Math Club

– This Week –

Compressed Sensing
Consider the linear equation: $y = A x^{*}$, where $A \in \mathbb{R}^{n \times d}$ and $y \in \mathbb{R}^{n}$ are known, and $x^{*} \in \mathbb{R}^{d}$ is the unknown. Assuming $n \ll d$, the system is underdetermined. However, if $x^{*}$ is sparse, meaning it has only a few nonzero components, it can be recovered using computationally efficient algorithms.

In this talk, we explore this problem, known as compressed sensing, and discuss the basis pursuit algorithm and the restricted isometry property for exact recovery.

Welcome to the Math Club home page!

The math club meets once a week in the Winter term, on Thursday evenings for about an hour. It is intended for anyone interested in mathematics, whether they are a math major or not.

At each meeting a speaker will discuss an interesting idea in mathematics. We try to pick topics that can be understood without much background. An ideal topic is one which starts with something simple, and by exploring its twists and turns, leads to something unexpectedly deeper.

The goal is to show mathematics the way that mathematicians see it: a living subject full of deep and intertwining ideas, growing naturally out of our desire to understand the fundamental concepts of space and number.

  Date Topic Speaker
Jan. 23   The $2$-adic logarithm M. Ram Murty
30   Domino Tilings Gregory G. Smith
Feb. 6   Pseudorandom number generation and the NSA backdoor Mike Roth
13   Conway's Winning Ways Jamie Mingo
27   Kuratowski's closure-complement problem Ivan Dimitrov
Mar. 6   Left orders on Groups Thomas Barthelmé
13   Ultrafilters and Ramsey Theory Francesco Cellarosi
20   Compressed Sensing Yanglei Song
27   The Permanent Bahman Gharesifard
Apr. 3   TBA Teresa Chiri

The meetings are Thursdays in Jeff 118 from 17:30–18:30.

To suggest a topic for the Math Club, or to find out further information, please email Ivan Dimitrov, Mike Roth, or Greg Smith .

 
Web Site of the Week
Check out Quanta Magazine; an online science magazine specializing in Mathematics, Physics, and the Life Sciences.