mathematics

Graph Theory & Networks

Vertices, edges, and the surprising power of networks — from shortest paths and spanning trees to flow problems and graph coloring.

graph theorynetworksDijkstraspanning treegraph coloringmax flowEulerian path

Graph theory is the study of networks: objects (vertices) connected by relationships (edges). Born from Euler's 1736 solution to the Königsberg bridge problem, it now underpins everything from GPS navigation and social networks to chip design and epidemiology. Many of its core questions — shortest paths, optimal colorings, maximum flows — are deceptively simple to state yet profoundly difficult to solve in general.

These simulations let you build, manipulate, and analyze graphs in real time. Watch Dijkstra's algorithm fan outward to find the shortest path. See a minimum spanning tree grow edge by edge. Experiment with chromatic numbers, push flow through a network, and trace Eulerian circuits across every edge exactly once.

5 interactive simulations

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Eulerian & Hamiltonian Path Explorer

Trace paths that visit every edge or every vertex exactly once — discover why Euler paths are easy to find but Hamiltonian paths are NP-hard

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Graph Coloring & Chromatic Number

Explore the graph coloring problem — assign colors to vertices so that no two adjacent vertices share a color and discover the chromatic number

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Minimum Spanning Tree Simulator

Build the cheapest network connecting all nodes — watch Kruskal's algorithm sort edges and grow a minimum spanning tree step by step

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Max Flow / Min Cut Simulator

Push flow through a network from source to sink and discover the max-flow min-cut theorem — the duality that connects maximum throughput to minimum bottleneck

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Dijkstra's Shortest Path Simulator

Watch Dijkstra's algorithm explore a weighted graph step by step, revealing the shortest path from source to destination in real time