News

Introducing the academy candidates in physics

2025. March 13.

Ferenc Simon, Gábor Takács, and Levente Tapasztó, candidates for membership of the Hungarian Academy of Sciences, publish outreach articles in a special issue of Fizikai Szemle. All thre articles (in Hungarian) are freely available from the website of the March issue of Fizikai Szemle.

 

Ferenc Simon (professor, BME Faculty of Natural Sciences, Institute of Physics, Department of Physics)
Spintronics: Introduction and applications

 

Gábor Takács (professor, head of institute, BME Faculty of Natural Sciences, Institute of Physics, Department of Theoretical Physics)
Do closed quantum systems achieve balance? – When the “light cone” closes

 

Levente Tapasztó (scientific advisor, HUN-REN EK; research professor, BME Faculty of Natural Sciences)
Light trapped in graphene

 

Link: 
https://fizikaiszemle.elft.hu/szemle/138

Popular article on the 2024 physics Nobel prize

2025. February 02.

Popular article from BME researchers on the 2024 physics Nobel prize and related memristor applications published in the January issue of Fizikai Szemle.

 

Fehérvári János Gergő, Balogh Zoltán, Halbritter András Ernő
Neuromorphic computing, or how to turn the 2024 Nobel Prize in Physics into change?
Fizikai Szemle, January 2025, p 13-19

 

The Hungarian version of the article is available for free on the website of Fizikai Szemle.

 

 

 

Link: 
https://fizikaiszemle.elft.hu/szemle/136

Interview with Nándor Bokor

2025. January 07.

Nándor Bokor, associate professor at the BME Institute of Physics, discusses foundations and applications of general relativity in an interview published at index.hu.

 

The interview in Hungarian: https://index.hu/tudomany/2025/01/04/bokor-nandor-relativitas-elmelet-bm...

 

Spacetime-geometry, a popular book (in Hungarian) by Nándor Bokor: https://www.typotex.hu/book/13506/bokor_nandor_terido-geometria

 

Link: 
https://index.hu/tudomany/2025/01/04/bokor-nandor-relativitas-elmelet-bme-fizika-ter-ido-geometria/

Quantum Technology in the Institute of Physics

2024. December 12.

Thanks to a major HUN-REN research grant awarded yesterday, a new Quantum Technology Research Group will be launched on January 1st, 2025, at the BME Institute of Physics. The three-year project has a funding amount of cca. 180 million HUF. Research will be led by András Pályi, associate professor of BME Department of Theoretical Physics, in collaboration with numerous researchers of the department, as well as with Miklós Pintér, professor at the Corvinus University of Budapest. 

 

Results of the call at the HUN-REN webpage (in Hungarian): https://hun-ren.hu/hirek/6-palyazat-reszesul-tamogatasban-a-hun-ren-kozp...

 

Link: 
https://hun-ren.hu/hirek/6-palyazat-reszesul-tamogatasban-a-hun-ren-kozpont-altal-meghirdetett-tamogatott

How does a superconducting transistor work?

2024. October 31.

Experiments of the Nanoelectronics Research Group at the BME Institute of Physics reveal the switching mechanism of superconducting transistors. Published in Nature Communications.

 

Detailed report at the university news portal bme.hu, in Hungarian.

 
Tosson Elalaily, Martin Berke, Ilari Lilja, Alexander Savin, Gergő Fülöp, Lőrinc Kupás, Thomas Kanne, Jesper Nygård, Péter Makk, Pertti Hakonen & Szabolcs Csonka 
Switching dynamics in Al/InAs nanowire-based gate-controlled superconducting switch
Nature Communications 15, 9157 (2024)
 
A recent review paper of this research field, co-authored by BME researchers:
Leon Ruf, Claudio Puglia, Tosson Elalaily, Giorgio De Simoni, Francois Joint, Martin Berke, Jennifer Koch, Andrea Iorio, Sara Khorshidian, Peter Makk, Simone Gasparinetti, Szabolcs Csonka, Wolfgang Belzig, Mario Cuoco, Francesco Giazotto, Elke Scheer, Angelo Di Bernardo
Gate control of superconducting current: Mechanisms, parameters and technological potential
https://arxiv.org/abs/2302.13734

 

Link: 
https://www.bme.hu/hirek/241029/bme-ttk-fizika-tanszek-kutatas-szupravezeto-tranzisztorok

Physics Nobel Prize for neural networks

2024. October 09.

In 2024, the Nobel Prize in Physics was awarded to American physicist John J. Hopfield and British-Canadian computer scientist Geoffrey E. Hinton, for their discoveries that enable machine learning with artificial neural networks.
 
This might sound surprising, since machine learning belongs more to the field of computer science than to physics. This contradiction is resolved by the fact that the award-winning artificial neural networks were inspired by statistical physical models. Hopfield created his memory model based on one of the simplest and most-studied statistical physics model, the so-called Ising model. The thorough understanding of Hopfield's results was made possible by methods developed in the theory of spin glasses. Hinton developed a stochastic extension of Hopfield's model, in which another cornerstone of statistical physics, the Boltzmann distribution, plays the key role.
 
Physics was not only an inspiration for creating these machine learning models, but also relies on them in applications. "The laureates’ work has already been of the greatest benefit. In physics we use artificial neural networks in a vast range of areas, such as developing new materials with specific properties,” says Ellen Moons, Chair of the Nobel Committee for Physics.
 
Statistical phyiscs as well as machine learning plays a pivotal role BME's physics BSc, physicist-engineer BSc, and physicist MSc training, e.g., in the form of the courses Statistical Physics 1 and 2, Physics of Disordered Systems, Introduction to Machine Learning, and Artificial Intellingence in Data Science. Researchers of BME Institute of Physics apply and develop methods of machine learning: an application example is a neural-network-based method for malaria diagnostics, and a development example is the realistic simulation of a memristor-based Hopfield neural network. 
 
Press release on the webpage of the Nobel Prize: https://www.nobelprize.org/prizes/physics/2024/summary/ 
 
Link: 
https://www.nobelprize.org/prizes/physics/2024/summary/

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