A topic in the Open Knowledge Graph — a free, open map of 15,290 topics and the order to learn them in.

Eulerian Circuits and Paths

College Depth 75 in the knowledge graph ☐ I know this ☆ Set as goal
6topics build on this
386prerequisites beneath it
See this on the map →
Graph Paths, Cycles, and ConnectivityIntroduction to Graph Theory→→Hamiltonian Circuits and Paths
euler-circuit euler-path eulerian-graph konigsberg-bridges

Core Idea

An Eulerian circuit is a closed walk traversing every edge exactly once; an Eulerian path is an open walk doing the same. Euler's theorem (1736) states: a connected graph has an Eulerian circuit if and only if every vertex has even degree, and an Eulerian path (but not circuit) if and only if exactly two vertices have odd degree. The Königsberg bridge problem — can one cross all seven bridges without repeating any? — was Euler's original motivation and arguably the founding problem of graph theory.

How It's Best Learned

Attempt Eulerian circuits on small graphs by hand before seeing the theorem. Verify Euler's condition on several examples. Connect to practical route-planning problems (mail delivery, snow plowing) where the goal is to traverse all edges with minimum repetition.

Common Misconceptions

Explainer

Euler's theorem is one of the most elegant results in graph theory: a complete solution to a natural traversal problem, given by a single, easy-to-check condition. You've studied graph connectivity and the basic vocabulary of graphs. Now the question is: can you plan a walk that uses every edge exactly once? Think of the graph as a map where edges are streets and vertices are intersections — you want a route that covers every street exactly once, ideally returning to where you started.

The key insight comes from thinking locally about each vertex. Every time a walk passes through a vertex (entering, then leaving), it consumes two edges — one in, one out. For a circuit (a closed walk that returns to its starting vertex) to traverse every edge exactly once, every vertex must balance its arrivals and departures perfectly. This forces every vertex to have even degree — an equal number of edges on each side of any passage. If any vertex has odd degree, it cannot be perfectly balanced, meaning the walk must either start or end there, making a closed circuit impossible.

Euler's theorem converts this local observation into a complete characterization. For a connected graph: it has an Eulerian circuit if and only if every vertex has even degree; it has an Eulerian path (open walk through every edge once) if and only if exactly two vertices have odd degree — those two are the start and end of the path. Connectivity is also required: you cannot traverse edges in a component you can never reach. The Königsberg bridge problem, which motivated Euler's 1736 paper, had four land masses each with an odd number of bridge connections — so no Eulerian path was possible, proving the famous walk impossible.

One distinction is critical to keep sharp: Eulerian circuits cover every edge once, while Hamiltonian circuits visit every vertex once. These problems sound related but are fundamentally different in difficulty. Eulerian circuit existence is solvable in linear time — just check that all degrees are even and the graph is connected. Hamiltonian circuit existence is NP-complete, with no known efficient algorithm. The degree condition works for Euler because edges are "used up" as you traverse them, allowing a clean local argument to close the analysis. No comparable local condition exists for Hamilton, which is why the two problems, despite their surface similarity, have completely different theories.

Practice Questions 5 questions

Prerequisite Chain

Understanding Zero → The Number Zero → Counting to Five → Counting to 10 → Counting to 20 → Counting a Set of Objects Up to 20 → Cardinality: The Last Number Counted → Matching Numerals to Quantities → Subitizing Small Quantities → Addition Within 10 → Number Bonds to 10 → Addition Within 20 → Doubles and Near Doubles → Doubles Facts Within 10 → Near Doubles Facts Within 20 → Mental Math Strategies for Addition → Mental Math: Adding and Subtracting Tens → Addition Within 100 → Repeated Addition as Multiplication → Multiplication as Equal Groups → Multiplication: Arrays → Basic Multiplication Facts (0s, 1s, 2s, 5s, 10s) → Multiplication Facts Within 100 → Division as Equal Sharing → Division as Grouping (Measurement Division) → Division: Grouping (Repeated Subtraction) Model → Division: Fair Sharing Model → Division as Equal Sharing → Division as Grouping → Basic Division Facts → Division Facts Within 100 → Multiplication and Division Fact Families → Relationship Between Multiplication and Division → Division Facts as Inverse of Multiplication → Remainders and Quotients in Division → Division Word Problems → Multi-Step Word Problems → Solving Multi-Step Word Problems → Multiplication Word Problems → Division Word Problems → Introduction to Long Division → Factors and Multiples → Prime and Composite Numbers → Equivalent Fractions → Relating Fractions and Decimals → Decimal Place Value → Integers and the Number Line → Comparing and Ordering Integers → Absolute Value → Adding Integers → Subtracting Integers → Multiplying Integers → Introduction to Exponents → Order of Operations → Integer Order of Operations → Variable Expressions → The Distributive Property → Variables and Expressions Review → Introduction to Polynomials → Adding and Subtracting Polynomials → Multiplying Polynomials → Factorial → Permutations → Combinations → Counting Principles: Addition and Multiplication Rules → Introduction to Graph Theory → Propositional Logic Foundations → Logical Equivalences → Set Operations: Union, Intersection, and Complement → Proof by Cases → Proving by Cases and Exhaustion → Vacuous Truth and Trivial Cases → Proof by Cases (Proof by Exhaustion) → Mathematical Induction → Graph Paths, Cycles, and Connectivity → Eulerian Circuits and Paths

Longest path: 76 steps · 386 total prerequisite topics

Prerequisites (2)

Leads To (1)