Welcome to the pages of our Computational Quantum Science research group! Our research covers various aspects of complex quantum systems, especially non-equilibrium settings. We have a strong focus on the development of computational methods that leverage the latest developments in machine learning for this purpose. Our group is part of PGI-8 at FZ Jülich and the FIDS at the University of Regensburg.
News
Massimo joined as new PhD student
Our group continues growing: Massimo joined us as a new PhD student. He will work on investigating the dynamics of correlated two-dimensional materials with neural quantum states.
Explicitly time-dependent NQS
Our article on explicitly time-dependent NQS has been published in Machine Learning: Science and Technology. Instead of conventional forward-integration of Schrödinger’s equation, this technique optimizes an artificial neural network to solve the dynamics simultaneoulsy across a whole time interval. We demonstrated the efficiency of the approach by simulating quench dynamics and a time-dependent control protocol for a large two-dimensional quantum magnet.
Paper on roughening dynamcis published
Thanks to great efforts by Wladi, our work on roughening dynamics now appeared in Physical Review Letters! In this paper, we describe how the smooth-interface regime below the roughening transition of the two-dimensional quantum Ising model leads to prethermal plateaux in the non-equilibrium dynamics of domain wall initial conditions.
Stefan and Valentin joined us for Master projects
Two new Master students joined our group: Stefan will work on aspects of many-body quantum chaos and Valentin will continue to develop our explicitly time-dependent NQS approach.
Postdoc opening
We are looking for a motivated postdoc to join our team and work on new approaches to tackle the quantum many-body problem with machine learning techniques. See the opening for details.
Update: Review of applications has started.
Noé joined as new PhD student
With the beginning of October, Noé joined our group as a new PhD student. He is going to work on our DFG project ``Machine Learning to Tailor Correlated States of Matter’'.
Workshop on NQS for dynamics coming up
In November we’ll be hosting a workshop on simulating the non-equilibrium dynamics with neural quantum states here in Regensburg. See the workshop website for more information!
Jonas distinguished as Young Excellent Scientist
Our Postdoc Jonas has secured one of the five places in FZ Jülich’s Young Excellent Scientist Program (YESP). The program offers individual support modules, among which the funding to hold their own symposium on a topic of their choice. Congratulations, Jonas!
Opening for PhD position
We are looking for a new PhD student for a DFG-funded project on “machine learning to tailor correlated states of matter”. The project in cooperation with colleagues at MPI PKS will evolve around neural quantum states for non-equilibrium quantum many-body physics.
Update: The position has been filled.
Introducing wave function networks
The advent of quantum simulators and computers has made projective measurement a reality at the many-particle level: Experiments routinely collect high-quality pictures of wave functions made of hundreds of components. But the wealth of information obtained challenges traditional theoretical modeling, which often focuses on a few observables. In our work, that is now published in Phys. Rev. X, we introduce a framework to describe wave-function measurements using network theory, enabling the discovery of a very deep inner structure in quantum wave functions: scale-freeness similar to other completely disconnected ensembles, such as those found in communication, social networks and the internet.