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Persistence landscapes of affine fractals

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
We develop a method for calculating the persistence landscapes of affine fractals using the parameters of the corresponding transformations. Given an iterated function system of affine transformations that satisfies a certain compatibility condition, we prove that there exists an affine transformation acting on the space of persistence landscapes, which intertwines the action of the iterated function system. This latter affine transformation is a strict contraction and its unique fixed point is the persistence landscape of the affine fractal. We present several examples of the theory as well as confirm the main results through simulations.
Wydawca
Rocznik
Strony
163--192
Opis fizyczny
Bibliogr. 40 poz., rys.
Twórcy
  • Department of Mathematics, Iowa State University, 396 Carver Hall, Ames, IA 50011, United States
  • Department of Mathematics, Iowa State University, 396 Carver Hall, Ames, IA 50011, United States
  • Department of Mathematics, Iowa State University, 396 Carver Hall, Ames, IA 50011, United States
Bibliografia
  • [1] P. Bubenik, Statistical topological data analysis using persistence landscapes, J. Machine Learn. Res. 16 (2015), no. 1, 77–102.
  • [2] V. Robins, Computational topology at multiple resolutions: foundations and applications to fractals and dynamics, Ph.D. thesis, University of Colorado, 2000.
  • [3] G. Máté and D. W. Heermann, Persistence intervals of fractals, Phys. A Statist. Mech. Appl. 405 (2014), 252–259.
  • [4] G. Carlsson, A. Zomorodian, A. Collins, and L. J. Guibas, Persistence barcodes for shapes, Int. J. Shape Model. 11 (2005), no. 2, 149–187.
  • [5] E. Munch, K. Turner, P. Bendich, S. Mukherjee, J. Mattingly, and J. Harer, Probabilistic Fréchet means for time varying persistence diagrams, Electron. J. Statistic. 9 (2015), no. 1, 1173–1204.
  • [6] V. Kovacev-Nikolic, P. Bubenik, D. Nikolic, and G. Heo, Using persistent homology and dynamical distances to analyze protein binding, Statistic. Appl. Genetics Mol. Biol. 15 (2016), no. 1, 19–38.
  • [7] I. Donato, M. Gori, M. Pettini, G. Petri, S. De Nigris, R. Franzosi, et al., Persistent homology analysis of phase transitions, Phys. Rev. E 93 (2016), no. 5, 052138.
  • [8] J.-Y. Liu, S.-K. Jeng, and Y.-H. Yang, Applying topological persistence in convolutional neural network for music audio signals, 2016, arXiv: http://arXiv.org/abs/arXiv:1608.07373.
  • [9] P. Dlotko and T. Wanner, Topological microstructure analysis using persistence landscapes, Phys. D 334 (2016), 60–81.
  • [10] G. Cantor, De la puissance des ensembles parfaits de points, Acta Math. 4 (1884), no. 1, 381–392.
  • [11] R. S. Strichartz, Analysis on fractals, Notices Amer. Math. Soc. 46 (1999), no. 10, 1199–1208.
  • [12] J. W. S. Cassels, On a problem of Steinhaus about normal numbers, Colloq. Math. 7 (1959), 95–101.
  • [13] W. M. Schmidt, Über die Normalität von Zahlen zu verschiedenen Basen, Acta Arith. 7 (1961/1962), 299–309.
  • [14] R. Lyons and Y. Peres, Probability on Trees and Networks, Cambridge Series in Statistical and Probabilistic Mathematics, Cambridge University Press, New York, 2017.
  • [15] P. E. T. Jorgensen, Analysis and Probability: Wavelets, Signals, Fractals, Graduate Texts in Mathematics, vol. 234, Springer, New York, 2006.
  • [16] A. Byars, E. Camrud, S. N. Harding, S. McCarty, K. Sullivan, and E. S. Weber, Sampling and interpolation of cumulative distribution functions of Cantor sets in [0, 1], Dem. Math. 54 (2021), 85–109.
  • [17] A. D. Pollington, The Hausdorff dimension of a set of normal numbers. II, J. Austral. Math. Soc. Ser. A 44 (1988), no. 2, 259–264.
  • [18] Y. Peres and B. Solomyak, Self-similar measures and intersections of Cantor sets, Trans. Amer. Math. Soc. 350 (1998), no. 10, 4065–4087.
  • [19] C. Allain and M. Cloitre, Characterizing the lacunarity of random and deterministic fractal sets, Phys. Rev. A 44 (1991), 3552–3558.
  • [20] B. Yu, M. Zou, and Y. Feng, Permeability of fractal porous media by Monte Carlo simulations, Int. J. Heat Mass Transf. 48 (2005), 2787–2794.
  • [21] B. Yu, Fractal dimensions for multiphase fractal media, Fractals 14 (2006), no. 2, 111–118.
  • [22] P. E. T. Jorgensen and Steen Pedersen, Dense analytic subspaces in fractal L2-spaces, J. Anal. Math. 75 (1998), 185–228.
  • [23] R. S. Strichartz, Mock Fourier series and transforms associated with certain Cantor measures, J. Anal. Math. 81 (2000), 209–238.
  • [24] R. J. Ravier and R. S. Strichartz, Sampling theory with average values on the Sierpinski gasket, Constr. Approx. 44 (2016), no. 2, 159–194.
  • [25] J. E. Hutchinson, Fractals and self similarity, Indiana Univ. Math. J. 30 (1981), no. 5, 713–747.
  • [26] A. Hatcher, Algebraic Topology, Cambridge University Press, Cambridge, 2002.
  • [27] J. R Munkres, Elements of Algebraic Topology, Addison-Wesley Publishing Company, Boston, Massachusetts, United States, 1984.
  • [28] H. Edelsbrunner and J. Harer, Computational Topology: An Introduction, American Mathematical Society, Providence, RI 2010.
  • [29] J. A. Perea, A brief history of persistence, 2018, arXiv:1809.03624 [cs, math].
  • [30] K. Borsuk, On the imbedding of systems of compacta in simplicial complexes, Fundamenta Math. 35 (1948), 217–234 (eng).
  • [31] U. Bauer, Ripser: efficient computation of Vietoris–Rips persistence barcodes, J. Appl. Comput. Topology 5 (2021), no. 5, 391–423, DOI: https://doi.org/10.1007/s41468-021-00071-5.
  • [32] V. De Silva and R. Ghrist, Coverage in sensor networks via persistent homology, Algebraic Geometric Topol. 7 (2007), no. 1, 339–358.
  • [33] M. Bakke Botnan and W. Crawley-Boevey, Decomposition of persistence modules, Proc. Amer. Math. Soc. 148 (2020), 4581–4596, DOI: https://doi.org/10.1090/proc/14790.
  • [34] G. Azumaya, Corrections and supplementaries to my paper concerning Krull-Remak-Schmidt’s theorem, Nagoya Math. J. 1 (1950), 117–124 (eng).
  • [35] F. Chazal, V. de Silva, M. Glisse, and S. Oudot, The structure and stability of persistence modules, Springer Briefs in Mathematics, Springer, Cham, 2016.
  • [36] F. Chazal, D. Cohen-Steiner, M. Glisse, L. J. Guibas, and S. Oudot, Proximity of persistence modules and their diagrams, Research report RR-6568, INRIA, 2008.
  • [37] D. Cohen-Steiner, H. Edelsbrunner, and J. Harer, Stability of persistence diagrams, Discrete Comput. Geometry 37 (2007), no. 1, 103–120.
  • [38] F. Chazal, V. de Silva, and S. Oudot, Persistence stability for geometric complexes, Geom. Dedicata 173 (2014), 193–214.
  • [39] P. Bubenik, The persistence landscape and some of its properties, Topological Data Analysis, Abel Symposia, Springer International Publishing, Cham, 2020, pp. 97–117 (eng).
  • [40] G. Angeloro and M. J. Catanzaro, Pyscapes (version 0.1.0), https://github.com/gabbyangeloro/pyscapes.
Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a6233fb5-a2a2-4a82-8412-1299197cc4cc
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