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
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.
Opening for student assistant
We are lookging for a dedicated student assistant to support our research team. The main tasks will evolve around programming and conducting explorative studies in the area of machine learning for quantum science.
Update: The position has been filled.
Learning Hamiltonians that describe non-equilibrium steady states
Periodic driving is a prime way to engineer quantum matter with interesting properties. For this purpose, it is essential to bring the system into metastable steady states, the properties of which governed by a corresponding effective Hamiltonian. We have developed a deep-learning-assisted variational algorithm to reconstruct such effective Hamiltonians from observations. Thereby, we could recover local Hamiltonians in pre-thermal regimes and observe the growing complexity of instantaneous effective Hamiltonians in subsequent heating regimes. Our findings are now published in Phys. Rev. Research.
Observing fluctuation relations on a quantum processor
Jarzynski’s equality describes a relation in statistical physics between the fluctuations during a work process and the thermal free energy difference corresponding to the initial and final ensemble. While Jarzynski’s equality has been checked in many scenarios, previous experiments focused on systems with only a handful of degrees of freedom in the quantum regime. In our collaboration with colleagues at MPI PKS, the University of Bonn, and UC Berkeley/LBNL, we probed for the first time Jarzynski’s equality in the quantum many-body regime. We devise a dynamical protocol to measure work on quantum computers using a suitably prepared thermal ensemble and tested Jarzynski’s equality on different quantum processors with up to 16 qubits. The article has now been published in Phys. Rev. X.
Combined school and conference at ICTP
Together with colleagues from Hamburg, Waterloo, and Augsburg, we are organizing a school and conference “Frontiers at the intersection of quantum simulation and machine learning” to be held from Apr 8 to 19 2024 at the International Centre for Theoretical Physics (ICTP) in Trieste. This will be the first event at ICTP co-sponsored by the WE Heraeus Foundation. More detailed information will follow soon on the event website.
Jonas joins us as a Postdoc
Our group keeps growing and today is Jonas Rigo’s first day as a Postdoc. Welcome, Jonas!
Simulating spectral functions with NQS
We developed a new approach to simulate spectral functions using neural quantum states, which for example accurately captures the gap closing at the phase transition of a two-dimensional quantum magnet despite the associated diverging time scale. The paper appeared today in Phys. Rev. Lett.!