528 research outputs found

    d-๋ฐ˜์ˆœ์„œ์˜ ๊ฒฝ์Ÿ๊ทธ๋ž˜ํ”„์˜ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์‚ฌ๋ฒ”๋Œ€ํ•™ ์ˆ˜ํ•™๊ต์œก๊ณผ, 2018. 2. ๊น€์„œ๋ น.The \emph{competition graph} C(D)C(D) of a digraph DD is defined to be a graph whose vertex set is the same as DD and which has an edge joining two distinct vertices xx and yy if and only if there are arcs (x,z)(x,z) and (y,z)(y,z) for some vertex zz in DD. Competition graphs have been extensively studied for more than four decades. Cohen~\cite{cohen1968interval, cohen1977food, cohen1978food} empirically observed that most competition graphs of acyclic digraphs representing food webs are interval graphs. Roberts~\cite{roberts1978food} asked whether or not Cohen's observation was just an artifact of the construction, and then concluded that it was not by showing that if GG is an arbitrary graph, then GG together with additional isolated vertices as many as the number of edges of GG is the competition graph of some acyclic digraph. Then he asked for a characterization of acyclic digraphs whose competition graphs are interval graphs. Since then, the problem has remained elusive and it has been one of the basic open problems in the study of competition graphs. There have been a lot of efforts to settle the problem and some progress has been made. While Cho and Kim~\cite{cho2005class} tried to answer his question, they could show that the competition graphs of doubly partial orders are interval graphs. They also showed that an interval graph together with sufficiently many isolated vertices is the competition graph of a doubly partial order. In this thesis, we study the competition graphs of dd-partial orders some of which generalize the results on the competition graphs of doubly partial orders. For a positive integer dd, a digraph DD is called a \emph{dd-partial order} if V(D) \subset \RR^d and there is an arc from a vertex x\mathbf{x} to a vertex y\mathbf{y} if and only if x\mathbf{x} is componentwise greater than y\mathbf{y}. A doubly partial order is a 22-partial order. We show that every graph GG is the competition graph of a dd-partial order for some nonnegative integer dd, call the smallest such dd the \emph{partial order competition dimension} of GG, and denote it by dimโกpoc(G)\dim_\text{poc}(G). This notion extends the statement that the competition graph of a doubly partial order is interval and the statement that any interval graph can be the competition graph of a doubly partial order as long as sufficiently many isolated vertices are added, which were proven by Cho and Kim~\cite{cho2005class}. Then we study the partial order competition dimensions of some interesting families of graphs. We also study the mm-step competition graphs and the competition hypergraph of dd-partial orders.1 Introduction 1 1.1 Basic notions in graph theory 1 1.2 Competition graphs 6 1.2.1 A brief history of competition graphs 6 1.2.2 Competition numbers 7 1.2.3 Interval competition graphs 10 1.3 Variants of competition graphs 14 1.3.1 m-step competition graphs 15 1.3.2 Competition hypergraphs 16 1.4 A preview of the thesis 18 2 On the competition graphs of d-partial orders 1 20 2.1 The notion of d-partial order 20 2.2 The competition graphs of d-partial orders 21 2.2.1 The regular (d โˆ’ 1)-dimensional simplex โ–ณ dโˆ’1 (p) 22 2.2.2 A bijection from H d + to a set of regular (d โˆ’ 1)-simplices 23 2.2.3 A characterization of the competition graphs of d-partial orders 25 2.2.4 Intersection graphs and competition graphs of d-partial orders 27 2.3 The partial order competition dimension of a graph 29 3 On the partial order competition dimensions of chordal graphs 2 38 3.1 Basic properties on the competition graphs of 3-partial orders 39 3.2 The partial order competition dimensions of diamond-free chordal graphs 42 3.3 Chordal graphs having partial order competition dimension greater than three 46 4 The partial order competition dimensions of bipartite graphs 3 53 4.1 Order types of two points in R 3 53 4.2 An upper bound for the the partial order competition dimension of a graph 57 4.3 Partial order competition dimensions of bipartite graphs 64 5 On the m-step competition graphs of d-partial orders 4 69 5.1 A characterization of the m-step competition graphs of dpartial orders 69 5.2 Partial order m-step competition dimensions of graphs 71 5.3 dim poc (Gm) in the aspect of dim poc (G) 76 5.4 Partial order competition exponents of graphs 79 6 On the competition hypergraphs of d-partial orders 5 81 6.1 A characterization of the competition hypergraphs of d-partial orders 81 6.2 The partial order competition hyper-dimension of a hypergraph 82 6.3 Interval competition hypergraphs 88 Abstract (in Korean) 99Docto

