2011
DOI: 10.1088/0266-5611/27/12/124003
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Dualities in persistent (co)homology

Abstract: We consider sequences of absolute and relative homology and cohomology groups that arise naturally for a filtered cell complex. We establish algebraic relationships between their persistence modules, and show that they contain equivalent information. We explain how one can use the existing algorithm for persistent homology to process any of the four modules, and relate it to a recently introduced persistent cohomology algorithm. We present experimental evidence for the practical efficiency of the latter algori… Show more

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Cited by 125 publications
(182 citation statements)
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“…Standard Persistence and Matrix Reduction. We review the presentation of standard persistence as in [15], where explicit chains representing a compatible homology basis are maintained. For a standard filtra-…”
Section: If a And C Injective Of Corankmentioning
confidence: 99%
See 1 more Smart Citation
“…Standard Persistence and Matrix Reduction. We review the presentation of standard persistence as in [15], where explicit chains representing a compatible homology basis are maintained. For a standard filtra-…”
Section: If a And C Injective Of Corankmentioning
confidence: 99%
“…The special case where all the arrows in the filtration have the same orientation -commonly known as standard persistence -has been extensively studied. In this case, zigzag modules are just modules over the ring of polynomials F[t], so computing their interval decomposition as in theorem 1.1 comes down to reducing a matrix to column-echelon or rowechelon form over F [t], with the additional twist that the ordering of the simplices by time of insertion in the filtration must be preserved [15,23]. Most methods use Gaussian elimination for this reduction and therefore incur a cubic worst-case time complexity in the number n of simplex insertions [20].…”
mentioning
confidence: 99%
“…By collecting windows beginning at every trace record, a high-dimensional point cloud is formed. We next use topological analysis [11,28] to detect circular features within the point cloud. These circular features represent cyclical behavior in the trace, as the points within such circles represent roughly the same pattern of memory access.…”
Section: Technical Overviewmentioning
confidence: 99%
“…The algorithm that computes the persistent cohomology of a sequence of simplicial complexes [11] is a modified version of the persistent homology algorithm [3,14], which in turn is a variation of the classic Smith normal form algorithm [21]. It involves a specific ordering in conducting matrix reduction on the coboundary matrices of the nested simplicial complexes.…”
Section: Detecting Circular Features In a Point Cloudmentioning
confidence: 99%
“…Both variants lack a proof of usefulness in application scenarios. The currently fastest approaches in practice are based on the cohomological persistence algorithm by De Silva et al [dSMVJ11] and on heuristics of the standard reduction algorithm that exploit the structure of the boundary matrices [CK11].…”
mentioning
confidence: 99%