Statistics seminars

Early active black holes seen by JWST, pulsar-timing evidence for a gravitational-wave background and stellar tidal disruptions probe different parts of black-hole growth. This talk presents L-GalaxiesBH, which follows black holes and their host galaxies from early formation to the present. Combining these observations constrains growth models, including the abundance of rapidly growing early objects, massive binaries nearby and elusive intermediate-mass systems.

Sisi Zhou examines how quantum information methods can improve the precision of physical measurements. Qubit examples distinguish noise that quantum error correction can suppress from noise indistinguishable from the signal. The discussion extends to several qubits, phase estimation, many-body measurements and distributed sensors. A second part applies quantum-learning tools, including tomography, certification and purification, to estimation of several parameters. Because incompatible observables prevent all parameters from being measured optimally together, designing measurements is difficult. The talk presents practical protocols for several such sensing tasks that combine efficient implementation with sensitivity close to the optimum.

Paco Villaescusa examines how simulations and artificial intelligence change the extraction of physical knowledge from precision cosmological surveys. The talk asks how much information lies in large-scale structure beyond power spectra, including nonlinear scales and higher-order statistics, and introduces the Quijote and Backlight simulation programmes. It then addresses the uncertain astrophysical processes that complicate small-scale inference through CAMELS, a framework combining cosmology, galaxy formation and machine learning. DREAMS is presented as a route to predicting dark-matter observables while accounting for baryonic uncertainties. The final part considers coupling simulations with increasingly capable AI: Denario is introduced as an agentic research system that generates hypotheses, designs analyses, writes and executes code, interprets results and refines research directions. The discussion considers what coordinated populations of agents and simulations spanning physical scales could make possible.

A Markov chain can sample effectively from a random or data-informed start even when worst-case initialization mixes slowly. This talk uses weak Poincaré inequalities to analyse that regime, with applications to simulated annealing for spherical spin glasses and to mixtures of log-concave distributions.

Continuum Glauber dynamics samples Gibbs point processes with repulsive interactions, including hard spheres. This talk develops continuous spectral-independence and localization tools to establish spectral gaps and efficient sampling for arbitrary-range repulsive potentials. The approach improves fixed-density packing thresholds and works directly in the continuum rather than discretizing the model.

Claims of an unexpectedly large quasar dipole have raised questions about large-scale cosmic isotropy. This talk tests whether survey selection and estimation effects can explain the discrepancy with the motion inferred from the microwave background. Higher angular multipoles in the quasar map can account for the difference, emphasizing the need to control systematic effects before interpreting the signal as a failure of standard cosmology.