Student March Meeting Talks

Note: Pizza will be served at 12:15pm
Speaker: Anirudh Chandrasekaran, Mohit Pandey, and Shiyu Zhou, Boston University

When: February 27, 2020 (Thu), 12:30PM to 01:30PM (add to my calendar)
Location: SCI 352
Hosted by: Eric Boyers

This event is part of the Graduate Student Council Events.

This student seminar, we will hear from several BU graduate students about the work they will be presenting at the upcoming APS March Meeting. Feedback for the speakers is welcome and encouraged!

Anirudh Chandrasekaran - Catastrophe theory classification of Fermi surface topological transitions

Abstract: We classify all possible singularities in the electronic dispersion of two-dimensional systems that occur when the Fermi surface changes topology, using catastrophe theory. For systems with up to seven control parameters (i.e., pressure, strain, bias voltage, etc), the theory guarantees that the singularity belongs to to one of seventeen standard types. We show that at each of these singularities the density of states diverges as a power law, with a universal exponent characteristic of the particular catastrophe, and we provide its universal ratio of amplitudes of the prefactors of energies above and below the singularity. We further show that crystal symmetry restricts which types of catastrophes can occur at the points of high symmetry in the Brillouin zone. For each of the seventeen wallpaper groups in two-dimensions, we can list which catastrophes are possible at each high symmetry point.

Mohit Pandey - Detecting chaos using adiabatic gauge potential

Abstract: Finding signatures of chaos in the quantum world has been a long standing puzzle. We propose adiabatic gauge potential (AGP), which encodes the geometry of eigenstates when varying a control parameter in the Hamiltonian, as an extremely sensitive diagnostic tool for quantum chaos. Frobenius norm of AGP shows remarkably different scaling with system size for integrable and chaotic systems: polynomial versus exponential. Moreover, AGP norm scaling can detect chaos at exponentially small integrability-breaking strength, which is orders of magnitude smaller than what can be detected using mean ratio of two consecutive level spacings.