Toroidal Coordinates: Decorrelating Circular Coordinates with Lattice Reduction

Authors Luis Scoccola , Hitesh Gakhar , Johnathan Bush , Nikolas Schonsheck , Tatum Rask, Ling Zhou , Jose A. Perea

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Author Details

Luis Scoccola
  • Department of Mathematics, Northeastern University, Boston, MA, USA
Hitesh Gakhar
  • Department of Mathematics, The University of Oklahoma, Norman, OK, USA
Johnathan Bush
  • Department of Mathematics, University of Florida, Gainesville, FL, USA
Nikolas Schonsheck
  • Department of Mathematical Sciences, University of Delaware, Newark, DE, USA
Tatum Rask
  • Department of Mathematics, Colorado State University, Fort Collins, CO, USA
Ling Zhou
  • Department of Mathematics, The Ohio State University, Columbus, OH, USA
Jose A. Perea
  • Department of Mathematics and Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA

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Luis Scoccola, Hitesh Gakhar, Johnathan Bush, Nikolas Schonsheck, Tatum Rask, Ling Zhou, and Jose A. Perea. Toroidal Coordinates: Decorrelating Circular Coordinates with Lattice Reduction. In 39th International Symposium on Computational Geometry (SoCG 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 258, pp. 57:1-57:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


The circular coordinates algorithm of de Silva, Morozov, and Vejdemo-Johansson takes as input a dataset together with a cohomology class representing a 1-dimensional hole in the data; the output is a map from the data into the circle that captures this hole, and that is of minimum energy in a suitable sense. However, when applied to several cohomology classes, the output circle-valued maps can be "geometrically correlated" even if the chosen cohomology classes are linearly independent. It is shown in the original work that less correlated maps can be obtained with suitable integer linear combinations of the cohomology classes, with the linear combinations being chosen by inspection. In this paper, we identify a formal notion of geometric correlation between circle-valued maps which, in the Riemannian manifold case, corresponds to the Dirichlet form, a bilinear form derived from the Dirichlet energy. We describe a systematic procedure for constructing low energy torus-valued maps on data, starting from a set of linearly independent cohomology classes. We showcase our procedure with computational examples. Our main algorithm is based on the Lenstra-Lenstra-Lovász algorithm from computational number theory.

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Algebraic topology
  • dimensionality reduction
  • lattice reduction
  • Dirichlet energy
  • harmonic
  • cocycle


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