Balancing Graphs Using Geometric Invariant Theory

Finding Good Coordinates for Sampling: The Importance of Geometry

Matrix Optimization Informed by Geometric Invariant Theory and Symplectic Geometry

Optimization Informed by Geometric Invariant Theory and Symplectic Geometry

Math 105

Complex Analysis

Generating (and Computing with) Very Large Ensembles of Random Polygonal Knots

Optimization and Normal Matrices

RMHS

Geometric Approaches to Frame Theory

Introduction to Knot Theory

Frames as Loops

Applications of Grassmannians and Flag Manifolds

Frames, Optimization, and Geometric Invariant Theory

Hodge and Gelfand Theory in Clifford Analysis and Tomography

Topological Polymers and Random Embeddings of Graphs

Finding Good Coordinates for Sampling Configuration Spaces

Geometric Approaches to Frame Theory

Geometric Approaches to Frame Theory

Animations

Some Applications of Symplectic Geometry

A Lie Algebraic Perspective on Frame Theory

Random Graph Embeddings with General Edge Potentials

What is a Random Knot? And Why Do We Care?

The (Symplectic) Geometry of Spaces of Frames

Generating (and Computing with) Very Large Ensembles of Random Polygonal Knots

An Introduction to Symplectic Geometry and Some Applications

New Stick Number Bounds from Random Sampling of Confined Polygons

What is (Applied) Symplectic Geometry?

New Stick Number Bounds from Random Sampling of Confined Polygons

Hamiltonian Group Actions on Frame Spaces

Modeling Topological Polymers

Symplectic Geometry and Frame Theory

Stiefel Manifolds and Polygons

Visualizing Higher Dimensions

Tensors in Differential Geometry

Symplectic Geometry and Frame Theory

Using Differential Geometry to Model Complex Biopolymers

What’s the Probability a Random Triangle is Obtuse?

For MATH 161

What’s the Probability a Random Triangle is Obtuse?

An Introduction to Geometric Probability, Shape Spaces, Group Actions, and Grassmannians

Modeling Topological Polymers

Symplectic Geometry and Frame Theory

The Geometry of Topologically Constrained Random Walks

Symplectic Geometry and Frame Theory

Random Walks are Almost Closed

Loop closure is surprisingly non-destructive

Random Walks are Almost Closed

Loop closure is surprisingly non-destructive

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.

From random walks to closed polygons

A natural map from random walks to equilateral polygons in any dimension

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.

The Geometry of Polygon Space

Acute triangles, convex quadrilaterals, flag means, and more