Quantum many-body physics
We study how interactions generate collective quantum behavior in systems that are analytically challenging and often computationally extreme. The emphasis is on identifying useful models, robust signatures, and theoretically controlled routes to understanding correlated matter.
- Strongly interacting lattice models and emergent phenomena
- Topological phases and topological observables
- Nonequilibrium dynamics and driven quantum matter
- Connections between model Hamiltonians and experimentally accessible signatures
AMO and engineered quantum systems
Many of our projects are motivated by clean, tunable quantum platforms such as ultracold atoms, optical lattices, Rydberg arrays, and polar molecules. These systems provide a direct bridge between many-body theory, quantum control, and experimental realization.
- Ultracold atoms and molecules in lattices and tweezers
- Dipolar and rotational-state physics in molecular platforms
- Synthetic interactions, Floquet engineering, and resource-state generation
- Observable design for analogue and digital quantum simulation
Quantum information and simulation
The group develops theory and algorithms for quantum simulation, with particular interest in measurement-based approaches, benchmark design, and the structure of quantum resource states. This work links many-body physics to quantum computing architectures and workflows.
- Measurement-based quantum computing and graph-state methods
- Hardware-aware quantum simulation algorithms
- Benchmarking protocols for near-term quantum devices
- Error-aware and measurement-efficient algorithm design
Computational condensed matter and scientific software
Our work is strongly computational. We use and help build scalable tools for solving quantum many-body problems, and we care about reproducibility, software sustainability, and broad access to scientific computing infrastructure.
- Exact diagonalization, DMRG, Monte Carlo, and hybrid workflows
- Open-source software ecosystems for quantum simulation
- Reusable data resources and benchmark datasets
- Training-oriented infrastructure for the next generation of computational physicists