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The Computational Complexity of Multidimensional Persistence

Journal Article · · Proposed Journal Article, unpublished
OSTI ID:1429696
 [1];  [2]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  2. Google, Inc., Mountain View, CA (United States)
We present findings on the computational complexity of computing multidimensional persistent homology. We first show that the worst-case computational complexity of multidimensional persistence is exponential. We then present an algorithm for computing multidimensional persistence which extends the algorithm given by Zomorodian and Carlsson for computing one-dimensional persistence. The computational complexity of our algorithm is polynomial in the size of the persistence module and exponential in the persistence dimension.
Research Organization:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
DOE Contract Number:
AC04-94AL85000
OSTI ID:
1429696
Report Number(s):
SAND--2017-12740J; 659005
Journal Information:
Proposed Journal Article, unpublished, Journal Name: Proposed Journal Article, unpublished Vol. 2017; ISSN 9999-9999
Publisher:
See Research Organization
Country of Publication:
United States
Language:
English

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