Planar graph

In graph theory, a planar graph is a graph that can be embedded in the plane, i.e., it can be drawn on the plane in such a way that its edges intersect only at their endpoints. In other words, it can be drawn in such a way that no edges cross each other. Such a drawing is called a plane graph or planar embedding of the graph. A plane graph can be defined as a planar graph with a mapping from every node to a point on a plane, and from every edge to a plane curve on that plane, such that the extreme points of each curve are the points mapped from its end nodes, and all curves are disjoint except on their extreme points. Every graph that can be drawn on a plane can be drawn on the sphere as well, and vice versa, by means of stereographic projection. Plane graphs can be encoded by combinatorial maps or rotation systems. An equivalence class of topologically equivalent drawings on the sphere, usually with additional assumptions such as the absence of isthmuses, is called a planar ma

Modeling and Controlling epidemics : a graph perspective

Philippe Sakari Rossinelli

The social and economical impact a virus has in a population is not negligible. For this reason, gaining a theoretical understanding of the behavior of a virus is of prime importance. This project is going to be divided in several parts. First, we will discuss the topology of different graphs. Secondly, we are going to talk about the propagation of a virus on a graph, and the optimal nodes to do that. We will introduce the notion of cost function, and how relevant it is. Lastly, we will be talking about vaccinating a graph.

2015

On the robustness of the metric dimension of grid graphs to adding a single edge

Satvik Mehul Mashkaria, Gergely Odor, Patrick Thiran

The metric dimension (MD) of a graph is a combinatorial notion capturing the minimum number of landmark nodes needed to distinguish every pair of nodes in the graph based on graph distance. We study how much the MD can increase if we add a single edge to the graph. The extra edge can either be selected adversarially, in which case we are interested in the largest possible value that the MD can take, or uniformly at random, in which case we are interested in the distribution of the MD. The adversarial setting has already been studied by [Eroh et. al., 2015] for general graphs, who found an example where the MD doubles on adding a single edge. By constructing a different example, we show that this increase can be as large as exponential. However, we believe that such a large increase can occur only in specially constructed graphs, and that in most interesting graph families, the MD at most doubles on adding a single edge. We prove this for

d

-dimensional grid graphs, by showing that

2d

appropriately chosen corners and the endpoints of the extra edge can distinguish every pair of nodes, no matter where the edge is added. For the special case of

d=2

, we show that it suffices to choose the four corners as landmarks. Finally, when the extra edge is sampled uniformly at random, we conjecture that the MD of 2-dimensional grids converges in probability to

3+\mathrm{Ber}(8/27)

, and we give an almost complete proof.

2022

On the robustness of the metric dimension of grid graphs to adding a single edge

Satvik Mehul Mashkaria, Gergely Odor, Patrick Thiran

d

-dimensional grid graphs, by showing that

2d

appropriately chosen corners and the endpoints of the extra edge can distinguish every pair of nodes, no matter where the edge is added. For the special case of

d=2

3+\mathrm{Ber}(8/27)

, and we give an almost complete proof.

2022

An Maxflow Algorithm for Directed Planar Graphs

Modeling and Controlling epidemics : a graph perspective

On the robustness of the metric dimension of grid graphs to adding a single edge

On the robustness of the metric dimension of grid graphs to adding a single edge

Modeling and Controlling epidemics : a graph perspective

An Maxflow Algorithm for Directed Planar Graphs