Péter Rakyta, Zoltán Zimborás (2022.01.01 - 2022.06.31)

Eötvös University, Wigner Research Centre for Physics

Grant: NKFIH 2020-2.1.1-ED-2021-00179

Abstract: In this work we propose a novel numerical approach to decompose general quantum programs in terms of single- and two-qubit quantum gates with a CNOT gate count very close to the current theoretical lower bounds. In particular, it turns out that 15 and 63 CNOT gates are sufficient to decompose a general 3 and 4-qubit unitary, respectively, with high numerical accuracy. Our approach is based on a sequential optimization of parameters related to the single-qubit rotation gates involved in a pre-designed quantum circuit used for the decomposition. In addition, the algorithm can be adopted to sparse inter-qubit connectivity architectures provided by current mid-scale quantum computers, needing only a few additional CNOT gates to be implemented in the resulting quantum circuits.

Publications:
[1] Péter Rakyta, Zoltán Zimborás: Approaching the theoretical limit in quantum gate decomposition, Quantum 6 (2022) 710
DOI: 10.22331/q-2022-05-11-710

Gábor Tolnai, Dávid Légrády (2022.08.01 - 2022.12.31)

Budapest University of Technology and Economics

Publication: Adjoint-based Path Length Stretching in a Woodcock Framework with SIR Angular Biasing

Grant: NKFIH 2020-2.1.1-ED-2021-00179

Kivonat: The GUARDYAN (GPU Assisted Reactor Dynamic Analysis) code developed at the Budapest University of Technology and Economics Institute of Nuclear Techniques directly models the time-dependent phenomena occurring in nuclear reactors. In contrast to conventional reactor dynamics modelling methods, GUARDYAN applies little to no approximations at simulating the physical processes. Price to pay for ultimate accuracy is running time, a real second translates to 6-24h calculation time depending on the complexity of the reactor geometry.

This project aims at increasing the computation efficiency by applying variance reduction techniques. This is done by the importance (a.k.a. the adjoint) function used for biasing the interaction laws, for which calculation schemes are being developed in the form of nonanalog Woodcock tracking for free path sampling and scouting samples (sampling importance resampling - SIRS ) for the angular bias.

An accurately pre-calculated adjoint function is needed for the proper biasing, this is computed by GUARDYAN specifically for the problem at hand. Large computation effort is needed for producing the sufficiently detailed adjoint for a certain problem, but it can be used for the whole transient scenario. For demonstrating the usefulness of the new variance reduction scheme under development, several test cases of varying complexity should be analysed and the corresponding adjoint function generated demanding large GPU capacity.

Péter Rakyta, Zoltán Zimborás (2022.01.01 - 2022.06.31)

Eötvös University, Wigner Research Centre for Physics

Grant: NKFIH 2020-2.1.1-ED-2021-00179

Abstract: In this work, we report on a novel quantum gate approximation algorithm based on the application of parametric two-qubit gates in the synthesis process. The utilization of these parametric two-qubit gates in the circuit design allows us to transform the discrete combinatorial problem of circuit synthesis into an optimization problem over continuous variables. The circuit is then compressed by a sequential removal of two-qubit gates from the design, while the remaining building blocks are continuously adapted to the reduced gate structure by iterated learning cycles. We implemented the developed algorithm in the SQUANDER software package and benchmarked it against several state-of-the-art quantum gate synthesis tools. Our numerical experiments revealed outstanding circuit compression capabilities of our compilation algorithm providing the most optimal gate count in the majority of the addressed quantum circuits.

