Important breakthrough in quantum physics by Prof. Dr. Tomaž Prosen and a Google Lab Team

The research by Prof Prosen and his team sheds light on a totally new type of transport in quantum materials which lies somewhere between traditional diffusion and ideal ballistic transport. This work, which came about in collaboration with Google’s quantum computing group, is based on simulations of the dynamics of the Heisenberg spin chain using a digital quantum computer. The results confirmed earlier theoretical predictions by Prof Prosen and his colleagues at UL FMF and, at the same time, revealed surprising new phenomena that point to the existence of a new universal class of nonequilibrium statistical physics.

This is one of the first genuinely useful quantum simulations of new, nonequilibrium quantum transport phenomena. A universal digital quantum computer, using 46 superconducting qubits, simulates the dynamics of a multi-body quantum magnet with almost negligible errors. The result partly surpasses state-of-the-art traditional computers and represents the first empirical evidence for a new universality class of quantum transport.

“Our research opens new doors in the understanding of quantum transport phenomena. I am proud of the collaboration with colleagues at the University of Ljubljana that has led to this achievement, and of Google’s Quantum AI team, since together we have gone beyond the traditional boundaries of knowledge. This achievement not only signifies progress in physics, it confirms the potential of quantum simulations for the resolution of complex scientific questions,” said the article’s lead author, Prof Tomaž Prosen.

Harvard University physics professor Subir Sachdev offered the following comment on the discovery: “Quantum computers have great potential for describing the quantum dynamics of many-body systems in regimes that are inaccessible to traditional computers. Deeper understanding of quantum dynamics is the key to numerous fundamental problems in physics, as well as a number of technologically important problems, from superconductors at higher temperatures to the insides of black holes. In this article, a team from Google’s Quantum AI lab and external collaborators have clearly demonstrated the usefulness of quantum computers and shown how a chain of 46 superconducting qubits has a totally new regime of quantum dynamics not conjectured either by theory or by traditional computers.”

Gregor Majdič, rector of the University of Ljubljana, offered this reflection on the achievement: “Publications by our researchers in a prestigious scientific journal such as Science represent a key pillar in the construction and consolidation of the international reputation of the University of Ljubljana. Such publications are not only proof of the outstanding quality and innovativeness of the work done by our research teams, they are also the foundation for raising the profile of our university at the global level. This is a sign that the University of Ljubljana is a place of scientific excellence that attracts top talents and opens its doors to international research and academic collaborations. Articles in such important publications also stimulate innovation and technological progress, both of which have a broad social and economic impact.”

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Q&A: Dynamics of magnetization at infinite temperature in a Heisenberg spin chain 

The article appeared in the 5 April 2024 issue of Science 

What achievement does the article published in this prestigious scientific journal represent?
A few years ago the research groups of Prof Tomaž Prosen and Prof Marko Žnidarič at UL FMF theoretically predicted a completely new type of transport that can be observed in specific quantum materials and is somewhere between diffusion or Ohm’s law and ideal, i.e. ballistic, transport. Further research, conducted by numerous groups around the world, hinted at a universal behaviour described by the famous equation of Kardar, Parisi and Zhang (known as the KPZ equation). This equation, surprisingly, essentially describes many different phenomena, such as random surface growth, the statistical physics of polymers, or even traffic. The new research, the fruit of a collaboration between Prof Prosen and Google’s quantum computing group, used a digital quantum computer to simulate the dynamics of a Heisenberg spin chain. On the one hand, the research confirmed the earlier predictions of the KPZ equation for average transport quantities, while on the other, surprisingly, it confirmed recent conjectures (again from the same group at UL FMF) that fluctuations (statistical fluctuations around the average) behave completely differently from the manner predicted by the KPZ equation. Thus a digital quantum computer has helped obtain evidence for a conjectured new universality class of nonequilibrium statistical physics. The article appeared in the 5 April 2024 edition of Science.

What does this achievement represent for the field of quantum computing? How important is the position occupied by UL FMF in research in this field at the global level?
Over the last two years we have seen remarkable progress in the field of quantum simulations of many-body quantum systems. The latter are extremely difficult to simulate using normal, traditional supercomputers. Quantum simulations, even using existing technology, which we call NISQ (noisy intermediate scale quantum), are progressing in leaps and bounds and, despite the fact that we are not yet in an era of so-called fault-tolerant quantum computing, already present specific advantages in comparison to traditional simulations. The research conducted by UL FMF in collaboration with Google Quantum AI represents an important breakthrough achievement in this direction.

How did this collaboration with researchers at Google in the USA come about? What were the research goals of this collaboration?
Two years ago Prof Tomaž Prosen met one of the leaders of Google’s quantum computing team at a conference in Oxford and almost immediately got him interested in a research proposal. The idea was one that was perfect for Google’s hardware. This first idea and discussion were followed by the formal phase of a project proposal, which was quickly accepted by a specific research group at Google Quantum AI, which then got to work.

What was Prof Prosen’s role in this collaboration?
Prof Prosen is one of the two lead (corresponding) authors of the research and is responsible for the theoretical part. In practice, this meant numerous Zoom meetings with the experimental part of the Google Quantum AI research group based in Santa Barbara (USA), where interpretations of the enormous quantity of data produced by the quantum simulator crystallised.

For more information, click here.

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Professor Tomaž Prosen is an internationally renowned physicist specialising in the study of exactly solvable models, particularly quantum chaos in the context of many-body quantum systems. He is known for his research into the dynamics of spin chains and qubit circuits with local interactions, where he studies models that explain phenomena in these complex systems. In his research, Prof Prosen has introduced a self-dual kicked Ising model, which enables the direct calculation of spectral correlations without assumptions, and identified mechanisms that explain the success of the theory of random matrix ensembles in many-body quantum systems. His work has contributed to understanding of dynamic properties in quantum physics and has been of key importance for the global progress of research in this field. Prof Prosen is the only Slovenian researcher to have twice obtained funding from the European Research Council (ERC) with projects for established researchers (Advanced Grant) – in 2016 and 2023. These projects represent the European research community’s recognition of his influential contribution to science and are proof of his leading position in the international scientific community and his breakthrough achievements in quantum physics. Last year he received the Blinc Award for Outstanding Singular Achievements.

Photograph: Prof Tomaž Prosen by Peter Irman

Link to the article: https://www.science.org/doi/10.1126/science.adi7877 

or https://arxiv.org/pdf/2306.09333.pdf.