly precise Relative Stopping Power (RSP) maps of patient anatomy to minimize range uncertainties. Using the aforementioned hadrons for imaging before the treatment offers higher reconstruction quality and dosimetric advantage in comparison to conventional X-ray CT for this purpose. However, executing the...
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Bence Dudás (Eötvös Loránd University)28/05/2026, 14:20
FLORA: Flow-based Latent-informed Optimization for 3D proton-CT Reconstruction with Spatial Attention. A deep learning framework for conditioned image reconstruction developed for Proton Computed Tomography (pCT). The pipeline utilizes a Varriational Autoencoder-GAN approach to be able to learn biologically correct 3D CT reconstruction, while the latent Flow-matching enables us to condition in...
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Regina Nora Fiam (Eötvös Loránd University)28/05/2026, 14:40
Learning counterfactual representations for cellular perturbations is a fundamental challenge in representation learning, significantly hindered by the fundamentally unpaired nature of interventional data. Current state-of-the-art generative approaches (e.g., GEARS) circumvent this by relying heavily on domain-specific heuristics, such as masking the input space to a subset of highly variable...
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Péter Hunyadi (Pázmány Péter University, Faculty of Information Technology and Bionics)28/05/2026, 15:00Lecture
In most types of cancer, immunosuppression limits an effective anti-cancer immune response. Leukocyte immunoglobulin-like receptor B4 (LILRB4) is an immune checkpoint inhibitor molecule that plays a role in various signaling processes contributing to tumor immune evasion. The aim of our research is to investigate this receptor and its family in colorectal cancer, with a particular focus on the...
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Zoltan Juhasz (Pannon Egyetem)28/05/2026, 15:50Lecture
In this talk, we plan to report the results of our performance optimisation effort aimed at speeding up a GPU-accelerated 2D Particle-in-Cell plasma simulation code, following an international plasma simulation benchmarking effort of 19 leading plasma research groups. We studied the effects of memory management, data movements, the choice and implementation of the Poisson solver, the use of...
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Bálint Tóth (University of Pannonia)28/05/2026, 16:10Lecture
Particle-in-Cell (PIC) simulation is an important tool in plasma science, where certain properties and behaviour can only be examined by simulations. Due to the large number of particles and simulation cycles, these simulations are extremely time-consuming and can be executed in acceptable time only with parallel implementations. A crucial step in the simulation is solving the Poisson equation...
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Suraj Prasad (HUN-REN Wigner Research Centre for Physics)28/05/2026, 16:30Lecture
One of the major open problems in the collider physics community is understanding the onset of quark–gluon plasma (QGP) signatures. Collisions of Oxygen nuclei provide a golden opportunity to probe the emergence of collective phenomena in collider experiments. Additionally, $^{16}$O nuclei are theorized to possess a clustered nuclear structure, where α-particles occupy the corners of a regular...
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28/05/2026, 16:50
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Anisa Khatun28/05/2026, 17:10Lecture
Modern high-energy physics analyses rely heavily on large-scale Monte Carlo (MC)
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simulations for machine-learning training, efficiency corrections, and systematic
studies. For rare-signal workflows, obtaining sufficiently large reconstructed-level
signal samples often require computationally expensive MC campaigns with large
CPU and storage demands.
This work explores the use of... -
Bence Bakó (Wigner RCP)29/05/2026, 09:00
Quantum generative learning is a promising application of quantum computers, but faces several trainability challenges, including the difficulty in experimental gradient estimations. For certain structured quantum generative models, however, expectation values of local observables can be efficiently computed on a classical computer, enabling fully classical training without quantum gradient...
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Zoltán Kolarovszki29/05/2026, 09:20
Quantum generative modeling has emerged as a promising application of quantum computers, aiming to model complex probability distributions beyond the reach of classical methods. In practice, however, training such models often requires costly gradient estimation performed directly on the quantum hardware. Crucially, for certain structured quantum circuits, expectation values of local...
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Gregory Morse (Eötvös Loránd University and Wigner RCP)29/05/2026, 09:40Lecture
Quantum circuit decomposition under restricted hardware connectivity is fundamentally a search problem: the compiler must choose useful qubit partitions, map them to a target topology, and synthesize high-quality local decompositions without exploding routing cost. This talk presents two complementary advances for connectivity-aware quantum compilation. First, we introduce an all-partitions...