Publications: Efficient quantum gate decomposition via adaptive circuit compression

Kővári Emese, Kovács Tamás, Forgács-Dajka Emese (2022.01.01 - 2022.03.30)

Eötvös Loránd University, Center for Astrophysics and Space Science

Grant: NKFIH 2020-2.1.1-ED-2021-00179

Abstract: The trans-Neptunian space is of great interest of dynamical studies with an inexhaustible number of intriguing problems to be solved. Our aim is to carry out a large-scale survey of trans-Neptunian objects (TNOs) by means of dynamical maps. In the first part of the research, we concentrate on the dynamical role of mean-motion resonances (MMRs) among the TNOs, and the tools of understanding are dynamical maps of classical chaos indicators. In the second part, our focus becomes the quantification of the chaotic diffusion and that of the stability times of the small bodies. The chaotic diffusion is of fundamental importance for its rate will determine the long-term dynamics of a given celestial system. To estimate the rate of the diffusion (that is, to compute the diffusion coefficients) in the case of the 4125 TNOs selected in the first part of our study, we initiate the use of the Shannon entropy. This latter quantity allows, on the one hand, to measure the extent of unstable regions in the phase space (and thus serves as an indicator of chaos), and also enables the direct measurement of the diffusion coefficients. The characteristic times of stability - in the case of normal diffusion - are then achieved by taking the inverse of the diffusion coefficients. In the knowledge of the chaotic diffusion and stability times for as large a TNO sample as the one indicated above, the overall structure of the trans-Neptunian space might be mapped as well, along with the specification of dynamical classes or the update of the existing ones.

Eduárd Zsurka, Noel Plaszkó, Péter Rakyta, Andor Kormányos (2022.05.01 - 2022.11.31)

Eötvös Loránd University

Publication: Non-local Andreev reflection through Andreev molecular states in graphene Josephson junctions

Grant: NKFIH 2020-2.1.1-ED-2021-00179

Abstract: We propose that a device composed of two vertically stacked monolayer graphene Josephson junctions can be used for Cooper pair splitting. The hybridization of the Andreev bound states of the two Josephson junction can facilitate non-local transport in this normal-superconductor hybrid structure, which we study by calculating the non-local differential conductance. Assuming that one of the graphene layers is electron and the other is hole doped, we find that the non-local Andreev reflection can dominate the differential conductance of the system. Our setup does not require the precise control of junction length, doping, or superconducting phase difference, which could be an important advantage for experimental realization.

Mira Anna Gergácz, Ákos Keresztúri (2022.08.31-12.31)

Publication: Melting possibility of remnant seasonal water ice patches on Mars

Grant: NKFIH 2020-2.1.1-ED-2021-00179

Abstract: Due to the low thermal conductivity of the Martian surface and atmosphere, it is possible that after the recession of the seasonal polar icecap, small icy patches left behind in shady places might be met by direct sunlight during the summer. This work surveyed such frost patches using HiRISE images. Analyzing 110 images out of the available 1400 pieces that fit the selection criteria of location and season, and identified 37 images with smaller ice patches on them. These areas range between 140° and 200° solar longitude in the central latitude band between -40° and -60°. The diameter of the ice patches ranges between 1.5-300 meters, and remains on the surface even after the seasonal polar cap has passed over the area for the duration range of 19-133 martian days.

With the help of The Mars Climate Database (MCD) we simulated the surface temperature and predicted CO2 and H2O ice cover at 22 analyzed areas. Judging by the models, the average noon temperature does not reach the melting point of water, which is 273 K, therefore the occurrence of liquid water on the macroscopic scale is highly unlikely, however there is a possibility that an interfacial premelting of ice (a few nanometers thick waterlayer) might form between the layered and the water ice.

Sudár Ákos, Varga-Kőfaragó Mónika, Barnaföldi Gergely Gábor és Légrády Dávid (2021.07.01 - 2022.08.31)

