{"title":"持久梅耶同调和持久梅耶拉普拉斯。","authors":"Li Shen, Jian Liu, Guo-Wei Wei","doi":"10.3934/fods.2024032","DOIUrl":null,"url":null,"abstract":"<p><p>In algebraic topology, the differential (i.e., boundary operator) typically satisfies <math> <msup><mrow><mi>d</mi></mrow> <mrow><mn>2</mn></mrow> </msup> <mo>=</mo> <mn>0</mn></math> . However, the generalized differential <math> <msup><mrow><mi>d</mi></mrow> <mrow><mi>N</mi></mrow> </msup> <mo>=</mo> <mn>0</mn></math> for an integer <math><mi>N</mi> <mo>≥</mo> <mn>2</mn></math> has been studied in terms of Mayer homology on <math><mi>N</mi></math> -chain complexes for more than eighty years. We introduce Mayer Laplacians on <math><mi>N</mi></math> -chain complexes. We show that both Mayer homology and Mayer Laplacians offer considerable application potential, providing topological and geometric insights to spaces. We also introduce persistent Mayer homology and persistent Mayer Laplacians at various <math><mi>N</mi></math> . The bottleneck distance and stability of persistence diagrams associated with Mayer homology are investigated. Our computational experiments indicate that the topological features offered by persistent Mayer homology and spectrum given by persistent Mayer Laplacians hold substantial promise for large, complex, and diverse data. We envision that the present work serves as an inaugural step towards integrating Mayer homology and Mayer Laplacians into the realm of topological data analysis.</p>","PeriodicalId":73054,"journal":{"name":"Foundations of data science (Springfield, Mo.)","volume":"6 4","pages":"584-612"},"PeriodicalIF":1.4000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467518/pdf/","citationCount":"0","resultStr":"{\"title\":\"PERSISTENT MAYER HOMOLOGY AND PERSISTENT MAYER LAPLACIAN.\",\"authors\":\"Li Shen, Jian Liu, Guo-Wei Wei\",\"doi\":\"10.3934/fods.2024032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In algebraic topology, the differential (i.e., boundary operator) typically satisfies <math> <msup><mrow><mi>d</mi></mrow> <mrow><mn>2</mn></mrow> </msup> <mo>=</mo> <mn>0</mn></math> . However, the generalized differential <math> <msup><mrow><mi>d</mi></mrow> <mrow><mi>N</mi></mrow> </msup> <mo>=</mo> <mn>0</mn></math> for an integer <math><mi>N</mi> <mo>≥</mo> <mn>2</mn></math> has been studied in terms of Mayer homology on <math><mi>N</mi></math> -chain complexes for more than eighty years. We introduce Mayer Laplacians on <math><mi>N</mi></math> -chain complexes. We show that both Mayer homology and Mayer Laplacians offer considerable application potential, providing topological and geometric insights to spaces. We also introduce persistent Mayer homology and persistent Mayer Laplacians at various <math><mi>N</mi></math> . The bottleneck distance and stability of persistence diagrams associated with Mayer homology are investigated. Our computational experiments indicate that the topological features offered by persistent Mayer homology and spectrum given by persistent Mayer Laplacians hold substantial promise for large, complex, and diverse data. We envision that the present work serves as an inaugural step towards integrating Mayer homology and Mayer Laplacians into the realm of topological data analysis.</p>\",\"PeriodicalId\":73054,\"journal\":{\"name\":\"Foundations of data science (Springfield, Mo.)\",\"volume\":\"6 4\",\"pages\":\"584-612\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2024-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467518/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Foundations of data science (Springfield, Mo.)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3934/fods.2024032\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Foundations of data science (Springfield, Mo.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3934/fods.2024032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
摘要
在代数拓扑中,微分算子(即边界算子)通常满足d2 = 0。然而,对于整数N≥2的广义微分d N = 0在N链配合物上的Mayer同源性已经研究了80多年。我们在N链配合物上引入了Mayer laplacian。我们证明Mayer同调和Mayer拉普拉斯算子都具有相当大的应用潜力,为空间提供了拓扑和几何的见解。我们还介绍了在不同N点上的持久迈耶同调和持久迈耶拉普拉斯算子。研究了Mayer同调持久性图的瓶颈距离和稳定性。我们的计算实验表明,持久迈耶同调提供的拓扑特征和持久迈耶拉普拉斯算子给出的谱对于大型、复杂和多样化的数据具有很大的前景。我们设想,目前的工作是将迈耶同调和迈耶拉普拉斯算子整合到拓扑数据分析领域的第一步。
PERSISTENT MAYER HOMOLOGY AND PERSISTENT MAYER LAPLACIAN.
In algebraic topology, the differential (i.e., boundary operator) typically satisfies . However, the generalized differential for an integer has been studied in terms of Mayer homology on -chain complexes for more than eighty years. We introduce Mayer Laplacians on -chain complexes. We show that both Mayer homology and Mayer Laplacians offer considerable application potential, providing topological and geometric insights to spaces. We also introduce persistent Mayer homology and persistent Mayer Laplacians at various . The bottleneck distance and stability of persistence diagrams associated with Mayer homology are investigated. Our computational experiments indicate that the topological features offered by persistent Mayer homology and spectrum given by persistent Mayer Laplacians hold substantial promise for large, complex, and diverse data. We envision that the present work serves as an inaugural step towards integrating Mayer homology and Mayer Laplacians into the realm of topological data analysis.