Metric geometry of spaces of persistence diagrams

Persistence diagrams are objects that play a central role in topological data analysis. In the present article, we investigate the local and global geometric properties of spaces of persistence diagrams. In order to do this, we construct a family of functors <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>D</mml:mi> <mml:mi>p</mml:mi></mml:msub> </mml:math> , <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>1</mml:mn> <mml:mo>≤</mml:mo> <mml:mi>p</mml:mi> <mml:mo>≤</mml:mo> <mml:mi>∞</mml:mi></mml:mrow> </mml:math> , that assign, to each metric pair (<i>X</i>, <i>A</i>), a pointed metric space <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msub><mml:mi>D</mml:mi> <mml:mi>p</mml:mi></mml:msub> <mml:mrow><mml:mo>(</mml:mo> <mml:mi>X</mml:mi> <mml:mo>,</mml:mo> <mml:mi>A</mml:mi> <mml:mo>)</mml:mo></mml:mrow> </mml:mrow> </mml:math> . Moreover, we show that <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>D</mml:mi> <mml:mi>∞</mml:mi></mml:msub> </mml:math> is sequentially continuous with respect to the Gromov-Hausdorff convergence of metric pairs, and we prove that <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>D</mml:mi> <mml:mi>p</mml:mi></mml:msub> </mml:math> preserves several useful metric properties, such as completeness and separability, for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>p</mml:mi> <mml:mo>∈</mml:mo> <mml:mo>[</mml:mo> <mml:mn>1</mml:mn> <mml:mo>,</mml:mo> <mml:mi>∞</mml:mi> <mml:mo>)</mml:mo></mml:mrow> </mml:math> , and geodesicity and non-negative curvature in the sense of Alexandrov, for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>p</mml:mi> <mml:mo>=</mml:mo> <mml:mn>2</mml:mn></mml:mrow> </mml:math> . For the latter case, we describe the metric of the space of directions at the empty diagram. We also show that the Fréchet mean set of a Borel probability measure on <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msub><mml:mi>D</mml:mi> <mml:mi>p</mml:mi></mml:msub> <mml:mrow><mml:mo>(</mml:mo> <mml:mi>X</mml:mi> <mml:mo>,</mml:mo> <mml:mi>A</mml:mi> <mml:mo>)</mml:mo></mml:mrow> </mml:mrow> </mml:math> , <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>1</mml:mn> <mml:mo>≤</mml:mo> <mml:mi>p</mml:mi> <mml:mo>≤</mml:mo> <mml:mi>∞</mml:mi></mml:mrow> </mml:math> , with finite second moment and compact support is non-empty. As an application of our geometric framework, we prove that the space of Euclidean persistence diagrams, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msub><mml:mi>D</mml:mi> <mml:mi>p</mml:mi></mml:msub> <mml:mrow><mml:mo>(</mml:mo> <mml:msup><mml:mrow><mml:mi>R</mml:mi></mml:mrow> <mml:mrow><mml:mn>2</mml:mn> <mml:mi>n</mml:mi></mml:mrow> </mml:msup> <mml:mo>,</mml:mo> <mml:msub><mml:mi>Δ</mml:mi> <mml:mi>n</mml:mi></mml:msub> <mml:mo>)</mml:mo></mml:mrow> </mml:mrow> </mml:math> , <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>1</mml:mn> <mml:mo>≤</mml:mo> <mml:mi>n</mml:mi></mml:mrow> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>1</mml:mn> <mml:mo>≤</mml:mo> <mml:mi>p</mml:mi> <mml:mo><</mml:mo> <mml:mi>∞</mml:mi></mml:mrow> </mml:math> , has infinite covering, Hausdorff, asymptotic, Assouad, and Assouad-Nagata dimensions.