Wigner Research Centre for Physics és BME Institute of Nuclear Techniques

Grant: NKFIH 2020-2.1.1-ED-2021-00179

Abstract: The goal of development of proton computed tomography is the accurate measurement of the relative stopping power (RSP) distribution of the patient, which is necessary to reduce safety zones around the tumor in proton therapy. During the pCT imaging the patient is imaged by protons, which has determined direction and energy before they go into the patient, and their direction and energy is measured after they come out of the patient. From this information the most likely path (MLP) and the energy deposition in the patient can be determined. The 3D image is reconstructed from the measured data with the use of order suppressed expectation maximalization (OSEM) algorithm, which is an accelerated version of maximum likelihood expectation maximalization (ML-EM) algorithm. The goal of the current project is to develop an image reconstruction code, which runs in parallel threads of CPU and use GPU as well to minimize the image reconstruction time. This software will be used in the future to reconstruct the measured data of a pCT detector developed by the Bergen pCT Collaboration. This work would be contribution to the work of the group and their later publications.

Kacskovics Balázs[1,2] and Barta Dániel[1] (2023.2.13 - 8.15)

[1] Wigner Research Centre for Physics
[2] PTE Doctoral School of Physics

Abstract: We are modeling equilibrium configurations of rapidly rotating compact stars for various equation of states (EOS) including nuclear, hybrid and quark matter models. Apart from angular momentum we also will include into our investigation the temperature to go beyond the scope of cold-matter EOSs. In order to find a common ground with gravitational-wave observations we will compute the tidal Love-numbers of such stars. The physical parameters are determined by simulations written in the LORENE code library, which applies multi-domain spectral methods for numerically solving the 3+1 decomposition of Einstein equations.

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.

Bedőházi Zsolt[1,2] and Biricz András[1] (2023.02.13 - 05.15)

[1] ELTE Department of Complex Systems in Physics
[2] ELTE Doctoral School of Informatics

Abstract: The application of deep learning in gigapixel whole slide image analysis has shown promising results in terms of accuracy and efficiency compared to traditional image analysis techniques. Transformer based models as the current state-of-the-art algorithms are designed to identify and classify various structures and patterns within the tissue, providing insights into the underlying pathology and helping in the diagnosis and treatment of diseases. We are currently working on multiple projects in this field including breast cancer stage prediction [1] and colorectal cancer detection [2].

István Csabai, Ákos Gellért, Balázs Pál (2022.01.01 - 2022.03.30)

ELTE Department of Physics of Complex Systems

Publication: SARS-CoV-2 RBD deep mutational AlphaFold2 structures carry phenotypic information

Abstract: 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 prevention of similar pandemics. The GISAID and COVID-19 Data Portal databases contain millions of complete SARS-CoV-2 genomes. The genetic sequences can be obtained relatively easily and quickly thanks to modern genome sequencers, but it is very difficult to tell how rapidly a given variant will spread or how serious disease will it cause, solely based on the genetic sequences and the mutations. The genetic information is transcribed into proteins, and the spatial structure, charge distribution and interaction of the proteins with the host proteins determine the function of the virus, the so called phenotype. In summary, the genotype-phenotype problem is the estimation of the behaviour of a virus based on genetic information.

In the last year, the rapidly developing artificial intelligence approach has achieved a milestone that can significantly help genotype-phenotype research. Using the Alphafold2 method, the spatial structure of large proteins can be determined with sufficient accuracy in a reasonable time. The machine learning-based Alphafold2 method requires significant computational, mainly GPU, capacity.

We are collaborating with EMBL-EBI on the development of a SARS-CoV-2 genetic archive in the framework of a H2020 project. We aim to complement this with 3D structures of proteins of as many variants as possible and to use these structures to advance the genotype-phenotype question.

Andor Menczer (ELTE), Áron Vízkeleti (Wigner RCP), Mihály Máté (Wigner RCP) and Örs Legeza (Wigner RCP) - (2022.09.01 - 2022.11.30)

Abstract: Numerical simulation of quantum systems where strong interaction between atomic spins and itinerant electrons is present, and at the same time cannot be described with perturbative methods are in the focus of modern physics. These simulations are challenging because computational resources, in general, scale exponentially with system size. Developing algorithms to simulate these systems with polynomial complexity is one of the most heavily researched subjects today.

