21 Mar 2024
K. V. Shajesh
[video]
Punit recommended these two papers: by Berg and Marshall, and by Wilberforce, and a video.
Another related topic: Arnold tongue.
K. V. Shajesh
[video]
Punit recommended these two papers: by Berg and Marshall, and by Wilberforce, and a video.
Another related topic: Arnold tongue.
From https://www.youtube.com/watch?v=spUNpyF58BY |
Mohammad Sayeh
On Fourier and fractional Fourier transforms, and more.
Video of Part 1
Video of Part 2 (no sound...)
Mathew Gluck
Introduction to Principal Component Analysis
Abstract: Principal component analysis (PCA) is a data dimensionality reduction technique whose goal is to throw away the least essential components of a data set. It is commonly used by data science practitioners whose data belongs to a vector space of large dimensions. It is well-known that the eigenpairs of a suitable covariance matrix “know” which components of data are most important and which are least important. However, in many expositions on PCA, the reason behind this well-known fact is rarely explained. I will offer an explanation and I will show a concrete application of PCA in image data.
Philip Feinsilver
Symmetric functions: traces, determinants, the full story.
See references
From JK: This will be an opportunity to learn this topic in a novel and unique way. The presentation is planned for a few meetings. Do not miss them! You will be among the first few on the planet to get a new creative insight into the subject. Matrices in use!
A. Pasieka: Lorenz Attractor |
Mike Sullivan
Geometric Lorenz Attractor
Here are links sent by Mike:
Abstract of the talk: The Lorenz equations, developed and studied by the meteorologist Edward Lorenz in the 1960s, were one of the first examples of a chaotic system. They are a set of three nonlinear ordinary differential equations in three variables. The trajectories move toward a bounded subset of $\mathbb R^3$ and then seem to oscillate about, but never truly repeat. Mathematicians began studying these equations using both quantitative and qualitative methods. The former proved very difficult. The latter yielded results. Guckenheimer and Williams developed a geometric model with behavior similar to the Lorenz equations. Then Birman and Williams used topological methods to analyze this Geometric Lorenz Attractor. Decades later it was proved that the two systems are equivalent.
Participants should have had basic undergraduate courses in differential equations and linear algebra. We will begin with a review of systems of ordinary differential equations. This should last about 20 minutes. Then we will cover the construction of the Geometric Lorenz Attractor. That should take about 30 minutes. Next week we will cover Birman and Williams' proofs of the knot types of periodic orbits in the Geometric Lorenz Attractor.
This material was originally covered last Fall in my MATH 405 course. For now, you may wish to amuse yourself with this video.
Proto-topological (Quantum) Field Theories of Kijowski and SÅ‚awianowski
Video of Part 1
Video of Part 2
Video of Part 3
Abstract: Topological quantum field theories that are metric independent, like, e.g., Chern-Simons theory, give topological invariants of manifolds and knots. Classical field theories of Kijowski and SÅ‚awianowski are metric independent, and are defined on manifolds of a priori any dimension, and thus may give new topological invariants of manifolds.
In this talk, I will try to make a friendly introduction to these theories.
From Treewewal |
John McSorley
Graphs with trees of certain types, and related topics
Mohammad Sayeh
Neural networks and the global minimum problem
Video (there is a 20 min break in sound)
Micropatterning with sugar
(on surfaces, curvatures, and nanoscales)
2pm, Neckers 356