Current Research
My research interests have tended towards the intersection of
combinatorics, topology and geometry, with a primary focus on random
knots. I completed my PhD under the direction of Jason Cantarella.
Publications
Entries are also available in BibTeX format.

On the structure and scarcity of alternating knots.
Preprint: arXiv:1804.09780
Abstract:
Given a class of objects, a pattern theorem is a powerful result describing their structure. We show that alternating knots exhibit a pattern theorem, and use this result to prove a longstanding conjecture that alternating knots grow rare. This is currently the best possible analogue of a pair of theorems on alternating links of Sundberg and Thistlethwaite in 1998 and Thistlethwaite in 1998, given the current obstructions to an exact enumeration of knot diagrams. We also discuss implications of this pattern theorem for subknots and slipknots in minimal alternating knot diagrams and types, partially answering a conjecture of Millett and Jablan.

A Markov chain sampler for plane curves.
With Andrew Rechnitzer.
Preprint: arXiv:1804.03311
Abstract:
A plane curve is a knot diagram in which each crossing is replaced by a 4valent vertex, and so are dual to a subset of planar quadrangulations. The aim of this paper is to introduce a new tool for sampling diagrams via sampling of plane curves. At present the most efficient method for sampling diagrams is rejection sampling, however that method is inefficient at even modest sizes. We introduce Markov chains that sample from the space of plane curves using local moves based on Reidemeister moves. By then mapping vertices on those curves to crossings we produce random knot diagrams. Combining this chain with flat histogram methods we achieve an efficient sampler of plane curves and knot diagrams. By analysing data from this chain we are able to estimate the number of knot diagrams of a given size and also compute knotting probabilities and so investigate their asymptotic behaviour.

Slipknotting in random diagrams.
Preprint: arXiv:1803.07114
Abstract:
The presence of slipknots in configurations of proteins and DNA has been shown to affect their functionality, or alter it entirely. Historically, polymers are modeled as polygonal chains in space. As an alternative to space curves, we provide a framework for working with subknots inside of knot diagrams via knotoid diagrams. We prove using a pattern theorem for knot diagrams that not only are almost all knot diagrams slipknotted, almost all unknot diagrams are slipknotted. This proves in the random diagram model a conjecture yet unproven in random space curve models. We also discuss conjectures on the enumeration of knotoid diagrams.

A diagrammatic theory of random knots.
PhD thesis, University of Georgia.
Preprint available here
Abstract:
We study random knotting by considering knot and link diagrams as decorated, (rooted) topological maps on spheres and pulling them uniformly from among sets of a given number of vertices n. This model is an exciting new model which captures both the random geometry of space curve models of knotting as well as the ease of computing invariants from diagrams. This model of random knotting is similar to those studied by Diao et al., and Dunfield et al. We prove that unknot diagrams are asymptotically exponentially rare, an analogue of Sumners and Whittington's result for selfavoiding walks. Our proof uses the same idea: We first show that knot diagrams obey a pattern theorem and exhibit fractal structure. We use a rejection sampling method to present experimental data showing that these asymptotic results occur quickly, and compare parallels to other models of random knots. We finish by providing a number of extensions to the diagram model. The diagram model can be used to study embedded graph theory, open knot theory, virtual knot theory, and even random knots of fixed type. In this latter scenario, we prove a result still unproven for other models of random knotting. We additionally discuss an alternative method for randomly sampling diagrams via a Markov chain Monte Carlo method.

