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The chromatic index $\chi \prime (G)$, also called the edge chromatic number, is the least number of labels in a proper edge colouring of a finite undirected graph without self-loops. Equivalently, it is the smallest number of matchings in a graph whose set partition covers all the edges. We take $\chi \prime (G)=0$ when there are no edges. For an arbitrary edge colouring, one colour always suffices whenever an edge exists, so properness is essential to this definition. The chromatic number $\chi (G)$ instead colours vertices.^[ref]

To establish an exact chromatic index, supply both a proper edge colouring and a reason that fewer colours cannot work. Every edge at a fixed vertex must have its own colour, giving the lower bound $\chi \prime (G)\ge \Delta (G)$, where $\Delta (G)$ is the maximum degree of a graph. The bound need not be attained: it counts a single resource's workload, while conflicts can also accumulate around a graph cycle.

For the triangle in a graph $K_3$ with edges $ab,bc,ca$, every pair of edges shares a vertex, so all three require different labels. The assignment $c(ab)=1,c(bc)=2,c(ca)=3$ works, proving $\chi \prime (K_3)=3$ although $\Delta (K_3)=2$. In its line graph, those three edges become a three-vertex clique. Treating this as three pair-resource jobs makes the obstruction tangible: each resource has only two jobs, but every pair of jobs conflicts, so no slot can contain two jobs.

For the square cycle graph $C_4$ with edges $ab,bc,cd,da$, use $c(ab)=c(cd)=1$ and $c(bc)=c(da)=2$. Each colour class is a matching in a graph, and each vertex has one edge of each colour. Since $\Delta (C_4)=2$, this proves $\chi \prime (C_4)=2$. More generally, alternation closes on any even cycle graph $C_{2m}$, $m\ge 2$. On an odd cycle $C_{2m+1}$, $m\ge 1$, two-colour alternation would make the last and first edges share a colour at their common vertex; a third colour on the last edge suffices. Thus even cycle graphs have chromatic index two and odd cycle graphs have chromatic index three. These exact examples show why maximum degree of a graph alone does not determine the answer.

A bipartite graph has equal list-chromatic index, chromatic index and maximum degree of a graph $\Delta$. Start with a proper $\Delta$-edge coloring. Orient its line graph toward smaller colors at one part and toward larger colors at the other. An edge of color $c$ has at most $(c-1)+(\Delta -c)=\Delta -1$ outgoing neighbours. Every induced orientation has a digraph kernel obtained from a stable matching in a bipartite graph with those preferences. Apply the kernel list-coloring lemma.

A digraph kernel is an independent set $K$ of vertices such that each vertex outside $K$ has a directed edge from itself to a vertex in $K$. A directed graph is kernel-perfect if every induced subgraph has a digraph kernel. Preference orientations of the line graph of a bipartite graph are kernel-perfect: a stable matching in a bipartite graph is independent in the line graph, and stability supplies the required outgoing edge at every unmatched edge.

Color the vertices of a periodic graph independently red or blue with equal probabilities, and declare a vertex of its line graph open exactly when the corresponding edge has equal-colored endpoints. The resulting site percolation has marginal $1/2$ and is a finite-range dependent random field: sets at line-graph distance greater than one use disjoint color inputs. Red and blue open clusters cannot join. If the original graph has an infinite red component and an infinite blue component, its line graph consequently has at least two infinite percolation clusters. One explicit amenable graph with that property is obtained by replacing each square-lattice vertex by a complete graph on ten vertices, joining neighboring blocks completely. Blocks containing both colors have independent probability $511/512$; a Peierls argument proves that they percolate, and their infinite cluster carries both a red and a blue component. Thus finite-range dependence, even with all site marginals nondegenerate, does not substitute for finite energy in percolation uniqueness.

Each vertex of a bipartite graph has a strict preference ordering of its neighbours; every neighbour is preferred to being unmatched. A stable matching in a bipartite graph is a matching in a graph with no blocking edge: an unused edge blocks if both endpoints prefer each other to their assigned partners, interpreting an unmatched endpoint as willing to accept any neighbour. Stability does not require a perfect matching in a graph.

For existence, run the Gale-Shapley algorithm. Whenever a vertex in the first part is unmatched and has an untried neighbour, it proposes to its most preferred untried neighbour. A receiver keeps its preferred proposal and rejects the other, including any previously held proposal. At most $e(G)$ proposals occur, so the procedure stops with a matching in a graph. Suppose an edge $bg$ blocked this final matching in a graph. Since $b$ prefers $g$ to its final partner, or is unmatched, $b$ must have proposed to $g$. But a receiver's held proposal only improves, so $g$'s final partner is preferred to $b$ if $b$ was rejected. If $b$ was not rejected, the edge is in the matching in a graph. Both alternatives contradict blocking. Every finite bipartite preference instance therefore has a stable matching.

