Department of Physics & Astronomy
University of New Mexico

Physics and Astronomy Colloquium

Physics, Inference, and Networks (continued)

Presented by Cristopher Moore, Santa Fe Institute

There is a deep analogy between Bayesian inference and statistical physics. When we fit a model to noisy data, we can think about the "energy landscape" of possible models, and look for phase transitions where the ground truth suddenly gets lost in this landscape -- either because of thermal equilibrium (where "heat" is noise) or because of dynamics (e.g. a metastable state trapped behind a free energy barrier). I'll use this framework to describe phase transitions in community detection in networks, where communities suddenly become hard or impossible to find. If time permits, I'll discuss related spectral algorithms, and give a hint of similar phase transitions in other inference problems.

3:30 pm, Friday, September 23, 2022
Via Zoom. Please take the Satisfaction Survey,


Disability NoticeIndividuals with disabilities who need an auxiliary aid or service to attend or participate in P&A events should contact the Physics Department (phone: 505-277-2616, email: well in advance to ensure your needs are accomodated. Event handouts can be provided in alternative accessible formats upon request. Please contact the Physics front office if you need written information in an alternative format.

A schedule of talks within the Department of Physics and Astronomy is available on the P&A web site at