Exploring the interface between condensed matter physics and quantum information science.
We are interested in how quantum algorithms behave like condensed matter, how condensed matter is captured by quantum algorithms, and how machine learning can help us make discoveries in either of these areas.
Please explore our research, read our blog posts, or get to know our team!
news
Jul 21, 2022 | Arxiv alert: That is 3 in a day. Phew! Supersymmetry on the lattice: Geometry, Topology, and Spin Liquids, The fate of topological frustration in quantum spin ladders and generalizations, Topology shared between classical metamaterials and interacting superconductors |
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Jul 20, 2022 | Our Cornell PhD student Po-Wei successfully defended his thesis! Congratulations Dr. Lo!!! |
Jul 18, 2022 | Po-Wei B Exam: Topology Shared Between Classical and Quantum Materials 701 Clark Hall or Zoom |
Jun 29, 2022 | Our Binghamton graduate student Eric Aspling presented a poster at Quantum Information and Probability 2022 conference at Linnaeus University in Växjö, Sweden |
Jan 06, 2022 | Our results on adaptive variational Fermi-Hubbard circuits published on PRA. |
selected publications
- Emergent coding phases and hardware-tailored quantum codesarXiv preprint arXiv:2503.15483, 2025
- Supersymmetry on the lattice: Geometry, topology, and flat bandsPhysical Review Research, 2024
- Design constraints for Unruh-DeWitt quantum computersSciPost Physics Core, 2024
- Universal Quantum Computing with Field-Mediated Unruh–DeWitt QubitsarXiv preprint arXiv:2402.10173, 2024
- Revealing microcanonical phases and phase transitions of strongly correlated systems via time-averaged classical shadowsPhysical Review B, 2023
- Measurement-induced landscape transitions in hybrid variational quantum circuitsarXiv preprint arXiv:2312.09135, 2023