The density-matrix renormalization group (DMRG) algorithm is one such method, with the additional advantage that the underlying tensor algebra, in light of the conserved quantum numbers, can be broken up into millions of independent tasks. This makes this algorithm ideal for MPI and GPU based massive parallelization. Our research group have been researching the subject for two decades. A GPU based kernel application have been implemented recently thanks to Andor Menczer (ELTE graduate student). In this project we would like to test, and based on the results, optimize this application. At the same time, we would also like to apply it to two-dimensional electron systems, strongly correlated molecular clusters, and atomic nuclei.

The project involves Andor Menczer (ELTE), Áron Vízkeleti (WignerFK), Mihály Máté (WignerFK) and Örs Legeza (WignerFK). The source code was written in Matlab, and a standalone version was compiled using Matlab Compiler. We wish to carry out the testing, fine-tuning and application to large systems in steps. The GPU kernel was built using the Matlab Paralelization Toolbox, and CODA Coder. For the first step, we would like to ask for a three months long interval of access to one of the nodes (cluster 1, 2, 3, 4) that access NVIDIA graphics cards.

We plan to publish the simulation results in prestigious international journals, like the ones our previous work appeared in [1,2]

[1] The density matrix renormalization group algorithm on kilo-processor architectures: implementation and trade-offs, Csaba Nemes, Gergely Barcza, Zoltán Nagy, Örs Legeza, Péter Szolgay, Computer Physics Communications Volume 185, Issue 6, June 2014, Pages 1570-1581

[2] Massively parallel quantum chemical density matrix renormalization group method, Jiří Brabec, Jan Brandejs, Karol Kowalski, Sotiris Xantheas, Örs Legeza, Libor Veis, Computational Chemistry, https://doi.org/10.1002/jcc.26476

István Papp, Larissa Bravina, Mária Csete, Igor N. Mishustin, Dénes Molnár, Anton Motornenko, Leonid M. Satarov, Horst Stöcker, Daniel D. Strottman, András Szenes, Dávid Vass, Tamás S. Biró, László P. Csernai, Norbert Kroó (2022.01.01 - 2022.06.30)

Publication: Laser Wake Field Collider

Abstract: Inertial Confinement Fusion is a promising option to provide massive, clean, and affordable energy for humanity in the future. The present status of research and development is hindered by hydrodynamic instabilities occurring at the intense compression of the target fuel by energetic laser beams. NAno-Plasmonic, Laser Inertial Fusion Experiments (NAPLIFE) were proposed, as an improved way to achieve laser driven fusion. The improvement is the combination of two basic research discoveries:
(i) The possibility of detonations on space-time hyper-surfaces with time-like normal (i.e. simultaneous detonation in a whole volume)[1] and
(ii) to increase this volume to the whole target, by regulating the laser light absorption using nano-shells or nano-rods as antennas [2].
These principles can be realized in an in-line, one dimensional configuration, in the simplest way with two opposing laser beams as in particle colliders [3]. Such, opposing laser beam experiments were also performed recently. Here we study the consequences of the Laser Wake Field Acceleration (LWFA) if we experience it in a colliding laser beam set up. These studies can be applied to laser driven fusion, but also to other rapid phase transition, combustion, or ignition studies in other materials.

References:
[1] L. P. Csernai and D. D. Strottman, “Volume ignition via time-like detonation in pellet fusion,” Laser Part. Beams. 33 (2), 279--282 (2015).
[2] L. P. Csernai, N. Kroo, and I. Papp, “Radiation dominated implosion with nano--plasmonics,” Laser Part. Beams. 36 (2), 171--178 (2018).
[3] L.P Csernai, M. Csete, I.N. Mishustin, A. Motornenko, I. Papp, L.M. Starov, H. Stöcker, N. Kroó, "Radiation dominated implosion with flat target", Physics of Wave Phenomena, 2020, accepted for publication.

