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Attractors of compactly generated semigroups of regular polynomial mappings.
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Matematiska institutionen. Department of Mathematics, Faculty of Science, Albaha University, Al Baha, Saudi Arabia.ORCID-id: 0000-0001-7238-2421
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Matematiska institutionen.ORCID-id: 0000-0002-3444-6524
Jagiellonian University, Faculty of Mathematics and Computer ScienceInstitute of Mathematics, Institute of Mathematics..
2018 (engelsk)Inngår i: Complexity, ISSN 1076-2787, E-ISSN 1099-0526, artikkel-id 5698021Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

We investigate the metric space of pluriregular sets as well as the contractions on that space induced by infinite compact families of proper polynomial mappings of several complex variables. The topological semigroups generated by such families, with composition as the semigroup operation, lead to the constructions of a variety of Julia-type pluriregular sets. The generating families can also be viewed as infinite iterated function systems with compact attractors. We show that such attractors can be approximated both deterministically and probabilistically in a manner of the classic chaos game.

sted, utgiver, år, opplag, sider
2018. artikkel-id 5698021
Emneord [en]
Julia sets, pluricomplex Green function, iterated function systems
HSV kategori
Identifikatorer
URN: urn:nbn:se:uu:diva-355806DOI: 10.1155/2018/5698021ISI: 000450216100001OAI: oai:DiVA.org:uu-355806DiVA, id: diva2:1231052
Tilgjengelig fra: 2018-07-05 Laget: 2018-07-05 Sist oppdatert: 2018-12-19bibliografisk kontrollert
Inngår i avhandling
1. Approximation of pluricomplex Green functions: A probabilistic approach
Åpne denne publikasjonen i ny fane eller vindu >>Approximation of pluricomplex Green functions: A probabilistic approach
2018 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

This PhD thesis focuses on probabilistic methods of approximation of pluricomplex Green functions and is based on four papers.

The thesis begins with a general introduction to the use of pluricomplex Green functions in multidimensional complex analysis and a review of their main properties. This is followed by short description of the main results obtained in the enclosed papers.

In Paper I, we study properties of the metric space of pluriregular sets, that is zero sets of continuous pluricomplex Green functions. The best understood non-trivial examples of such sets are composite Julia sets, obtained by iteration of finite families of polynomial mappings in several complex variables. We prove that the so-called chaos game is applicable in the case of such sets. We also visualize some composite Julia sets using escape time functions and Monte Carlo simulation.

In Paper II, we extend results in Paper I to the case of infinite compact families of proper polynomials mappings. With composition as the semigroup operation, we generate families of infinite iterated function systems with compact attractors. We show that such attractors can be approximated probabilistically in a manner of the classic chaos game.

In Paper III, we study numerical approximation and visualisation of pluricomplex Green functions based on the Monte-Carlo integration. Unlike alternative methods that rely on locating a sequence of carefully chosen finite sets of points satisfying some optimal conditions for approximation purposes, our approach is simpler and more direct by relying on generation of pseudorandom points. We examine numerically the errors of approximation for some simple geometric shapes for which the pluricomplex Green functions are known. If the pluricomplex Green functions are not known, the errors in Monte Carlo integration can be expressed with the aid of statistics in terms of confidence intervals.

Finally, in Paper IV, we study how perturbations of an orthonomalization procedure influence the resulting approximate Bergman functions. To this end we consider the concept of near orthonormality of a finite set of vectors in an inner product space, understood as closeness of the Gram matrix of those vectors to the identity matrix. We provide estimates for the errors resulting from using nearly orthogonal bases instead of orthogonal ones. The motivation for this work comes from Paper III: when Gram matrices are calculated via Monte Carlo integration, the outcomes of standard orthogonalisation algorithms are nearly orthonormal bases.

sted, utgiver, år, opplag, sider
Uppsala: Department of Mathematics, 2018. s. 47
Serie
Uppsala Dissertations in Mathematics, ISSN 1401-2049 ; 109
Emneord
pluricomplex Green function, pluriregular sets, Bernstein-Markov property, Bergman function, nearly orthonormal polynomials, orthogonal polynomials, Monte Carlo simulation, composite Julia sets, Julia sets, iterated function systems, the chaos game.
HSV kategori
Identifikatorer
urn:nbn:se:uu:diva-355810 (URN)978-91-506-2714-5 (ISBN)
Disputas
2018-09-21, Polhemsalen, 10134, Ångströmslaboratoriet, Lägerhyddsvägen 1, Uppsala, 13:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2018-08-31 Laget: 2018-07-06 Sist oppdatert: 2018-08-31

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