    Revisiting Interval Graphs for Network Science

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    The vertices of an interval graph represent intervals over a real line where overlapping intervals denote that their corresponding vertices are adjacent. This implies that the vertices are measurable by a metric and there exists a linear structure in the system. The generalization is an embedding of a graph onto a multi-dimensional Euclidean space and it was used by scientists to study the multi-relational complexity of ecology. However the research went out of fashion in the 1980s and was not revisited when Network Science recently expressed interests with multi-relational networks known as multiplexes. This paper studies interval graphs from the perspective of Network Science

    ์ƒํƒœ๊ณ„์—์„œ์˜ ๊ฒฝ์Ÿ ๊ด€์ ์œผ๋กœ ๊ทธ๋ž˜ํ”„์™€ ์œ ํ–ฅ๊ทธ๋ž˜ํ”„์˜ ๊ตฌ์กฐ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์‚ฌ๋ฒ”๋Œ€ํ•™ ์ˆ˜ํ•™๊ต์œก๊ณผ, 2023. 2. ๊น€์„œ๋ น.In this thesis, we study m-step competition graphs, (1, 2)-step competition graphs, phylogeny graphs, and competition-common enemy graphs (CCE graphs), which are primary variants of competition graphs. Cohen [11] introduced the notion of competition graph while studying predator-prey concepts in ecological food webs.An ecosystem is a biological community of interacting species and their physical environment. For each species in an ecosystem, there can be m conditions of the good environment by regarding lower and upper bounds on numerous dimensions such as soil, climate, temperature, etc, which may be represented by an m-dimensional rectangle, so-called an ecological niche. An elemental ecological truth is that two species compete if and only if their ecological niches overlap. Biologists often describe competitive relations among species cohabiting in a community by a food web that is