Seminar
Discrete Modeling
Modulation of information flow in cortical circuits
Optimal Control Design for Fluid Mixing: from Open-Loop to Closed-Loop
The question of what velocity fields effectively enhance or prevent transport and mixing, or steer a scalar field to the desired distribution, is of great interest and fundamental importance to the fluid mechanics community. In this talk, we mainly discuss the problem of optimal mixing of an inhomogeneous distribution of a scalar field via active control of the flow velocity, governed by the Stokes or the Navier-Stokes equations.
Data Assimilation for Discontinuous State Variables
Data assimilation is a method for combining available observations with a background from numerical model, to find the best estimate of the system, which is crucial for improving environmental variable prediction. However, commonly used Gaussian distribution assumption could introduce biases for state variables with discontinuous profiles, such as sea ice thickness with sharp features. In this talk, we focus on the design of non-Gaussian prior based on various statistics of the state variables.
Accuracy of deterministic vs. stochastic modeling of Ca2+-dependent vesicle release
Short wave-long wave interactions in fluid dynamics
Traveling wave solutions to the free boundary Navier-Stokes equations
Lie theory in tensor categories with applications to modular representation theory
Modeling neuronal synchrony
The Graphs and Networks seminar will meet Mondays at 9:30 am via Microsoft Teams.
Greg Constantine will start by giving 3 talks on classification attempts of graphs of maximal complexity. The triangle-free strongly regular graphs -- all subgraphs of the Higman-Sims graph -- are proved to be instances of such graphs of maximal complexity. A series of conjectures and some stubborn research issues will be brought to attention.
Jon Rubin will then give several talks on networks. Sevak Mkrtchyan will also present a series of talks.