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Problems in Discrete Geometry, Incidence Geometry,and Extremal Graph Theory

Authors: Chao, Ting-Wei;

Problems in Discrete Geometry, Incidence Geometry,and Extremal Graph Theory

Abstract

In this thesis, we study several problems from discrete geometry, incidence geometry, and extremal graph theory. In Chapter 1, we discuss some results in discrete geometry. We study three different but similar discrete geometry problems, which share a similar idea on constructions. The problems ask for sets of points in d-dimensional space that are evenly distributed, and the notion of being evenly distributed is defined in different ways. In Chapter 2, we show sharp results on two problems in incidence geometry: the finite field Kakeya problem and the joints problem. The correct orders of magnitude for these two problems were both obtained by the dimension counting polynomial method. We improved both results by considering carefully chosen spaces of polynomials. The sharp bound on the joints problem also provides a new proof of the Kruskal-Katona theorem and its generalization. We will discuss this connection in this chapter and in chapter 3. In Chapter 3, we study several extremal problems on (hyper)graphs. In the first part of this chapter, we proved some of the Kruskal-Katona-type problems via the entropy method, including a short and new proof of Lov ́asz's version of the Kruskal-Katona theorem. In the second part of this chapter, we give a simplified version of Chase's proof of the Gan-Loh-Sudakov conjecture

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Keywords

Combinatorics and discrete mathematics (excl. physical combinatorics), Mathematical sciences

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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