a digraph whose vertices are the species and an arc goes from a predator to a prey. In this context, Cohen [11] defined the competition graph of a digraph as follows. The competition graph C(D) of a digraph D is defined to be a simple graph whose vertex set is the same as V (D) and which has an edge joining two distinct vertices u and v if and only if there are arcs (u, w) and (v, w) for some vertex w in D. Since Cohen introduced this definition, its variants such as m-step competition graphs, (i, j)-step competition graphs, phylogeny graphs, CCE graphs, p-competition graphs, and niche graphs have been introduced and studied. As part of these studies, we show that the connected triangle-free m-step competition graph on n vertices is a tree and completely characterize the digraphs of order n whose m-step competition graphs are star graphs for positive integers 2 โ‰ค m < n. We completely identify (1,2)-step competition graphs C_{1,2}(D) of orientations D of a complete k-partite graph for some k โ‰ฅ 3 when each partite set of D forms a clique in C_{1,2}(D). In addition, we show that the diameter of each component of C_{1,2}(D) is at most three and provide a sharp upper bound on the domination number of C_{1,2}(D) and give a sufficient condition for C_{1,2}(D) being an interval graph. On the other hand, we study on phylogeny graphs and CCE graphs of degreebounded acyclic digraphs. An acyclic digraph in which every vertex has indegree at most i and outdegree at most j is called an (i, j) digraph for some positive integers i and j. If each vertex of a (not necessarily acyclic) digraph D has indegree at most i and outdegree at most j, then D is called an hi, ji digraph. We give a sufficient condition on the size of hole of an underlying graph of an (i, 2) digraph D for the phylogeny graph of D being a chordal graph where D is an (i, 2) digraph. Moreover, we