István Papp, Larissa Bravina, Mária Csete, Igor N. Mishustin, Dénes Molnár, Anton Motornenko, Leonid M. Satarov, Horst Stöcker, Daniel D. Strottman, András Szenes, Dávid Vass, Tamás S. Biró, László P. Csernai, Norbert Kroó (2022.07.01 - 2022.12.31)

Abstract: Our dependence on fossil fuels grew more and more in the last century and today we are urged to find alternative energy sources. Laser driven fusion is a promising option for clean and safe energy production. The most successful configuration up to now uses indirect drive, the thermal radiation coming from a cylindrical Hohlraum. After the target is compressed by the incoming light, it develops Rayleigh-Taylor instabilities. An ongoing activity at Wigner Research Centre’s Nanoplasmonic Laser Fusion National Laboratory (NAPLIFE) collaboration is aiming for improving the chances of fusion by high-power short laser pulses and target fabrication, combining recent discoveries in heavy-ion collisions and optics [1]. Our aim is studying in simulations the surface plasmonic effect of resonant gold nano-antennas in different monomer mediums. The monomer serves only experimental purposes, proving the effectiveness of the nanorods. The plasmonic effect is vital for the project, since it will be used to manipulate the target’s absorption properties. The different layers of monomers with different gold nanoparticle densities will be studied, taking into account the lifetime of plasmons using a kinetic plasma model for conducting electrons [2]. The results will be essencial for future experiments in ELI-ALPS Szeged laser facility.

[1] L.P Csernai, N. Kroo and I. Papp, Radiation dominated implosion with nanoplasmonics, Laser and Particle Beams, Volume 36, Issue 2, June 2018 , pp. 171-178

[2] I. Papp, L. Bravina, M. Csete, et al., Kinetic model evaluation of the resilience of plasmonic nanoantennas for laser-induced fusion, PRX Energy, Vol. 1, Iss. 2 (2022)

Ernő Dávid, Dávid El-Saig, Zoltán Lehóczky and Gergely Gábor Barnaföldi (2021.12.01 - 2022.08.31)

Wigner RCP and Lombiq Technologies Ltd. cooperation

Abstract: Hastlayer by Lombiq Technologies allows software developers of the .NET platform to utilize FPGAs as compute accelerators. It converts standard .NET constructs into equivalent hardware implementations, automatically enhancing the performance while lowering the power consumption of suitable algorithms. Developers keep writing .NET programs as usual, no hardware design knowledge is required.

Hastlayer needs dedicated firmware and software components for each supported hardware platforms. In collaboration with Wigner RC there are already several supported platforms (like Microsoft Catapult cards and the Xilinx Alveo FPGA card family). The aim of the next development phase is to enable Hastlayer support for embedded platforms like FPGA cards based on the Xilinx Zynq family members.

Wigner's task is to develop the necessary firmware framework to run the Hastlayer-generated hardware cores and if there is a need then customize the Linux operating system running on the embedded ARM CPU cores.

Marcell Stippinger, András Telcs (2022.01.01 - 2022.03.30)

Wigner Research Centre for Physics

Abstract: The aim of the project is to develop a framework in which causal connection between time series can be explored. The core concept of the project is the investigation of Markov properties of different conditioned time series. The core of the method is the collection of result of large amount of conditional independence tests. The results then lead to a simple conclusion via a simple decision tree.

Balázs Kacskovics (2016.09.01 - 21.05.31)

Supervisor: Mátyás Vasúth

Wigner Research Centre for Physics

Publication:The orbital evolution and gravitational waves of OJ 287 in the 4th post-Newtonian order

Abstract: Although gravitational waves have been detected in 2016 with GW150914, but there are still many exotic cases to discover, e.g. binaries with Zoom-Whirl orbits, Super Massive Black Holes, etc. To examine such cases the Wigner RCP Gravitational group developed a software called CBwaves , that we would like to upgrade with the fourth terms of the post-Newtonian formalism and with its Hamiltonian formalism. Also we would like to enchance the runime of our code using parallelism.