[ugrads] SIAM Lunch and Computational Algebra Talk Update
Adam Rumpf
arumpf at hawk.iit.edu
Tue Nov 8 12:10:51 CST 2016
Hello All,
This is a reminder of this week's free lunch and computational algebra
talk, and an update on the location. The event will take place *tomorrow,
November 9, 12:40-1:50pm in RE (E1) Room 103*. The discussion will be
introductory level and should be accessible to everyone, regardless of
academic background. Please see the title and abstract below for more
details. As always, faculty and students of all majors are welcome to
attend. We hope to see you tomorrow!
Sincerely,
Adam Rumpf
IIT SIAM Student Chapter President
*Speaker:* Sonja Petrović
*Title:* Polynomials in Action
*Abstract:* Systems of polynomial equations are ubiquitous in the sciences,
including statistics, optimization, mathematical biology, coding theory,
robotics, etc. The interest in studying the structure of such systems stems
from the fact that it encodes important properties of the models in these
application areas. For example, we ask questions such as: how complex is
the system (i.e. the corresponding solution set?), are there even any
solutions (i.e. is the system feasible?), are there too many solutions
(e.g. infinitely many?), is there a better way to represent the system
(i.e. do we have too many redundant polynomials?). Oftentimes the problem
is even one step back, so to say: we are given an explicit description of
the applied problem, say a parametric model of evolution, and we are
interested in *finding* the corresponding polynomial system. This problem
is surprisingly difficult in many applications, yet its answer--when
obtainable--has already been shown very powerful in areas such as
phylogenetics, a branch of computational biology, and other areas that use
parametric statistical models.
This talk will give a glimpse into how such systems are constructed and
what some of the difficulties look like through an example. No prior
knowledge of computational algebra is required; this is, in fact, an
invitation to computational algebra.
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