Talks

Topics will include (but are not limited to): - Quantum error correction in quantum gravity and condensed matter - Quantum information scrambling and black hole information - Physics of random tensor networks and random unitary circuits

I will discuss the large-N limit of two-dimensional symmetric product orbifolds. The goal is to single out which symmetric product orbifold theory could lead to a strongly coupled theory, whose dual could be a semi-classical theory of AdS_3 gravity, by quantifying the large-N limit of the BPS spectrum and the behaviour under exactly marginal deformations. From this analysis, I will propose an infinite family of new holographic CFTs.

Zoom Link: https://pitp.zoom.us/j/99948208493?pwd=RDRYclc2a05kMmNZL3ZhMWxMdWdNUT09

Muons are the archetypal ‘who ordered that?’ surprise discovered in cosmic rays and fittingly, recent muon measurements including g–2 could be challenging standard paradigms again. Remarkably, tau g–2 remains poorly constrained but can be 280 times more sensitive to new physics than the muon. Recently, ATLAS and CMS announced groundbreaking measurements of tau g–2 using the landmark observation of tau pairs created via photon collisions in LHC heavy-ion data. Beyond colliders, quantum sensing progress enables next-generation haloscopes to illuminate axion-like origins of dark matter above microwave frequencies. This motivates the Broadband Reflector Experiment for Axion Detection (BREAD) proposal at Fermilab and its interdisciplinary science program bridging astronomy, particle physics, and quantum technology.

Zoom Link: https://pitp.zoom.us/j/95937524952?pwd=eFVaTXVXOHBiNE9TZk9oMGNxRUwyQT09

This course is designed to introduce modern machine learning techniques for studying classical and quantum many-body problems encountered in condensed matter, quantum information, and related fields of physics. Lectures will focus on introducing machine learning algorithms and discussing how they can be applied to solve problem in statistical physics. Tutorials and homework assignments will concentrate on developing programming skills to study the problems presented in lecture.

Next generation cosmic microwave background (CMB) experiments and galaxy surveys will generate a wealth of new data with unprecedented precision on small scales. Correlations between CMB anisotropies and the galaxy density carry valuable cosmological information about the largest scales, creating novel opportunities for inference. It is possible to foresee a future where reconstruction of the gravitational weak-lensing potential, velocity fields and the remote quadrupole field will provide the most precise tests of fundamental physics. The use of the second-order effects in the CMB to extract this information motivate a strong push towards low noise, high resolution frontiers of the upcoming generation CMB experiments. In this talk, I will discuss the prospects to use small-scale kinetic and polarized Sunyaev Zel’dovich effects and the moving-lens effect, in cross-correlation with ongoing galaxy surveys, to extract cosmological information. 

Zoom Link: https://pitp.zoom.us/j/91455862792?pwd=M1hFRDgyOXVKU1U4Z0pLcm1wZGdRQT09

This course will introduce some advanced topics in general relativity related to describing gravity in the strong field and dynamical regime. Topics covered include properties of spinning black holes, black hole thermodynamics and energy extraction, how to define horizons in a dynamical setting, formulations of the Einstein equations as constraint and evolution equations, and gravitational waves and how they are sourced.

Topics will include (but are not limited to): - Quantum error correction in quantum gravity and condensed matter - Quantum information scrambling and black hole information - Physics of random tensor networks and random unitary circuits

 

Unlike conventional global symmetries that act on all of space, subsystem symmetries act only on rigid subspaces such as lines, planes or fractal regions. Such symmetries are of interest for their close connection to fracton physics and in their own right. In this talk, I discuss phenomena that can occur in two-dimensional systems with subsystem symmetry and anyon excitations, where the symmetry fractionalizes on anyon excitations. This turns out to be manifest in the mobility of the fractionalized excitations under dynamics that respect the symmetry. Such symmetry fractionalization was previously thought to be impossible, and indeed there are a number of differences from conventional symmetry fractionalization. I will present a general framework to describe subsystem symmetry fractionalization in two dimensions, and give a number of simple examples of this phenomenon in commuting Pauli Hamiltonians.

This talk is based on arXiv:2203.13244, work in collaboration with David Stephen, Arpit Dua, José Garre-Rubio and Dominic Williamson.

Zoom Link: https://pitp.zoom.us/j/93741883840?pwd=RlMrUGwwVEt5WFdoNGpkMmdSVXp5UT09

I review a recent approach to connecting quantum gravity and the real world by deconstantizing the constants of nature, and using their conjugate as a time variable. This is nothing but a generalization of unimodular gravity. The wave functions are then packets of plane waves moving in a space that generalizes the Chern-Simons functional. For appropriate states they link up with classical cosmology in the appropriate limit. There are however deviations, namely during the matter to Lambda transition, raising the possibility that quantum gravity could be in action here and now. At the other extreme I show how this approach can be used to resolve the cosmological singularity, and perhaps more.

Zoom Link: https://pitp.zoom.us/j/94010122575?pwd=L291eHNSOG1wZmpCL1lmWHVJaEwwdz09

This course is designed to introduce modern machine learning techniques for studying classical and quantum many-body problems encountered in condensed matter, quantum information, and related fields of physics. Lectures will focus on introducing machine learning algorithms and discussing how they can be applied to solve problem in statistical physics. Tutorials and homework assignments will concentrate on developing programming skills to study the problems presented in lecture.