Journal of Applied and Computational Topology

Aims & Scope

Recent years have witnessed a substantial increase in the use of methods from algebraic and combinatorial topology in research within sciences and engineering, including in data analysis, visualization, image processing, robotics, and more broadly in theoretical computer science, biology, medicine, and social sciences.

Frequently, structural topological insights are needed in the discovery and analysis of fundamental mechanisms in applications.

The investigation of large data sets often requires development of new algorithms, which in turn depend on mathematical insights.

The Journal of Applied and Computational Topology is devoted to publishing high-quality research articles bridging algebraic and combinatorial topology on the one side and science and engineering on the other.

It aims to serve both mathematicians and users of mathematical methods.

We invite research contributions: from within the sciences, with focus on essential uses of topological methods and, from within topology, with a strong applied component or motivation from science and engineering.

We particularly encourage the submission of topical surveys and expository articles.

View Aims & Scope

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Metrics & Ranking

Journal Rank

Year	Value
2024	5121

Journal Citation Indicator

Year	Value
2024	170

SJR (SCImago Journal Rank)

Year	Value
2024	0.966

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	17

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Mathematics, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Ripser: efficient computation of Vietoris–Rips persistence barcodes

  Citation: 185

  Authors: Ulrich

• Persistence diagrams with linear machine learning models

  Citation: 94

  Authors: Ippei, Yasuaki, Masao

• Topology of random geometric complexes: a survey

  Citation: 77

  Authors: Omer, Matthew

• Functional summaries of persistence diagrams

  Citation: 55

  Authors: Eric, Yen-Chi, Jessi, Brittany Terese

• Hypothesis testing for topological data analysis

  Citation: 47

  Authors: Andrew, Katharine

• Toward a spectral theory of cellular sheaves

  Citation: 46

  Authors: Jakob, Robert

• Generalized persistence diagrams

  Citation: 44

  Authors: Amit

• Understanding the topology and the geometry of the space of persistence diagrams via optimal partial transport

  Citation: 35

  Authors: Vincent, Théo

• Persistent homology and microlocal sheaf theory

  Citation: 33

  Authors: Masaki, Pierre

• A functorial Dowker theorem and persistent homology of asymmetric networks

  Citation: 32

  Authors: Samir, Facundo

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