go further to completely characterize phylogeny graphs of (i, j) digraphs by listing the forbidden induced subgraphs. We completely identify the graphs with the least components among the CCE graphs of (2, 2) digraphs containing at most one cycle and exactly two isolated vertices, and their digraphs. Finally, we gives a sufficient condition for CCE graphs being interval graphs.์ด ๋…ผ๋ฌธ์—์„œ ๊ฒฝ์Ÿ๊ทธ๋ž˜ํ”„์˜ ์ฃผ์š” ๋ณ€์ด๋“ค ์ค‘ m-step ๊ฒฝ์Ÿ๊ทธ๋ž˜ํ”„, (1, 2)-step ๊ฒฝ์Ÿ ๊ทธ๋ž˜ํ”„, ๊ณ„ํ†ต ๊ทธ๋ž˜ํ”„, ๊ฒฝ์Ÿ๊ณต์ ๊ทธ๋ž˜ํ”„์— ๋Œ€ํ•œ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ์ข…ํ•ฉํ–ˆ๋‹ค. Cohen [11]์€ ๋จน์ด์‚ฌ์Šฌ์—์„œ ํฌ์‹์ž-ํ”ผ์‹์ž ๊ฐœ๋…์„ ์—ฐ๊ตฌํ•˜๋ฉด์„œ ๊ฒฝ์Ÿ๊ทธ๋ž˜ํ”„ ๊ฐœ๋…์„ ๊ณ ์•ˆํ–ˆ๋‹ค. ์ƒํƒœ๊ณ„๋Š” ์ƒํ˜ธ์ž‘์šฉํ•˜๋Š” ์ข…๋“ค๊ณผ ๊ทธ๋“ค์˜ ๋ฌผ๋ฆฌ์  ํ™˜๊ฒฝ์˜ ์ƒ๋ฌผํ•™์  ์ฒด๊ณ„์ด๋‹ค. ์ƒํƒœ๊ณ„์˜ ๊ฐ ์ข…์— ๋Œ€ํ•ด์„œ, ํ† ์–‘, ๊ธฐํ›„, ์˜จ๋„ ๋“ฑ๊ณผ ๊ฐ™์€ ๋‹ค์–‘ํ•œ ์ฐจ์›์˜ ํ•˜๊ณ„ ๋ฐ ์ƒ๊ณ„๋ฅผ ๊ณ ๋ คํ•˜์—ฌ ์ข‹์€ ํ™˜๊ฒฝ์„ m๊ฐœ์˜ ์กฐ๊ฑด๋“ค๋กœ ๋‚˜ํƒ€๋‚ผ ์ˆ˜ ์žˆ๋Š”๋ฐ ์ด๋ฅผ ์ƒํƒœ์  ์ง€์œ„(ecological niche)๋ผ๊ณ  ํ•œ๋‹ค. ์ƒํƒœํ•™์  ๊ธฐ๋ณธ๊ฐ€์ •์€ ๋‘ ์ข…์ด ์ƒํƒœ์  ์ง€์œ„๊ฐ€ ๊ฒน์น˜๋ฉด ๊ฒฝ์Ÿํ•˜๊ณ (compete), ๊ฒฝ์Ÿํ•˜๋Š” ๋‘ ์ข…์€ ์ƒํƒœ์  ์ง€์œ„๊ฐ€ ๊ฒน์นœ๋‹ค๋Š” ๊ฒƒ์ด๋‹ค. ํ”ํžˆ ์ƒ๋ฌผํ•™์ž๋“ค์€ ํ•œ ์ฒด์ œ์—์„œ ์„œ์‹ํ•˜๋Š” ์ข…๋“ค์˜ ๊ฒฝ์Ÿ์  ๊ด€๊ณ„๋ฅผ ๊ฐ ์ข…์€ ๊ผญ์ง“์ ์œผ๋กœ, ํฌ์‹์ž์—์„œ ํ”ผ์‹์ž์—๊ฒŒ๋Š” ์œ ํ–ฅ๋ณ€(arc)์„ ๊ทธ์–ด์„œ ๋จน์ด์‚ฌ์Šฌ๋กœ ํ‘œํ˜„ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ๋งฅ๋ฝ์—์„œ Cohen [11]์€ ๋‹ค์Œ๊ณผ ๊ฐ™์ด ์œ ํ–ฅ๊ทธ๋ž˜ํ”„์˜ ๊ฒฝ์Ÿ ๊ทธ๋ž˜ํ”„๋ฅผ ์ •์˜ํ–ˆ๋‹ค. ์œ ํ–ฅ๊ทธ๋ž˜ํ”„(digraph) D์˜ ๊ฒฝ์Ÿ๊ทธ๋ž˜ํ”„(competition graph) C(D) ๋ž€ V (D)๋ฅผ ๊ผญ์ง“์  ์ง‘ํ•ฉ์œผ๋กœ ํ•˜๊ณ  ๋‘ ๊ผญ์ง“์  u, v๋ฅผ ์–‘ ๋์ ์œผ๋กœ ๊ฐ–๋Š” ๋ณ€์ด ์กด์žฌํ•œ๋‹ค๋Š” ๊ฒƒ๊ณผ ๊ผญ์ง“์  w๊ฐ€ ์กด์žฌํ•˜์—ฌ (u, w),(v, w)๊ฐ€ ๋ชจ๋‘ D์—์„œ ์œ ํ–ฅ๋ณ€์ด ๋˜๋Š” ๊ฒƒ์ด ๋™์น˜์ธ ๊ทธ๋ž˜ํ”„๋ฅผ ์˜๋ฏธํ•œ๋‹ค. Cohen์ด ๊ฒฝ์Ÿ๊ทธ๋ž˜ํ”„์˜ ์ •์˜๋ฅผ ๋„์ž…ํ•œ ์ดํ›„๋กœ ๊ทธ ๋ณ€์ด๋“ค๋กœ m-step ๊ฒฝ์Ÿ๊ทธ๋ž˜ํ”„(m-step competition graph), (i, j)-step ๊ฒฝ์Ÿ๊ทธ๋ž˜ํ”„((i, j)-step competition graph), ๊ณ„ํ†ต๊ทธ๋ž˜ํ”„(phylogeny graph), ๊ฒฝ์Ÿ๊ณต์ ๊ทธ๋ž˜ํ”„(competition-common enemy graph), p-๊ฒฝ์Ÿ๊ทธ๋ž˜ํ”„(p-competition graph), ๊ทธ๋ฆฌ๊ณ  ์ง€์œ„๊ทธ๋ž˜ํ”„(niche graph)๊ฐ€ ๋„์ž…๋˜์—ˆ๊ณ  ์—ฐ๊ตฌ๋˜๊ณ  ์žˆ๋‹ค. ์ด ๋…ผ๋ฌธ์˜ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋“ค์˜ ์ผ๋ถ€๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์‚ผ๊ฐํ˜•์ด ์—†์ด ์—ฐ๊ฒฐ๋œ m-step ๊ฒฝ์Ÿ ๊ทธ๋ž˜ํ”„๋Š” ํŠธ๋ฆฌ(tree)์ž„์„ ๋ณด์˜€์œผ๋ฉฐ 2 โ‰ค m < n์„ ๋งŒ์กฑํ•˜๋Š” ์ •์ˆ˜ m, n์— ๋Œ€ํ•˜์—ฌ ๊ผญ์ง“์ ์˜ ๊ฐœ์ˆ˜๊ฐ€ n๊ฐœ์ด๊ณ  m-step ๊ฒฝ์Ÿ๊ทธ๋ž˜ํ”„๊ฐ€ ๋ณ„๊ทธ๋ž˜ํ”„(star graph)๊ฐ€ ๋˜๋Š” ์œ ํ–ฅ๊ทธ๋ž˜ํ”„๋ฅผ ์™„๋ฒฝํ•˜๊ฒŒ ํŠน์ง•ํ™” ํ•˜์˜€๋‹ค. k โ‰ฅ 3์ด๊ณ  ๋ฐฉํ–ฅ์ง€์–ด์ง„ ์™„์ „ k-๋ถ„ํ•  ๊ทธ๋ž˜ํ”„(oriented complete k-partite graph)์˜ (1, 2)-step ๊ฒฝ์Ÿ๊ทธ๋ž˜ํ”„ C_{1,2}(D)์—์„œ ๊ฐ ๋ถ„ํ• ์ด ์™„์ „ ๋ถ€๋ถ„ ๊ทธ๋ž˜ํ”„๋ฅผ ์ด๋ฃฐ ๋•Œ, C_{1,2}(D)์„ ๋ชจ๋‘ ํŠน์ง•ํ™” ํ•˜์˜€๋‹ค. ๋˜ํ•œ, C_{1,2}(D)์˜ ๊ฐ ์„ฑ๋ถ„(component)์˜ ์ง€๋ฆ„(diameter)์˜ ๊ธธ์ด๊ฐ€ ์ตœ๋Œ€ 3์ด๋ฉฐ C_{1,2}(D)์˜ ์ง€๋ฐฐ์ˆ˜(domination number)์— ๋Œ€ํ•œ ์ƒ๊ณ„์™€ ์ตœ๋Œ“๊ฐ’์„ ๊ตฌํ•˜๊ณ  ๊ตฌ๊ฐ„๊ทธ๋ž˜ํ”„(interval graph)๊ฐ€ ๋˜๊ธฐ ์œ„ํ•œ ์ถฉ๋ถ„ ์กฐ๊ฑด์„ ๊ตฌํ•˜์˜€๋‹ค. ์ฐจ์ˆ˜๊ฐ€ ์ œํ•œ๋œ ์œ ํ–ฅํšŒ๋กœ๋ฅผ ๊ฐ–์ง€ ์•Š๋Š” ์œ ํ–ฅ๊ทธ๋ž˜ํ”„(degree-bounded acyclic digraph)์˜ ๊ณ„ํ†ต๊ทธ๋ž˜ํ”„์™€ ๊ฒฝ์Ÿ๊ณต์ ๊ทธ๋ž˜ํ”„์— ๋Œ€ํ•ด์„œ๋„ ์—ฐ๊ตฌํ•˜์˜€๋‹ค. ์–‘์˜ ์ •์ˆ˜๋“ค i, j์— ๋Œ€ํ•˜์—ฌ (i, j) ์œ ํ–ฅ๊ทธ๋ž˜ํ”„๋ž€ ๊ฐ ๊ผญ์ง“์ ์˜ ๋‚ด์ฐจ์ˆ˜๋Š” ์ตœ๋Œ€ i, ์™ธ์ฐจ์ˆ˜๋Š” ์ตœ๋Œ€ j์ธ ์œ ํ–ฅํšŒ๋กœ ๊ฐ–์ง€ ์•Š๋Š” ์œ ํ–ฅ๊ทธ๋ž˜ํ”„์ด๋‹ค. ๋งŒ์•ฝ ์œ ํ–ฅ๊ทธ๋ž˜ํ”„ D์— ๊ฐ ๊ผญ์ง“์ ์ด ๋‚ด์ฐจ์ˆ˜๊ฐ€ ์ตœ๋Œ€ i, ์™ธ์ฐจ์ˆ˜๊ฐ€ ์ตœ๋Œ€ j ์ธ ๊ฒฝ์šฐ์— D๋ฅผ hi, ji ์œ ํ–ฅ๊ทธ๋ž˜ํ”„๋ผ ํ•œ๋‹ค. D๊ฐ€ (i, 2) ์œ ํ–ฅ๊ทธ๋ž˜ํ”„์ผ ๋•Œ, D์˜ ๊ณ„ํ†ต๊ทธ๋ž˜ํ”„๊ฐ€ ํ˜„๊ทธ๋ž˜ํ”„(chordal graph)๊ฐ€ ๋˜๊ธฐ ์œ„ํ•œ D์˜ ๋ฐฉํ–ฅ์„ ๊ณ ๋ คํ•˜์ง€ ์•Š๊ณ  ์–ป์–ด์ง€๋Š” ๊ทธ๋ž˜ํ”„(underlying graph)์—์„œ ๊ธธ์ด๊ฐ€ 4์ด์ƒ์ธ ํšŒ๋กœ(hole)์˜ ๊ธธ์ด์— ๋Œ€ํ•œ ์ถฉ๋ถ„์กฐ๊ฑด์„ ๊ตฌํ•˜์˜€๋‹ค. ๊ฒŒ๋‹ค๊ฐ€ (i, j) ์œ ํ–ฅ๊ทธ๋ž˜ํ”„์˜ ๊ณ„ํ†ต๊ทธ๋ž˜ํ”„์—์„œ ๋‚˜์˜ฌ ์ˆ˜ ์—†๋Š” ์ƒ์„ฑ ๋ถ€๋ถ„ ๊ทธ๋ž˜ํ”„(forbidden induced subgraph)๋ฅผ ํŠน์ง•ํ™” ํ•˜์˜€๋‹ค. (2, 2) ์œ ํ–ฅ๊ทธ๋ž˜ํ”„ D์˜ ๊ฒฝ์Ÿ๊ณต์ ๊ทธ๋ž˜ํ”„ CCE(D)๊ฐ€ 2๊ฐœ์˜ ๊ณ ๋ฆฝ์ (isolated vertex)๊ณผ ์ตœ๋Œ€ 1๊ฐœ์˜ ํšŒ๋กœ๋ฅผ ๊ฐ–์œผ๋ฉด์„œ ๊ฐ€์žฅ ์ ์€ ์„ฑ๋ถ„์„ ๊ฐ–๋Š” ๊ฒฝ์šฐ์ผ ๋•Œ์˜ ๊ตฌ์กฐ๋ฅผ ๊ทœ๋ช…ํ–ˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, CCE(D)๊ฐ€ ๊ตฌ๊ฐ„๊ทธ๋ž˜ํ”„๊ฐ€ ๋˜๊ธฐ ์œ„ํ•œ ์„ฑ๋ถ„์˜ ๊ฐœ์ˆ˜์— ๋Œ€ํ•œ ์ถฉ๋ถ„์กฐ๊ฑด์„ ๊ตฌํ•˜์˜€๋‹ค.1 Introduction 1 1.1 Graph theory terminology and basic concepts 1 1.2 Competition graphs and its variants 6 1.2.1 A brief background of competition graphs 6 1.2.2 Variants of competition graphs 8 1.2.3 m-step competition graphs 10 1.2.4 (1, 2)-step competition graphs 13 1.2.5 Phylogeny graphs 14 1.2.6 CCE graphs 16 1.3 A preview of the thesis 17 2 Digraphs whose m-step competition graphs are trees 19 2.1 The triangle-free m-step competition graphs 23 2.2 Digraphs whose m-step competition graphs are trees 29 2.3 The digraphs whose m-step competition graphs are star graphs 38 3 On (1, 2)-step competition graphs of multipartite tournaments 47 3.1 Preliminaries 48 3.2 C1,2(D) with a non-clique partite set of D 51 3.3 C1,2(D) without a non-clique partite set of D 66 3.4 C1,2(D) as a complete graph 74 3.5 Diameters and domination numbers of C1,2(D) 79 3.6 Disconnected (1, 2)-step competition graphs 82 3.7 Interval (1, 2)-step competition graphs 84 4 The forbidden induced subgraphs of (i, j) phylogeny graphs 90 4.1 A necessary condition for an (i, 2) phylogeny graph being chordal 91 4.2 Forbidden subgraphs for phylogeny graphs of degree bounded digraphs 99 5 On CCE graphs of (2, 2) digraphs 122 5.1 CCE graphs of h2, 2i digraphs 128 5.2 CCE graphs of (2, 2) digraphs 134 Abstract (in Korean) 168 Acknowledgement (in Korean) 170๋ฐ•

    2D growth processes: SLE and Loewner chains

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    This review provides an introduction to two dimensional growth processes. Although it covers a variety processes such as diffusion limited aggregation, it is mostly devoted to a detailed presentation of stochastic Schramm-Loewner evolutions (SLE) which are Markov processes describing interfaces in 2D critical systems. It starts with an informal discussion, using numerical simulations, of various examples of 2D growth processes and their connections with statistical mechanics. SLE is then introduced and Schramm's argument mapping conformally invariant interfaces to SLE is explained. A substantial part of the review is devoted to reveal the deep connections between statistical mechanics and processes, and more specifically to the present context, between 2D critical systems and SLE. Some of the SLE remarkable properties are explained, as well as the tools for computing with SLE. This review has been written with the aim of filling the gap between the mathematical and the physical literatures on the subject.Comment: A review on Stochastic Loewner evolutions for Physics Reports, 172 pages, low quality figures, better quality figures upon request to the authors, comments welcom

    Proceedings of the 17th Cologne-Twente Workshop on Graphs and Combinatorial Optimization

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    Estimating networks of sustainable development goals

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    An increasing number of researchers and practitioners advocate for a systemic understanding of the Sustainable Development Goals (SDGs) through interdependency networks. Ironically, the burgeoning network-estimation literature seems neglected by this community. We provide an introduction to the most suitable estimation methods for SDG networks. Building a dataset with 87 development indicators in four countries over 20 years, we perform a comparative study of these methods. We find important differences in the estimated network structures as well as in synergies and trade-offs between SDGs. Finally, we provide some guidelines on the potentials and limitations of estimating SDG networks for policy advice

    Arbeitsgemeinschaft: Percolation

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    Abstract. Percolation as a mathematical theory is more than fifty years old. During its life, it has attracted the attention of both physicists and mathematicians. This is due in large part to the fact that it represents one of the simplest examples of a statistical mechanical model undergoing a phase transition, and that several interesting results can be obtained rigorously. In recent years the interest in percolation has spread even further, following the introduction by Oded Schramm of the Schramm-Loewner Evolution (SLE) and a theorem by Stanislav Smirnov showing the conformal invariance of the continuum scaling limit of two-dimensional critical percolation. These results establish a new, powerful and mathematically rigorous, link between lattice-based statistical mechanical models and conformally invariant models in the plane, studied by physicists under the name of Conformal Field Theory (CFT). The Arbeitsgemeinschaft on percolation has attracted more than thirty participants, most of them young researchers, from several countries in Europe, North America, and Brazil. The main focus has been on recent developments, but several classical results have also been presented

    Quantum Loewner Evolution

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    What is the scaling limit of diffusion limited aggregation (DLA) in the plane? This is an old and famously difficult question. One can generalize the question in two ways: first, one may consider the {\em dielectric breakdown model} ฮท\eta-DBM, a generalization of DLA in which particle locations are sampled from the ฮท\eta-th power of harmonic measure, instead of harmonic measure itself. Second, instead of restricting attention to deterministic lattices, one may consider ฮท\eta-DBM on random graphs known or believed to converge in law to a Liouville quantum gravity (LQG) surface with parameter ฮณโˆˆ[0,2]\gamma \in [0,2]. In this generality, we propose a scaling limit candidate called quantum Loewner evolution, QLE(ฮณ2,ฮท)(\gamma^2, \eta). QLE is defined in terms of the radial Loewner equation like radial SLE, except that it is driven by a measure valued diffusion ฮฝt\nu_t derived from LQG rather than a multiple of a standard Brownian motion. We formalize the dynamics of ฮฝt\nu_t using an SPDE. For each ฮณโˆˆ(0,2]\gamma \in (0,2], there are two or three special values of ฮท\eta for which we establish the existence of a solution to these dynamics and explicitly describe the stationary law of ฮฝt\nu_t. We also explain discrete versions of our construction that relate DLA to loop-erased random walk and the Eden model to percolation. A certain "reshuffling" trick (in which concentric annular regions are rotated randomly, like slot machine reels) facilitates explicit calculation. We propose QLE(2,1)(2,1) as a scaling limit for DLA on a random spanning-tree-decorated planar map, and QLE(8/3,0)(8/3,0) as a scaling limit for the Eden model on a random triangulation. We propose using QLE(8/3,0)(8/3,0) to endow pure LQG with a distance function, by interpreting the region explored by a branching variant of QLE(8/3,0)(8/3,0), up to a fixed time, as a metric ball in a random metric space.Comment: 132 pages, approximately 100 figures and computer simulation
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