Solving Linear Differential Equations in Terms of Hypergeometric Functions by ₂-Descent

Let L be a linear ordinary differential equation with coefficients in C(x). This thesis presents algorithms to solve L in closed form. The key part of this thesis is 2-descent method, which is used to reduce L to an equation that is easier to solve. The starting point is an irreducible L, and the go...

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Other Authors: Fang, Tingting, 1982- (authoraut)
Format: Others
Language:English
English
Published: Florida State University
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Online Access:http://purl.flvc.org/fsu/fd/FSU_migr_etd-5350
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spelling ndltd-fsu.edu-oai-fsu.digital.flvc.org-fsu_1832442020-06-16T03:07:15Z Solving Linear Differential Equations in Terms of Hypergeometric Functions by ₂-Descent Fang, Tingting, 1982- (authoraut) Van Hoeij, Mark (professor directing thesis) Van Engelen, Robert A. (university representative) Agashe, Amod (committee member) Aldrovandi, Ettore (committee member) Aluffi, Paolo (committee member) Department of Mathematics (degree granting department) Florida State University (degree granting institution) Text text Florida State University Florida State University English eng 1 online resource computer application/pdf Let L be a linear ordinary differential equation with coefficients in C(x). This thesis presents algorithms to solve L in closed form. The key part of this thesis is 2-descent method, which is used to reduce L to an equation that is easier to solve. The starting point is an irreducible L, and the goal of 2-descent is to decide if L is projectively equivalent to another equation $\tilde{L}$ that is defined over a subfield C(f) of C(x). Although part of the mathematics for 2-descent has already been treated before, a complete implementation could not be given because it involved a step for which we do not have a complete implementation. Our key novelty is to give an approach that is fully implementable. We describe and implement the algorithm for order 2, and show by examples that the same also work for higher order. By doing 2-descent for L, the number of true singularities drops to at most n/2 + 2 (n is the number of true singularities of L). This provides us ways to solve L in closed form(e.g.in terms of hypergeometric funtions). A Dissertation submitted to the Department of Mathematics in partial fulfillment of the requirements for the degree of Doctor of Philosophy. Fall Semester, 2012. October 16, 2012. 2-descent, algorithm Includes bibliographical references. Mark van Hoeij, Professor Directing Thesis; Robert A. van Engelen, University Representative; Amod Agashe, Committee Member; Ettore Aldrovandi, Committee Member; Paolo Aluffi, Committee Member. Mathematics FSU_migr_etd-5350 http://purl.flvc.org/fsu/fd/FSU_migr_etd-5350 This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). The copyright in theses and dissertations completed at Florida State University is held by the students who author them. http://diginole.lib.fsu.edu/islandora/object/fsu%3A183244/datastream/TN/view/Solving%20Linear%20Differential%20Equations%20in%20Terms%20of%20Hypergeometric%20Functions%20by%20%E2%82%82-Descent.jpg
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language English
English
format Others
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topic Mathematics
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Solving Linear Differential Equations in Terms of Hypergeometric Functions by ₂-Descent
description Let L be a linear ordinary differential equation with coefficients in C(x). This thesis presents algorithms to solve L in closed form. The key part of this thesis is 2-descent method, which is used to reduce L to an equation that is easier to solve. The starting point is an irreducible L, and the goal of 2-descent is to decide if L is projectively equivalent to another equation $\tilde{L}$ that is defined over a subfield C(f) of C(x). Although part of the mathematics for 2-descent has already been treated before, a complete implementation could not be given because it involved a step for which we do not have a complete implementation. Our key novelty is to give an approach that is fully implementable. We describe and implement the algorithm for order 2, and show by examples that the same also work for higher order. By doing 2-descent for L, the number of true singularities drops to at most n/2 + 2 (n is the number of true singularities of L). This provides us ways to solve L in closed form(e.g.in terms of hypergeometric funtions). === A Dissertation submitted to the Department of Mathematics in partial fulfillment of the requirements for the degree of Doctor of Philosophy. === Fall Semester, 2012. === October 16, 2012. === 2-descent, algorithm === Includes bibliographical references. === Mark van Hoeij, Professor Directing Thesis; Robert A. van Engelen, University Representative; Amod Agashe, Committee Member; Ettore Aldrovandi, Committee Member; Paolo Aluffi, Committee Member.
author2 Fang, Tingting, 1982- (authoraut)
author_facet Fang, Tingting, 1982- (authoraut)
title Solving Linear Differential Equations in Terms of Hypergeometric Functions by ₂-Descent
title_short Solving Linear Differential Equations in Terms of Hypergeometric Functions by ₂-Descent
title_full Solving Linear Differential Equations in Terms of Hypergeometric Functions by ₂-Descent
title_fullStr Solving Linear Differential Equations in Terms of Hypergeometric Functions by ₂-Descent
title_full_unstemmed Solving Linear Differential Equations in Terms of Hypergeometric Functions by ₂-Descent
title_sort solving linear differential equations in terms of hypergeometric functions by ₂-descent
publisher Florida State University
url http://purl.flvc.org/fsu/fd/FSU_migr_etd-5350
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