Math/ICES Center of Numerical Analysis Seminar (Spring 2015)

Time and Location: Friday, 3:00-4:00PM, POB 6.304 (Previously known as ACE 6.304). Special time and locations are indicated in color.

If you are interested in meeting a speaker, please contact Kui Ren (

Here are the links to the past seminars: Fall 2014 Spring 2014 Spring 2013 Fall 2012, Spring 2012, Fall 2011, Spring 2011, Fall 2010, Spring 2010, Fall 2009



Title and Abstract


POB 4.304

Gil Ariel,
Bar Ilan University)

Multiscale dynamics of marching locust swarms.

A key question in the study of collective animal motion is how the details of animal locomotion and interaction between individuals affect the macroscopic dynamics of the hoard, flock or swarm. Motivated by lab experiments with marching locust nymphs we suggest a generic principle, in which intermittent animal motion can be considered as a sequence of individual decisions, in which animals repeatedly reassess their situation and decide whether or not to swarm. This interpretation implies some generic characteristics regarding the build-up and emergence of collective order in swarms: in particular, that order and disorder are generic meta-stable states of the system, suggesting that the emergence of order is kinetic and does not necessarily require external environmental changes. Joint work with Yotam Ophir, Sagi Levi, Eshel Ben-Jacob and Amir Ayali.


3:00-4:00 PM
POB 6.304

Sebastian Acosta
(Baylor College of Medicine)

Thermoacoustic imaging in an enclosure with variable wave speed

Unlike the free-space setting, we consider thermoacoustic imaging in a region enclosed by a surface where an impedance boundary condition is imposed. This condition models physical boundaries such as acoustic mirrors or detectors. By recognizing that the inverse problem is equivalent to boundary observability, we use control operators to derive a solvable equation for the unknown initial condition. If well-known geometrical conditions are satisfied, this approach is naturally suited for variable wave speed and for measurements on a subset of the boundary. We will also discuss some preliminary results and challenges concerning the numerical solution of the proposed reconstruction equation


POB 6.304
David Aristoff
(Mathematics, Colorado State University)
The parallel replica method for Markov Chains

Markov chains have widespread applications in computational math, chemistry, physics and statistics. For instance, in Markov chain Monte Carlo, Markov chains are used to estimate deterministic quantities for which closed-form expressions are unknown. Another example is in computational chemistry, where Markov chains are used to model molecular dynamics. Of course, it is essential that the Markov chains can be simulated efficiently. We present a very general algorithm for improving the real-time efficiency of Markov chain simulations. In many cases of practical interest, the chains tend to get "stuck" in certain subsets of configuration space. Our algorithm uses many replicas of the chain, simulated in parallel, to help it get "unstuck". The algorithm can be seen as a generalization of A.F. Voter's parallel replica method for simulating Langevin dynamics.