LASSP/AEP Student Seminar: Yichen Xu (Kim Group)

Average-Exact Mixed Anomalies and Compatible Phases

The quantum anomaly of a global symmetry is known to strongly constrain the allowed low-energy physics in a clean and isolated quantum system. However, the effect of quantum anomalies in disordered systems is much less understood, especially when the global symmetry is only preserved on average by the disorder. In this work, we focus on disordered systems with both average and exact symmetries A×K, where the exact symmetry K is respected in every disorder configuration, and the average A is only preserved on average by the disorder ensemble. When there is a mixed quantum anomaly between the average and exact symmetries, we argue that the mixed state representing the ensemble of disordered ground states cannot be featureless. While disordered mixed states smoothly connected to the anomaly-compatible phases in clean limit are certainly allowed, we also found disordered phases that have no clean-limit counterparts, including the glassy states with strong-to-weak symmetry breaking, and average topological orders for certain anomalies. We construct solvable lattice models to demonstrate each of these possibilities. We also provide a field-theoretic argument to provide a criterion for whether a given average-exact mixed anomaly admits a compatible average topological order.

Become a Fellow

Join the Cornell Institute for Digital Agriculture and become a participating member in advancing research, thought, policy and practice to advance the field of digital agriculture and help build stronger, more resilient agri-food systems.

Stay up to Date

Receive our newsletter for announcements of events, opportunities, digital ag news, Cornell news, and more.

CIDA - Cornell Institute for Digital Agriculture

If you have a disability and are having trouble accessing information on this website or need materials in an alternate format, contact [email protected] for assistance.

FOLLOW US


CIDA Copyright 2023 | CIDA is an equal opportunity employer | Terms of Use | Privacy Policy