Lecture 6: Creating a simplicial complex from data. in a series of preparatory lectures for the Fall 2013 online course MATH:7450 (22M:305) Topics in Topology:

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Lecture 6: Creating a simplicial complex from data. in a series of preparatory lectures for the Fall 2013 online course MATH:7450 (22M:305) Topics in Topology: Scientific and Engineering Applications of Algebraic Topology Target Audience: Anyone interested in topological data analysis including graduate students, faculty, industrial researchers in bioinformatics, biology, business, computer science, cosmology, engineering, imaging, mathematics, neurology, physics, statistics, etc. Isabel K. Darcy Mathematics Department/Applied Mathematical & Computational Sciences University of Iowa

Creating a simplicial complex Step 0.) Start by adding 0-dimensional vertices (0-simplices)

Creating a simplicial complex Step 0.) Start by adding data points = 0-dimensional vertices (0-simplices)

Creating a simplicial complex 0.) Start by adding 0-dimensional data points Note: we only need a definition of closeness between data points. The data points do not need to be actual points in R n

Creating a simplicial complex 0.) Start by adding 0-dimensional data points Note: we only need a definition of closeness between data points. The data points do not need to be actual points in R n (1, 8) (1, 5) (2, 7)

Creating a simplicial complex 0.) Start by adding 0-dimensional data points Note: we only need a definition of closeness between data points. The data points do not need to be actual points in R n (dog, happy) (dog, content) (wolf, mirthful)

Creating a simplicial complex 1.) Adding 1-dimensional edges (1-simplices) Note: we only need a definition of closeness between data points. The data points do not need to be actual points in R n

Creating a simplicial complex 1.) Adding 1-dimensional edges (1-simplices) Add an edge between data points that are close

Creating a simplicial complex 1.) Adding 1-dimensional edges (1-simplices) Add an edge between data points that are close

Creating a simplicial complex 1.) Adding 1-dimensional edges (1-simplices) Let T = Threshold Connect vertices v and w with an edge iff the distance between v and w is less than T

Creating a simplicial complex 1.) Adding 1-dimensional edges (1-simplices) Let T = Threshold = Connect vertices v and w with an edge iff the distance between v and w is less than T

Creating a simplicial complex 1.) Adding 1-dimensional edges (1-simplices) Add an edge between data points that are close

Creating the Vietoris-Rips simplicial complex 2.) Add all possible simplices of dimensional > 1.

Creating the Vietoris Rips simplicial complex 2.) Add all possible simplices of dimensional > 1.

Step 0.) Start by adding data points = 0-dimensional vertices (0-simplices) Creating the Vietoris Rips simplicial complex

1.) Adding 1-dimensional edges (1-simplices) Add an edge between data points that are close Creating the Vietoris Rips simplicial complex

2.) Add 2-dimensional triangles (2-simplices) Add all possible 2-simplices. Creating the Vietoris Rips simplicial complex

3.) Add 3-dimensional tetrahedrons (3-simplices) Add all possible 3-simplices. Creating the Vietoris Rips simplicial complex

4.) Add 4-simplices Add all possible 4-simplices. Creating the Vietoris Rips simplicial complex

Step 0.) Start by adding data points = 0-dimensional vertices (0-simplices) Creating the Vietoris Rips simplicial complex

1.) Adding 1-dimensional edges (1-simplices) Add an edge between data points that are close Creating the Vietoris Rips simplicial complex

2.) Add all possible simplices of dimensional > 1.

Creating the Vietoris Rips simplicial complex Let T = Threshold = Connect vertices v and w with an edge iff the distance between v and w is less than T

0.) Start by adding 0-dimensional data points Note: we only need a definition of closeness between data points. The data points do not need to be actual points in R n Creating the Vietoris Rips simplicial complex

0.) Start by adding 0-dimensional data points Note: we only need a definition of closeness between data points. The data points do not need to be actual points in R n Creating the Vietoris Rips simplicial complex