Asymptotic laws for random knot diagrams.
Journal of Physics A: Mathematical and Theoretical 50 (2017),
no. 22, p. 225001.
DOI: 10.1088/17518121/aa6e45
Preprint: arXiv:1608.02638
Abstract:
We study random knotting by considering knot and link diagrams as decorated, (rooted) topological maps on spheres and pulling them uniformly from among sets of a given number of vertices n, as first established in recent work with Cantarella and Mastin. The knot diagram model is an exciting new model which captures both the random geometry of space curve models of knotting as well as the ease of computing invariants from diagrams. We prove that unknot diagrams are asymptotically exponentially rare, an analogue of Sumners and Whittington’s landmark result for selfavoiding polygons. Our proof uses the same key idea: we first show that knot diagrams obey a pattern theorem, which describes their fractal structure. We examine how quickly this behavior occurs in practice. As a consequence, almost all diagrams are asymmetric, simplifying sampling from this model. We conclude with experimental data on knotting in this model. This model of random knotting is similar to those studied by Diao et al, and Dunfield et al.

Knot probabilities in random diagrams.
With Jason Cantarella and Matt Mastin.
Journal of Physics A: Mathematical and Theoretical 49 (2016),
no. 40, p. 405001.
DOI: 10.1088/17518113/49/40/405001
Preprint: arXiv:1512.05749
Abstract:
We consider a natural model of random knotting—choose a knot diagram at random from the finite set of diagrams with n crossings. We tabulate diagrams with 10 and fewer crossings and classify the diagrams by knot type, allowing us to compute exact probabilities for knots in this model. As expected, most diagrams with 10 and fewer crossings are unknots (about 78% of the roughly 1.6 billion 10 crossing diagrams). For these crossing numbers, the unknot fraction is mostly explained by the prevalence of ‘treelike’ diagrams which are unknots for any assignment of over/under information at crossings. The data shows a roughly linear relationship between the log of knot type probability and the log of the frequency rank of the knot type, analogous to Zipf’s law for word frequency. The complete tabulation and all knot frequencies are included as supplementary data.
Talks
External

A Markov chain sampler for knot diagrams.
Special Session on Mathematical Methods for the Study of the Three Dimensional Structure of Biopolymers (AMS Fall Western Sectional Meeting 2018).
San Francisco State University, San Francisco, CA, October 2018.

Slipknots in unknot diagrams.
2018 Summer Conference on Topology and its Applications.
Western Kentucky University, Bowling Green, KY, July 2018.

Random Knot Diagrams: New results on open questions.
Deguchi Laboratory Seminar.
Ochanomizu University, Tokyo, Japan, May 2018.

Monte Carlo sampling of knot diagrams (workshop tutorial).
Approximate Enumeration of Polygons, Polymers and Link Diagrams.
University of British Columbia, Vancouver, BC, March 2018.

An efficient Markov chain sampler for plane curves.
Discrete Math Seminar.
University of British Columbia, Vancouver, BC, March 2018.

Slipknotting in random knot diagrams.
The Geometry and Topology of Knotting and Entanglement in Proteins.
Casa Matematica Oaxaca (CMO), Oaxaca, Mexico, November 2017.
Video available here.

A SumnersWhittington result for knot diagrams.
Means, Methods, and Results in the Statistical Mechanics of Polymeric Systems II.
Fields Institute, Toronto, ON, June 2017.
Video available here.

A Markov chain sampler for knot diagrams.
Special Session on Invariants of Knots, Links, and 3manifolds (AMS Spring Eastern Sectional Meeting 2017).
Hunter College, New York, NY, May 2017.

Slipknotting in the Knot Diagram Model.
Special Session on Knot Theory and its Applications (AMS Spring Southeast Sectional Meeting 2017).
College of Charleston, Charleston, SC, March 2017.

Slipknotting in the Knot Diagram Model.
MAA Invited Paper Session on Random Polygons and Knots (Joint Mathematics Meetings 2017).
Atlanta, GA, January 2017.

Random knots in physics and biology.
Annual Math and Physics Lecture.
Piedmont College, Demorest, GA, November 2016.

Asymptotic laws for knot diagrams.
28th International Conference on Formal Power Series and Algebraic Combinatorics.
Vancouver, BC, July 2016.

Asymptotic laws for knot diagrams.
Graduate Student Topology and Geometry Conference 2016.
IU Bloomington, Bloomington, IN, April 2016.

