Annual Report 2008.pdf - SAMSI

Publications
1. E.T. Spiller, A. Budhiraja, K. Ide, and C.K.R.T. Jones. Modified Particle Filter Methods
for Assimilating Lagrangian Data into a Point-vortex Model (to appear in Physica D).
Other Research
Papers from Ph.D. Research:
1. E.T. Spiller, and W.L. Kath. A Method for Determining Most Probable Errors in
Nonlinear Lightwave Systems. (to appear in SIAM Journal on Applied Dynamical
Systems)
2. E.T. Spiller, and G. Biondini. Importance Sampling for Dispersion Managed Solitons.
(in preparation)
Presentations:
“Rare events and pdf scaling of nonlinear lightwave systems”
SIAM Conference on Nonlinear Waves and Coherent Structures. Rome, July 21-24, 2008
Awards:
AWM Travel grant to attend and present at SIAM Conference on Nonlinear Waves and Coherent
Structures. Amount: $1,725
Last year I began a research project using particle filters to perform data assimilation on pointvortex
fluid systems. This work is with Chris Jones, Amarjit Budhiraja, and Kayo Ide
Presentations:
“Modified Particle Filter Methods for Lagrangian Data Assimilation”
llinois Institute of Technology: Applied Math Seminar (invited), 29 January, 2008
University at Buffalo: Applied Math Seminar (invited), 4 February, 2008
Marquette University: Colloquium (invited), 8 February, 2008
Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, 6-11 July, 2007
Continuing Collaborations while at SAMSI
I still collaborate with my previous postdoctoral advisor Gino Biondini
ELAINE SPILLER – Commentary by Bruce Pitman and Jim Berger
Elaine has been involved with two major research activities while at SAMSI. One is on Particle
Filtering for Lagrangian Data Assimilation. This has already led to one paper to appear in
Physica D.
Elaine’s other major effort was in the area of granular materials/volcanology, which tied in with
both with the Computer Models program last year and the Risk program this year. Elaine was a
key component of a working group that has developed powerful new methodology for making
risk assessments of dangerous geophysical flows, utilizing a unique combination of computer
modeling, probabilistic modeling, and statistical risk assessment. This has already led to a paper
(submitted to Technometrics) and a funded 3-year NSF research grant.
Elaine was new to both the granular flow and statistical risk aspects of the problem, and so was
initially slow to become heavily involved. As the project developed, however, she became a full