For the mutual-worst edge in stable matchings, let $M,N$ be stable matchings with $bg\in M$ and $bg\notin N$. We give the argument using alternating graph components including possible unmatched endpoints. If $b$ were unmatched in $N$, then $g$ would have to prefer its $N$-partner to $b$, since otherwise $bg$ would block $N$. Following the $N$-edge from $g$, stability of $M$ forces its other endpoint to have and prefer an $M$-partner. Stability of $N$ then forces the next vertex to have and prefer an $N$-partner. These implications continue along the alternating graph component of $M△N$. They cannot stop, because at a missing next edge the preceding edge would block the appropriate matching in a graph. They also cannot close into a cycle in a graph, since the graph component already has endpoint $b$. This contradiction proves that $b$ is matched in $N$. The same reasoning applies to $g$.

Now $b$ prefers its $N$-partner to $g$, because $g$ is its worst choice. Along the alternating graph component, stability of $M$ forces that partner to prefer its $M$-partner; stability of $N$ forces the next vertex in $b$'s part to prefer its $N$-partner, and so on. A graph path graph component is impossible by the same endpoint argument, so this is a cycle in a graph. Thus throughout this cycle in a graph the part containing $b$ prefers $N$ and the part containing $g$ prefers $M$. In particular $g$ must prefer $b$ to its $N$-partner. That contradicts $b$ being $g$'s worst choice. Hence an edge ranked last by both endpoints, if present in one stable matching, is present in every stable matching.

For the list edge coloring assertion, let $\Delta$ be the maximum degree. We first prove that the chromatic index is $\Delta$. Use induction on the number of edges, with a proper $\Delta$-edge coloring of $G-uv$. Some color $a$ is missing at $u$ and some color $b$ is missing at $v$. If $a=b$, color $uv$ with it. Otherwise the edges of colors $a,b$ form alternating graph paths and even cycles in a graph. The graph component containing $u$ cannot contain $v$: an alternating graph path from $u$, starting with color $b$, would end at $v$ with color $a$, have even length, and place $u,v$ in the same bipartition class. Swap $a,b$ in the graph component containing $u$. Now $b$ is missing at both ends of $uv$, so it can be colored $b$. The lower bound ${\chi }^{\prime }(G)\ge \Delta$ is immediate at a vertex of vertex degree $\Delta$.

Fix such a proper coloring $c:E(G)\to \{1,\dots ,\Delta \}$. Orient the line graph toward the smaller color at vertices in the first part of $G$, and toward the larger color at vertices in the second part. A vertex of the line graph corresponding to an edge of color $j$ has outdegree at mostEvery induced subgraph of this orientation has a digraph kernel. Indeed, restrict to its edge set in the original bipartite graph, give first-part vertices a preference for smaller colors and second-part vertices a preference for larger colors, and choose a stable matching. Its edges form an independent set in the line graph. Every edge outside the matching in a graph has an endpoint whose partner is preferred to it, by stability; thus it has an outgoing edge to the independent set. This proves that the orientation is a kernel-perfect directed graph.

Here is the kernel list-coloring lemma with its proof. If a kernel-perfect directed graph $D$ has lists satisfying $|L(v)|\ge d_D^{+}(v)+1$, choose any color $a$ appearing in a list and a digraph kernel $K$ of the induced subgraph on vertices whose lists contain $a$. Color $K$ with $a$, delete $K$, and delete $a$ from the remaining lists. Each remaining vertex that loses a color had an outgoing neighbour in $K$, so its outdegree decreases by at least one; the list inequality persists. Vertices not losing a color also retain the inequality. Induction on the number of vertices completes a proper list coloring.

Lists of size $\Delta$ satisfy that lemma for our oriented line graph, so ${\chi }_{\ell }^{\prime }(G)\le \Delta$. Identical lists show ${\chi }_{\ell }^{\prime }(G)\ge {\chi }^{\prime }(G)$. Consequently the Galvin theorem for bipartite list edge coloring givesThe empty graph is immediate; if parallel edges are allowed, orient their line-graph adjacency in both directions when the two endpoints prescribe opposite directions. The outdegree bound still holds, and the same stable matching and digraph kernel proof applies with preferences on incident edges.

We use Zhang's argument, obtaining the critical nonpercolation conclusion from uniqueness rather than assuming it as part of the Harris-Kesten theorem. For independent bond percolation on ${\mathbb{Z}}^2$, apply part (ii) to independent site percolation on its line graph; open sites correspond to open bonds. The line graph is amenable and of finite type. Therefore an infinite bond cluster, if it exists, is almost surely unique. The same holds for the dual bond percolation model.

