Events on Thursday, May 1st, 2025
- R. G. Herb Condensed Matter Seminar
- Superconductivity with Anyons
- Time: 10:00 am - 6:00 pm
- Place: 5310 Chamberlin
- Speaker: Hart Goldman, UMN
- Abstract: I will discuss the phenomenology of superconductors hosting both order parameter vortices and fractionally charged anyon excitations. I will demonstrate that in such systems superconductivity and topological order are intertwined under applied magnetic fields, leading to surprising observable consequences departing from traditional superconductivity from electronic pairing. In particular, I will show that vortices nucleated by perpendicular magnetic fields must trap anyons in their cores. However, because only some vortices can trap an integer number of anyons, this places a constraint on the vortex phase winding. In general, rather than the expected hc/2e quantization of superconducting vortices, we find instead the enhanced flux quantum of hc/e, which I will argue should affect a wide range of observables. I will further develop a general Landau-Ginzburg theory describing vortex fluctuations and discuss the phase diagram as perpendicular magnetic field is increased, showing that condensation of the intertwined vortices leads to exotic insulating phases hosting neutral anyons and a nonvanishing thermal Hall effect.
- Host: Elio König
- NPAC (Nuclear/Particle/Astro/Cosmo) Forum
- The BayesLIM Project to map the high-redshift universe
- Time: 2:30 pm - 3:30 pm
- Place: Chamberlin 5280
- Speaker: Nick Kern, MIT
- Abstract: I will discuss using next-generation radio telescopes to map the high-redshift universe with unprecedented statistical precision, enabling us to tap into a trove of currently unharnessed cosmological information.
The Bayesian Line Intensity Mapping (BayesLIM) project leverages advances in machine learning software and hardware to deliver a comprehensive Bayesian forward model for cosmological intensity mapping experiments. Its goal is to enable the first robust detection of the high redshift 21 cm signal, while faithfully accounting for covariant uncertainties between the signal and contaminants. - Host: Peter Timbie