RESEARCH INTERESTS
The quest for a better theoretical understanding and experimental
exploitation of many-body phenomena motivates us to develop and
apply innovative control approaches as well as numerical simulation
techniques such as tensor network algorithms.
Several platforms are nowadays available for realising so-called
“Synthetic Quantum Matter”, the theoretical setting of which is the
overall big goal of our subdivision’s research activity. A
paradigmatic example is the quantum optical shaping of cold atomic
gases, but many others are also promising.
Achieving new phases “on-demand” is of primary interest not only for
fundamental questions within the condensed matter and quantum
information communities, but also in view of the emerging interest
in applications for quantum technology (as affirmed by the
EU-Flagship and the German Federal initiative for the upcoming five
to ten years).
The red line of our investigation is the combination of geometrical
constraints, different kind and range of interactions and
(synthetic) gauge fields to access
- interacting topological states of matter and
- many-body effects in the transport properties of low-dimensional systems.
The goal is to formulate concrete experimental proposals for cold
atomic gases, photonic waveguides, superconducting Josephson arrays,
or artificially grown materials, just to mention a few setups.
In order to broaden our understanding, besides analytical mappings
onto effective models, we routinely exploit numerical techniques
inspired by quantum information, namely tensor network algorithms.
This also leads to insights about the entanglement structure of
correlated states. Numerical simulations could serve to tailor and
validate the experimental setups before employing them to explore
regimes that are classically hard to compute.
Tensor Networks
Our numerical
work via Tensor Networks focuses on shaping and characterizing
interesting many-body phenomena via quantum simulators, as well
as on benchmarking the power of these physical platforms once
used as noisy intermediate-scale quantum computers:
- Using and further developing existing tensor network libraries and algorithms, possibly enriching them with tools coming from the machine learning community
- Investigating phases of matter where entanglement plays a key role, making them amenable to constitute the basis for developing quantum technologies
- Interfacing these research lines with the quantum optimal control activity of the PGI-8 institute of FZ-Jülich