Symposium on Frontiers of Solid State Theory — Part 2

Scientist for all over the world gathered at MPI to discuss the research directions of solid state theoretical physics

June 24 -  the MPI FKF hosted the second part of the “Frontiers of Solid State Theory” symposium.
The event brought together leading international experts in theoretical solid state physics to discuss the frontiers of solid state theory research and its new challenges. 
The list of speakers included Mathias Scheurer (University of Stuttgart), Titus Neupert (University of Zurich), Angelika Knothe (University of Regensburg), Fabian Kugler (University of Cologne), Bingqing Cheng (University of California, Berkeley), Kevin Jablonka (FSU Jena), Johannes Margraf (University of Bayreuth), Oriana Diessel (Harvard University), and Chris Bartel (University of Minnesota).

New Frontiers: Quantum Materials and Artificial Intelligence

Where is research going? What is the future of solid state theory? 
One of the most interesting themes for researchers in this area is certainly quantum materials and their potential applications in modern technologies.
Theoretical physicists and chemists must focus on two main aspects. While studying fundamental phenomena, such as unconventional superconductivity and fractional quantum Hall states, they must also consider the practical aspects. For example, they must consider how to manipulate these materials to realize the full potential of these quantum phenomena. 
The speakers at this symposium shared their experiences and tackled this issue from different angles.

Mathias Scheurer (University of Stuttgart) discussed how engineering layered materials by stacking two-dimensional sheets can lead to interesting states of matter, such as unconventional superconductivity and correlated insulators. He also addressed the significant role of topology in superconductivity in these systems.

Superconductivity is also a primary focus of Oriana Diessel (Harvard University), who approached the topic from a different angle.  A significant part of her research focuses on non-equilibrium physics. Non-equilibrium physics involves manipulating these systems with external drives, such as electric fields or laser impulses, to observe phenomena like superconductivity. Can the temperature at which materials become superconducting be controlled?  However unclear at the moment, this field of research is aiming in exactly this direction.

Titus Neupert (from the University of Zurich) has shifted the focus to a different phenomenon: the fractional quantum Hall effect. Materials that exhibit this phenomenon are of great interest due to their potential applications in quantum computing. In his talk, Neupert discussed how stacking layers of these materials could lead to stable qubits - a step forward in the solution of the decoherence problem that has hindered progress in quantum computing.

The scientific community has also devoted its efforts to bridging the gap with produced experimental data.
Fabian Kugler from the University of Cologne presented his insights into method development. He discussed how the finite-difference Parquet method could improve our understanding of the pseudogap phase in the Hubbard model, a long-standing question within the theoretical physics community.

Significant effort is also being devoted to applying our knowledge of the quantum world to the direct design and development of next-generation energy technologies. In this regard, Chris Bartel (University of Minnesota) discussed anion redox in lithium transition metal chalcogenide cathode materials and its relevance to producing lithium batteries with higher storage capacities.

During the symposium, the strong influence of the era of machine learning and artificial intelligence on the strategies that researchers adopt was impossible to miss. 
Bingqing Cheng (University of California, Berkeley) and Johannes Margraf (University of Bayreuth) discussed how machine learning methods have become a natural platform for atomistic simulations.

On the other end, Kevin Jablonka (Friedrich Schiller University Jena) moved the bar of expectations a little higher, expanding the range of applications of these new, ubiquitous methods beyond atomistic simulations. He proposed training language models to extract information from experimental result datasets, effectively proposing AI as an assistant to the analytical thought processes involved in interpreting them. This perspective raises the question of the relationship between human-driven and AI-driven scientific progress. 

The symposium provided a valuable opportunity to gain insight into cutting-edge research and to foster stimulating discussions between the MPI's scientific staff and the invited speakers.
We thank all the speakers for this fantastic symposium and look forward to the exciting developments in their research.