Past Events

  • High Energy Seminar: "AdS_2 Holography and Non-extremal Black Holes"

    David Rittenhouse Laboratory, 2N36

    Ioannis Papadimitriou (SISSA)

    I will present aspects of AdS_2 holography for a specific Einstein-Maxwell-Dilaton model that is obtained by Kaluza-Klein reduction from pure AdS_3 gravity with negative cosmological constant. In particular, I will derive the one-dimensional holographic dual for both running and constant dilaton solutions, and I will discuss the connection with the Sachdev-Ye-Kitaev model.

  • Condensed Matter seminar: "Optical Tools for Unraveling Whole-brain Neuronal Circuit Dynamics Underlying Behavior "

    David Rittenhouse Laboratory, A4

    Alipasha Vaziri, Rockefeller University

    Optical technologies have been transformative for our current understanding of structure and function of neuronal circuits underlying behavior and are in many cases the limiting factors for pushing our understanding of the brain forward. I will discuss two different areas of research in our lab in this context.

  • HE Experimental Physics: "Results from the DUNE 35-ton Prototype Detector"

    David Rittenhouse Laboratory, 2C8

    Jonathan Insler (Drexel University)

    The 35 ton prototype for the Deep Underground Neutrino Experiment (DUNE) far detector was a single phase liquid argon time projection chamber (LAr-TPC) integrated detector that took cosmics data for a six week run from February to the middle of March 2016. The 35 ton was built to test the liquid argon technologies to be used by the full size DUNE far detector in a fully integrated system.

  • Math-Bio seminar: "Structured latent factor models to recover interpretable networks from transcriptomic data"

    Carolyn Lynch Laboratory, 318

    Barbara Engelhardt, Princeton University

    Latent factor models have been the recent focus of much attention in "big data" applications because of their ability to quickly allow the user to explore the underlying data in a controlled and interpretable way. In genomics, latent factor models are commonly used to identify population substructure, identify gene clusters, and control noise in large data sets. In this talk I present a general framework for Bayesian latent factor models.

  • High Energy Seminar: "Entanglement, Holography and Causal Diamonds"

    David Rittenhouse Laboratory, 2N36

    Michal Heller (Perimeter Institute)

  • Condensed Matter seminar: "Unusual Fluctuations and Absorbing States"

    David Rittenhouse Laboratory, A4

    Dov Levine, Technion – Israel Institute of Technology

    Absorbing state models are far-from-equilibrium many-body systems which exhibit a phase transition with characteristics similar to those of a continuous equilibrium transition.  One major difference, however, which we have recently discovered, is that as the critical point is approached, spatial particle fluctuations decrease, resulting in a hyperuniform distribution with long-range correlations.  The effects of noise on these results will be discussed as well.

  • Astro Seminar: "Cosmology Constrains the Standard Model and Beyond!

    David Rittenhouse Laboratory, A4

    Amol Upadhye (University of Wisconsin-Madison)

    Neutrinos are Standard Model particles whose mass splittings are known, but whose absolute mass scale remains a mystery.  Cosmology provides the best upper bound on the sum of masses, 0.23 eV, a number intriguingly close to the dark energy scale, and promises to measure the neutrino masses over the next decade.  I describe the effects of massive neutrinos and evolving dark energy on the power spectrum of large-scale structure.  Working in the framework of higher-order cosmological perturbation theory, I show that the power spectrum in a wide variety of dark energy mod

  • Special Seminar - From viscous to elastic sheets: Dynamics of freely floating smectic films

    David Rittenhouse Laboratory - A4

    Kirsten Harth, Otto-von-Guericke Universität Magdeburg

    The dynamics of droplets and bubbles, particularly on microscopic scales, are of considerable importance in biological, environmental, and technical contexts. Soap bubbles, vesicles and components of biological cells are well known examples where the dynamic features are significantly influenced by the properties of thin membranes enclosed by fluids. Two-dimensional membrane motions couple to 3D shape transformations.

  • Math-Bio Seminar: "Fluctuation and fixation in the Axelrod model"

    318 Carolyn Lynch Lab

    Nicolas Lanchier, Arizona State University

    The Axelrod model is a spatial stochastic model for the dynamics of cultures which includes two key social components: homophily, the tendency of individuals to interact more frequently with individuals who are more similar, and social influence, the tendency of individuals to become more similar when they interact. Each individual is characterized by a collection of opinions about different issues, and pairs of neighbors interact at a rate equal to the number of issues for which they agree, which results in the interacting pair agreeing on one more issue.

  • Math-Bio Seminar: "The joint total tree length at linked loci in populations of variable size"

    318 Carolyn Lynch Lab

    Matthias Steinrücken, University of Massachusetts Amherst

    The inference of historical population sizes from contemporary genomic sequence data has gained a lot of attention in recent years. A particular focus has been on recent exponential growth in humans. This recent growth has had a strong impact on the distribution of rare genetic variants, which are of particular importance when studying disease related genetic variation. The popular PSMC method (Li and Durbin, 2011) can be used to infer population sizes from a sample of two chromosomes.