A roboticsbased calculus class.
MAA Session on Mathematical Modeling in the Undergraduate Classroom (Joint Mathematics Meetings 2016).
Seattle, WA, January 2016.

Asymptotic laws for knot diagrams.
AMS Session on General Topics (Joint Mathematics Meetings 2016).
Seattle, WA, January 2016.

Asymptotic laws for knot diagrams.
Geometry Seminar.
Tulane University, New Orleans, LA, October 2015.

Asymptotics of random knot diagrams.
Special Session on Algebraic and Combinatorial Structures in Knot Theory (AMS Fall Western Sectional Meetings 2015).
CSU Fullerton, Fullerton, CA, October 2015.

Asymptotics of random knot diagrams.
Special Session on Topological Combinatorics (AMS Fall Southeastern Sectional Meetings 2015).
University of Memphis, Memphis, TN, October 2015.

Asymptotic laws for knot diagrams.
Discrete Math Seminar.
University of British Columbia, Vancouver, BC, September 2015.

Asymptotic laws for knot diagrams.
Discrete Math Seminar.
Simon Fraser University, Burnaby, BC, September 2015.

Knot diagrams and blossom trees.
PIMSUSASK Graduate Summer School on Applied Combinatorics.
University of Saskatchewan, Saskatoon, SK, May 2015.

Random knot diagrams.
Special Session on Inverse Problems and Related Mathematical Methods in Physics (AMS Spring Western Sectional Meetings).
University of Nevada, Las Vegas, NV, April 2015.

Packets, Solving Symmetries, and Sudoku.
With Malcolm Rupert.
AMSMAASIAM Special Session on Research in Mathematics by Undergraduates and Students in PostBaccalaureate Programs (Joint Mathematics Meetings 2011).
New Orleans, LA, January 2011.

Packets, Solving Symmetries, and Sudoku.
With Malcolm Rupert.
Young Mathematicians Conference.
The Ohio State University, Columbus, OH, August 2010.
Internal

Statistical mechanics of knot diagrams.
Postdoc Seminar.
Colorado State University, Fort Collins, CO, March 2018.

A Markov chain Monte Carlo sampler for knot diagrams.
Geometry Seminar.
University of Georgia, Athens, GA, March 2017.

Patterns in knot diagrams.
Geometry Seminar.
University of Georgia, Athens, GA, August 2016.

The quantum harmonic oscillator.
Geometry Seminar.
University of Georgia, Athens, GA, October 2015.

Asymptotic laws for knot diagrams.
Geometry Seminar.
University of Georgia, Athens, GA, September 2015.

How to count (a quick glance at analytic combinatorics).
Graduate Student Seminar.
University of Georgia, Athens, GA, September 2015.

Asymptotics of knot and link diagrams.
Mock AMS Conference.
University of Georgia, Athens, GA, July 2015.

Virtual Knot Theory.
Graduate Student Seminar.
University of Georgia, Athens, GA, February 2015.

Random Planar Diagrams.
Geometry Seminar.
University of Georgia, Athens, GA, January 2014.

The Poincaré homolgy sphere as the link of a singularity.
Graduate Student Topology Seminar.
University of Georgia, Athens, GA, November 2014.

Discrete Ricci Flow.
Research Group on Minimal Surfaces.
University of Georgia, Athens, GA, November 2014.

The Tropical Grassmannian.
Mock AMS Conference.
University of Georgia, Athens, GA, June 2014.

Hope for slackers: Playing games to prove theorems.
Mock AMS Conference.
University of Georgia, Athens, GA, June 2013.

The Classification of Surfaces.
Mock AMS Conference.
University of Georgia, Athens, GA, June 2012.

Vinogradov's generalization of a theorem of AubryThue.
VIGRE Research Group on Minkowski's Geometry of Numbers.
University of Georgia, Athens, GA, March 2012.
Previous Research