Finding Good Coordinates for Sampling: The Importance of Geometry
Sep 06, 20241650
Matrix Optimization Informed by Geometric Invariant Theory and Symplectic Geometry
Jul 15, 20242040
Optimization Informed by Geometric Invariant Theory and Symplectic Geometry
May 22, 20243140
Math 105
Apr 12, 20242420
Complex Analysis
Mar 27, 20242490
Generating (and Computing with) Very Large Ensembles of Random Polygonal Knots
Mar 26, 20242860
Optimization and Normal Matrices
Mar 18, 20242920
RMHS
Mar 06, 20242290
Geometric Approaches to Frame Theory
Nov 10, 20233550
Introduction to Knot Theory
Oct 02, 20233010
Frames as Loops
Sep 27, 20233560
Applications of Grassmannians and Flag Manifolds
Jul 06, 20234480
Frames, Optimization, and Geometric Invariant Theory
Apr 10, 20235191
Hodge and Gelfand Theory in Clifford Analysis and Tomography
Aug 22, 20226700
Topological Polymers and Random Embeddings of Graphs
Aug 16, 20226630
Finding Good Coordinates for Sampling Configuration Spaces
Mar 17, 20229030
Geometric Approaches to Frame Theory
Mar 16, 20228940
Geometric Approaches to Frame Theory
Feb 24, 20228960
Animations
Dec 08, 20217760
Some Applications of Symplectic Geometry
Nov 16, 20211,0660
A Lie Algebraic Perspective on Frame Theory
Oct 05, 20211,0120
Random Graph Embeddings with General Edge Potentials
Sep 28, 20211,0930
What is a Random Knot? And Why Do We Care?
Sep 23, 20211,0120
The (Symplectic) Geometry of Spaces of Frames
Feb 19, 20211,3690
Generating (and Computing with) Very Large Ensembles of Random Polygonal Knots
Jan 10, 20211,2060
An Introduction to Symplectic Geometry and Some Applications
Oct 17, 20201,5900
New Stick Number Bounds from Random Sampling of Confined Polygons
Oct 03, 20201,5660
What is (Applied) Symplectic Geometry?
Sep 27, 20201,4710
New Stick Number Bounds from Random Sampling of Confined Polygons
Mar 08, 20202,1510
Hamiltonian Group Actions on Frame Spaces
Jan 09, 20201,5350
Modeling Topological Polymers
Sep 26, 20191,6710
Symplectic Geometry and Frame Theory
Jul 03, 20191,8100
Stiefel Manifolds and Polygons
Jul 01, 20192,2370
Visualizing Higher Dimensions
Jun 14, 20192,4130
Tensors in Differential Geometry
Jun 02, 20192,5722
Symplectic Geometry and Frame Theory
Jan 21, 20191,7290
Using Differential Geometry to Model Complex Biopolymers
Jan 14, 20192,1390
What’s the Probability a Random Triangle is Obtuse?
For MATH 161
Dec 05, 20181,4140
What’s the Probability a Random Triangle is Obtuse?
An Introduction to Geometric Probability, Shape Spaces, Group Actions, and Grassmannians
Nov 19, 20182,3880
Modeling Topological Polymers
Nov 04, 20181,7330
Symplectic Geometry and Frame Theory
Oct 31, 20181,5430
The Geometry of Topologically Constrained Random Walks
Oct 14, 20182,3220
Symplectic Geometry and Frame Theory
Sep 24, 20181,6050
Random Walks are Almost Closed
Loop closure is surprisingly non-destructive
Jul 12, 20181,7720
Random Walks are Almost Closed
Loop closure is surprisingly non-destructive
Apr 19, 20181,8930
Equilateral Polygons, Shapes of Ring Polymers, and an Application to Frame Theory
Random flights in 3-space forming a closed loop, or random polygons, are a standard simplified model of so-called ring polymers like bacterial DNA. Equilateral random polygons, where all steps are the same length, are particularly interesting (and challenging) in this context. In this talk I will describe an (almost) toric Kähler structure on the moduli space of equilateral polygons and show how to exploit this structure to get a fast algorithm to directly sample the space. Using work of Hausmann–Knutson, the Kähler structure on the space of equilateral polygons can be realized as the Kähler reduction of the standard Kähler structure on the Grassmannian of 2-planes in complex n-space. This means that equilateral polygons in 3-space can be lifted to Finite Unit-Norm Tight Frames (FUNTFs) in complex 2-space. I will describe how to modify the polygon sampler to produce a FUNTF sampler and show that optimal packings in the 2-sphere lift to FUNTFs with low coherence.
Mar 12, 20181,9640
From random walks to closed polygons
A natural map from random walks to equilateral polygons in any dimension
Nov 04, 20172,2150
A Geometric Approach to Sampling Loop Random Flights
In statistical physics, the basic (and highly idealized) model of a ring polymer like bacterial DNA is a closed random flight in 3-space with equal-length steps, often called an equilateral random polygon. While random flights without the closure condition are easy to simulate and analyze, the fact that the steps in a random polygon are not independent has made it challenging to develop practical yet provably correct sampling and numerical integration techniques for polygons. In this talk I will describe a geometric approach to the study of random polygons which overcomes these challenges. The symplectic geometry of the space of polygon conformations can be exploited to produce both Markov chain and direct sampling algorithms; in fact, this approach can be generalized to produce a sampling theory for arbitrary toric symplectic manifolds. This is joint work with Jason Cantarella, Bertrand Duplantier, and Erica Uehara.
Oct 18, 20172,1100
The Geometry of Polygon Space
Acute triangles, convex quadrilaterals, flag means, and more