Courses: ongoing
The following courses were scheduled for the ongoing academic year:
The following courses were scheduled for the ongoing academic year:
Sven Bachmann : sbach@math.ubc.ca
University of British Columbia
Solid foundation in linear algebra, rigorous analysis (at the level of `baby Rudin’) and elementary point set topology. Knowledge in functional analysis and measure theory is an advantage, but the necessary material will be reviewed. No physics background beyond high school physics required.
UBC MATH320 and MATH321 (or equivalent)
UBC MATH420 and MATH421 (or equivalent) are recommended but not required.
Registration for this course is not currently available.
The goal of MATH 512 is to introduce mathematical methods of quantum theory. No prerequisite of quantum physics is required. The course will cover some aspects of functional analysis, operator theory and the calculus of variations with short excursions into representation theory and operator algebras. The physical axioms of quantum theory will be introduced and elementary results will be discussed. We will introduce the Hilbert space formulation of quantum theory, discuss quantum dynamics and its relation to spectral properties of linear operators. We will also study the role of symmetries in quantum physics, in particular the rotation group thereby introducing the intrinsically quantum notion of spin. The course will conclude with a short study of strongly interacting systems and the role of locality in their analysis.
First day of teaching: Wed Sep 09; Last day of teaching: Monday Dec 07. University closed Sep 30, Oct 12, and Nov 11. Midterm break: Nov 09-11.
This will be a hybrid course delivered by Zoom. The instructor will lecture at a blackboard using a camera to allow remote participants to see the content. There will be course notes (hand written, possibly typed up) made available as the course progresses. Office hours will be conducted over zoom.
This course may be open to students from universities outside of the PIMS network, and those coming from industry/government.
There will be
The course grade will be given by $$ \max \left\{ 0.75G_H + 0.25G_F, 0.5G_H + 0.5G_F \right\} $$ where $G_H$ is the average grade of the assignments and $G_F$ is the grade of the final exam.
Andrei Volodin : andrei.volodin@uregina.ca
University of Regina
This is a graduate course, so there are no prerequisites. At the same time, students should know probability and statistics (especially linear regression) at an intermediate level.
Registration for this course is not currently available.
This course aims to introduce various statistical models for time series and cover the main methods for analysis and forecasting. Topics include: Deterministic time series: Trends and Seasonality; Random walk models; Stationary time series: White noise processes, Autoregressive (AR), Moving Average (MA), Autoregressive Moving Average (ARMA) models; Estimation, Diagnosis and Forecasting with various time series models; computer programming for Time Series Analysis.
Tuesday and Thursday 10:00 - 11:15 a.m. in CL 305 and remotely on Zoom (see syllabus)
There are 8 asynchronous computer labs, starting on Sept. 16
Please note that these times above are in the Saskatchewan timezone and that Saskatchewan doesn’t participate in daylight savings.
This will be a hybrid course delivered by Zoom. The instructor will share the existing electronic presentation and will use a laptop (or tablet), which can be shared electronically for some special notes during lectures.
This course may be open to students from universities outside of the PIMS network, and those coming from industry/government.
Your final grade will be calculated as follows: