Talks

Topologically ordered phases of matter have long been regarded as lying beyond the Landau–Ginzburg paradigm of symmetry breaking. Our recent studies of anyon condensation, however, suggest that such phases may, in fact, be brought back within the Landau–Ginzburg framework. In this talk, I will present a framework that brings topological phases back into the Landau–Ginzburg picture by reformulating the string-net model to be a genuine lattice gauge theory coupled to anyonic matter fields. Within this modified model, topological phase transitions induced by anyon condensation and their consequent phenomena, such as order parameter fields, coherent states, Goldstone modes, and gapping gauge degrees of freedom, can be formulated as Landau's effective theory of the Higgs mechanism.

Carrying the insights of conditional probability to the quantum realm is notoriously difficult due to the non-commutative nature of quantum observables. Nevertheless, conditional expectations on C* and von Neumann algebras have played a significant role in the development of quantum information theory, and especially the study of quantum error correction. In quantum gravity, it has been suggested that conditional expectations may be used to implement the holographic map algebraically, with quantum error correction underlying the emergence of spacetime through the generalized entropy formula. However, the requirements for exact error correction are almost certainly too strong for realistic theories of quantum gravity. In this talk, we provide an overview of the multifaceted nature of quantum conditional probability by exploring different non-commutative generalizations of conditional expectations which meet the demands of non-exact error correction. We then exemplify the utility of these tools through two examples. First, we demonstrate how operator valued weights can be used to classify the possible symmetries (including non-invertible symmetries) of a quantum system. Then, we introduce a generalization of Connes’ spatial theory leading to a fully non-commutative form of Bayes' law. This allows for an exact quantification of the information gap occurring in the data processing inequality for arbitrary quantum channels. When applied to algebraic inclusions, this further provides an approach to factorizing the entropy of states into a sum of terms including an emergent area operator that is fully non-commutative rather than central. 

Generative AI — a class of algorithms that learn complex probability distributions from data — is opening new avenues for discovery across fundamental physics. In this talk, I will highlight several recent applications. At the LHC, we are ushering in a new paradigm of model-agnostic searches for new physics, developing powerful anomaly detection methods using generative AI techniques such as normalizing flows. These same methods, applied to astronomical data, have enabled discovery of stellar streams and ultra-faint dwarf galaxies. Generative methods also accelerate simulation-based inference across many domains, including gravitational wave detection at pulsar timing arrays. When combined with physics-informed neural networks, generative AI enables an entirely new model-free measurement of the dark matter density in the local Galactic neighborhood. Finally, I will discuss how generative AI in the form of agentic LLMs is creating new modes of human-AI collaboration that promise to further accelerate research. Taken together, these advances signal that we have entered a new and exciting era — one where the oldest questions about our universe may very well be answered with the help of the newest AI tools.

The AdS/CFT correspondence makes it possible in principle to study explicit black hole microstates using field theory techniques. In practice, this is still difficult because the field theory is only dual to gravity when it is strongly coupled. A more modest goal is to focus on supersymmetric black holes which have the minimal energy allowed by their other charges. The superconformal index suggests that many of these are protected from quantum corrections and can therefore be constructed at weak coupling. I will explain how one can identify candidates for black holes by searching the Hilbert space of ABJM theory. On general grounds, these should depend sensitively on trace relations at finite N. This principle, known as fortuity, was first established in a similar study of maximally supersymmetric Yang-Mills theory. I will show that similarities between the two theories extend to the quantitative level thereby allowing additional progress to be made without a brute force search.