—  Mathematics & Statistics

MATH 390: The SMaRT Seminar | Spring 2023

Mondays, 4:15–5:30 in Cuneo Hall 103

SMaRT (Seminar in Mathematics Research for sTudents) is the class for MATH 390.

Students who are not enrolled in the course and faculty are welcome to attend.

For the students enrolled in MATH 390, the seminar will cultivate their presentation skills through participation and critical discussion of brief lectures on familiar and unfamiliar topics. Enrolled students will be able to access a detailed syllabus for the course and further resources on Sakai.

Professor:  Dr. Carmen Rovi


January
23
First Class
Organizational meeting with enrolled students
30
Dr Peter Tingley
Shannon's Information Theorem
February
6
Dr Xiang Wan
Discrete Variable Representation Theory and Applications in Quantum Chemistry
13
Ariana Grymski
Conway Rational Tangles and the Thompson Group
20
Dr Rafael S. González D'León
Polytopes
27

TBD
March
6 Spring break - No classes
13
TBD
TBD
20
TBD
TBD
27
TBD
TBD
April
3
TBD
TBD
10
Easter Holidays - No class
17
TBD
TBD
24
TBD
TBD

Directions

Cuneo Hall is located in the Loyola's Lake Shore Campus, on 6430 N. Kenmore Avenue, Chicago, IL (map)

Abstracts

February 6: Dr Xiang Wan - Discrete Variable Representation Theory and Applications in Quantum Chemistry:

Molecules are made up of multiple atoms connected by bonds that are constantly changing in length, resulting in vibrational movement. Such intra-molecular motion fundamentally determines energy levels and wave functions of molecules, which is one of the main objectives in quantum chemistry. Mathematically, Schrödinger equation is used to model molecular vibrations, and therefore solving the equation (more precisely, understanding the Schrödinger operator), either analytically or numerically, is critical for us to understand these particles. In this talk, we will introduce the Discrete Variable Representation (DVR) method, which develops a finite dimensional approximation to the infinite dimensional Schrödinger operator and constructs a non-trivial basis for the associated matrix to be sparse (therefore making the computation feasible). We will explore the mathematical derivation of the finite dimensional matrices and applications of the DVR method on molecules of different sizes.