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Journal
Journal of Applied and Computational Topology
Published
2024-09-03
DOI
https://doi.org/10.1007/s41468-024-00189-2
Citations
6
Primary Topic
Topological and Geometric Data Analysis
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article
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1.81

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article

Metric geometry of spaces of persistence diagrams

Ingrid Amaranta Membrillo Solis, Mauricio Che, Luis Guijarro, Fernando Galaz‐García
6 citations
Journal of Applied and Computational Topology
Topological and Geometric Data Analysis
1.81
article

Metric geometry of spaces of persistence diagrams

Ingrid Amaranta Membrillo Solis, Mauricio Che, Luis Guijarro, Fernando Galaz‐García
article en
6 citations

Abstract

Persistence diagrams are objects that play a central role in topological data analysis. In the present article, we investigate the local and global geometric properties of spaces of persistence diagrams. In order to do this, we construct a family of functors <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>D</mml:mi> <mml:mi>p</mml:mi></mml:msub> </mml:math> , <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>1</mml:mn> <mml:mo>≤</mml:mo> <mml:mi>p</mml:mi> <mml:mo>≤</mml:mo> <mml:mi>∞</mml:mi></mml:mrow> </mml:math> , that assign, to each metric pair (<i>X</i>, <i>A</i>), a pointed metric space <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msub><mml:mi>D</mml:mi> <mml:mi>p</mml:mi></mml:msub> <mml:mrow><mml:mo>(</mml:mo> <mml:mi>X</mml:mi> <mml:mo>,</mml:mo> <mml:mi>A</mml:mi> <mml:mo>)</mml:mo></mml:mrow> </mml:mrow> </mml:math> . Moreover, we show that <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>D</mml:mi> <mml:mi>∞</mml:mi></mml:msub> </mml:math> is sequentially continuous with respect to the Gromov-Hausdorff convergence of metric pairs, and we prove that <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>D</mml:mi> <mml:mi>p</mml:mi></mml:msub> </mml:math> preserves several useful metric properties, such as completeness and separability, for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>p</mml:mi> <mml:mo>∈</mml:mo> <mml:mo>[</mml:mo> <mml:mn>1</mml:mn> <mml:mo>,</mml:mo> <mml:mi>∞</mml:mi> <mml:mo>)</mml:mo></mml:mrow> </mml:math> , and geodesicity and non-negative curvature in the sense of Alexandrov, for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>p</mml:mi> <mml:mo>=</mml:mo> <mml:mn>2</mml:mn></mml:mrow> </mml:math> . For the latter case, we describe the metric of the space of directions at the empty diagram. We also show that the Fréchet mean set of a Borel probability measure on <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msub><mml:mi>D</mml:mi> <mml:mi>p</mml:mi></mml:msub> <mml:mrow><mml:mo>(</mml:mo> <mml:mi>X</mml:mi> <mml:mo>,</mml:mo> <mml:mi>A</mml:mi> <mml:mo>)</mml:mo></mml:mrow> </mml:mrow> </mml:math> , <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>1</mml:mn> <mml:mo>≤</mml:mo> <mml:mi>p</mml:mi> <mml:mo>≤</mml:mo> <mml:mi>∞</mml:mi></mml:mrow> </mml:math> , with finite second moment and compact support is non-empty. As an application of our geometric framework, we prove that the space of Euclidean persistence diagrams, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow><mml:msub><mml:mi>D</mml:mi> <mml:mi>p</mml:mi></mml:msub> <mml:mrow><mml:mo>(</mml:mo> <mml:msup><mml:mrow><mml:mi>R</mml:mi></mml:mrow> <mml:mrow><mml:mn>2</mml:mn> <mml:mi>n</mml:mi></mml:mrow> </mml:msup> <mml:mo>,</mml:mo> <mml:msub><mml:mi>Δ</mml:mi> <mml:mi>n</mml:mi></mml:msub> <mml:mo>)</mml:mo></mml:mrow> </mml:mrow> </mml:math> , <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>1</mml:mn> <mml:mo>≤</mml:mo> <mml:mi>n</mml:mi></mml:mrow> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>1</mml:mn> <mml:mo>≤</mml:mo> <mml:mi>p</mml:mi> <mml:mo><</mml:mo> <mml:mi>∞</mml:mi></mml:mrow> </mml:math> , has infinite covering, Hausdorff, asymptotic, Assouad, and Assouad-Nagata dimensions.

Journal of Applied and Computational TopologyVol. 8(8)
Queen Mary University of London (GB), Durham University (GB), Institute of Mathematical Sciences (ES), University of Southampton (GB), Universidad Carlos III de Madrid (ES), Universidad Autónoma de Madrid (ES)
Instituto de Ciencias Matemáticas, Leverhulme Trust, Durham University, Consejo Nacional de Ciencia y Tecnología, Ministerio de Economía y Competitividad, Ministerio de Ciencia e Innovación, European Research Council, Division of Mathematical Sciences
Openalex Percentile: Top 13%
Topological and Geometric Data Analysis
1.81
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