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Peter Rakyta (Department of Physics of Complex Systems, Eötvös Loránd University)29/05/2026, 10:00Lecture
This project develops a hardware-accelerated, low-latency inference framework for real-time denoising and signal reconstruction in high-throughput, noise-limited measurement systems. While motivated by X-ray Free Electron Laser (XFEL) imaging, the proposed approach is designed to be broadly applicable to a wide range of data-intensive scientific and industrial domains, including plasma...
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Szabolcs Molnár (HUN-REN Wigner RCP)29/05/2026, 10:50
Tuning a Monte Carlo Event Generator requires many tools and a lot of en-
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ergy. For demonstrating what can be achieved with a toolbox—that contains all
of the required packages and dependencies to work out-of-the-box—HIJING++
is a perfect candidate for tuning. The tools—by default—can only be installed
separately and maintaining them one-by-one is a tedious task. The toolbox in
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Péter Naszvadi (Wigner RCP)29/05/2026, 11:10
In a recent work (Naszvadi, Adam and Koniorczyk, Mathematics 2025, 13(16), 2633) we have introduced an ILP model for solving the code-theoretic problem of finding the maximal cardinality of codes with a minimum codeword Hamming distance. Our method is not based on algebraic structure of the alphabets, it is suitable for decomposing bigger problem instances into equivalent smaller ones, and can...
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Prof. Gabor Vattay (Eötvös Loránd University)29/05/2026, 11:30Lecture
We present a cohesive framework for simulating seismic wave propagation utilizing quantum computing paradigms and their classical tensor network equivalents.
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We detail a quantum circuit-based formulation for the explicit finite-difference time-domain (FDTD) solution of the two-dimensional acoustic wave equation and
map this quantum architecture onto a tensor train representation, namely... -
Antal Jakovac (Wigner RCP, Department of Computational Sciences)29/05/2026, 11:50Lecture
We introduce a minimal structural framework for cognitive representations based on the notion of context as a partition of the world state space. The framework treats invariance recognition and representative selection as fundamental operations and realizes them through a coupled Concept Graph and Procedure Graph. Together, these define a minimal cognitive algebra for constructing and...
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Attila Czirják (ELI-ALPS, and University of Szeged)29/05/2026, 12:10Lecture
We numerically investigate high-order harmonic generation (HHG) in a noble gas jet or cell with a supercomputer code [1] which computes the single atom response based on the one-dimensional (1D) time-dependent Schrödinger equation (TDSE) and couples it to the macroscopic propagation of the electromagnetic radiation, thus it enables to compare 1D TDSE-based HHG simulations with experimental...
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Balázs Pál (Wigner Research Centre for Physics)29/05/2026, 14:00
Cosmological N-body simulations are fundamental tools for studying the non-linear evolution of large-scale structure, yet the vast majority adopt periodic cubic ($\mathbb{T}^3$) boundary conditions. This choice breaks rotational invariance, prevents angular momentum conservation, and introduces artificial correlations at scales comparable to the box size. The StePS simulation framework and its...
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Ms Ashika Achuthankutty (University of Szeged)29/05/2026, 14:20Lecture
Scalar-tensor theories of gravity with a dynamical scalar field coupling non-minimally to matter via a conformal factor $A(\phi)$ pose computational challenges beyond standard general relativistic solvers. We present a fully numerical Python framework for constructing slowly rotating neutron star solutions in the massive scalar-tensor theory defined by the Einstein-frame coupling $\alpha(\phi)...
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Franciska Sprok (HUN-REN Wigner FK)29/05/2026, 14:40
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Andras Horvath (Pázmány Péter Catholic University - Faculty of Information Technology and Bionics), Gábor János Tornai (StreamNovation Ltd.)29/05/2026, 15:00Lecture
Self-consistent field (SCF) calculations remain the computational bottleneck in quantum chemistry workflows. The initial density matrix guess significantly impacts convergence speed, with the Superposition of Atomic Densities (SAD) being the de facto standard. We present a machine learning approach that achieves comparable performance to SAD using a remarkably compact model predicting only...
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