Assume for contradiction that $\theta (1/2)>0$. The planar dual graph is another square lattice, and its open bonds correspond to closed primal bonds, also with parameter $1/2$. Both models then have an infinite percolation cluster almost surely, by part (i). As a disc $D_R$ expands, the probability that it meets an infinite cluster tends to one, for each model. Choose $R$ avoiding all primal and dual vertices and all intersections of either graph with the four endpoints of the following arcs. Divide the boundary circle into four equal arcs $A_1,A_2,A_3,A_4$ in cyclic order. Let $L_i$ be the event of an infinite primal open ray whose last exit from $D_R$ is in $A_i$; define $L_i^{\ast }$ similarly for an infinite dual open ray. After that exit the entire ray stays outside the disc. The existence of a ray follows by finite branching in an infinite locally finite graph.

Each $L_i$ is increasing in the primal bond states, and their union has probability tending to one. Four-fold rotation symmetry makes their probabilities equal. The FKG inequality for their decreasing complements gives the square-root trick for positively associated eventsThe left side tends to zero, so $\mathbb{P}(L_i)\to 1$. Apply the same argument to the dual states to get $\mathbb{P}(L_i^{\ast })\to 1$. A union bound, requiring no independence between the models, now shows that for sufficiently large $R$ the alternating eventhas positive probability.

The alternating exterior-arm separation lemma says that the two primal rays on this event cannot be joined by a primal open path lying outside $D_R$. Indeed, such a joining path contains a simple crosscut of the exterior between the two primal exit points. Join that crosscut to a chord inside the disc. The Jordan curve theorem puts one of the alternating dual exit points on the bounded side. Its dual ray, which is restricted to the exterior of the disc and runs to infinity, would have to cross the open primal crosscut. A dual open bond cannot cross a primal open bond. This is impossible.

Let $F$ be the finite set of primal bonds whose drawn edges meet $D_R$, and let $E$ be the projection of the alternating-arm event onto the states outside $F$. Because $F$ is finite, this projection is a finite union of measurable events; $\mathbb{P}(E)>0$. Every configuration in $E$ admits an assignment on $F$ witnessing the original four arms. Now close all bonds of $F$. The infinite tails of the two primal rays beyond their first exterior vertices survive; any path joining the surviving tails would now avoid the disc. Appending their original exterior segments back to their exit points would give the forbidden exterior connection. Thus the modified configuration contains at least two infinite percolation clusters. By independence, or the finite-energy property of Bernoulli percolation, $\mathbb{P}(E\cap \{F\text{ all closed}\})=2^{-|F|}\mathbb{P}(E)>0$. This contradicts the uniqueness obtained from part (ii). Therefore

We first specify the standard hypotheses of percolation uniqueness on an amenable quasi-transitive graph. A locally finite graph has finite degree at every vertex; a quasi-transitive graph, or graph of finite type, has finitely many vertex orbits under the acting group $\Gamma$ of graph automorphisms. Here the site percolation law is invariant under $\Gamma$ and independent, with one parameter $p_j$ for each orbit. Initially suppose $0<p_j<1$. This gives the finite-energy property of Bernoulli percolation: conditional on all states outside any finite set, every assignment inside that set has positive probability. An amenable graph has finite sets $W_n$ with $|{\partial }^{+}{W}_n|/|W_n|\to 0$, where ${\partial }^{+}{W}_n$ denotes the external vertex boundary. Finite type bounds the degrees uniformly, so internal and external boundary conventions are equivalent here.

Let $N$ be the number of infinite percolation clusters, taking values in $\{0,1,2,\dots ,\infty \}$. Each event $\{N=j\}$ is invariant. Part (i), together with countability of these possibilities, shows that $N$ is an almost-sure constant.

Suppose first that this constant is a finite integer $j\ge 2$. Some finite connected set $F$ meets all $j$ infinite percolation clusters with positive probability, since increasing finite sets exhaust the graph. Make every vertex of $F$ open. This joins all the infinite clusters. Opening a finite set cannot produce a new infinite cluster from finite clusters: only finitely many clusters meet its finite boundary, and their finite union is finite. By the finite-energy property the modified event has positive probability, contradicting the almost-sure value $j$. Thus a finite $N$ must be $0$ or $1$.

Suppose instead that $N=\infty$ almost surely. Some finite connected set $F$ meets three distinct infinite percolation clusters with positive probability. Open all of $F$. Its vertices belong to one open cluster, and deleting $F$ from that cluster leaves at least three infinite components. This is an encounter box in percolation. We use boxes rather than assume that the local geometry permits a single trifurcation vertex in percolation.

Here is the boundary-counting contradiction in detail. Translates of $F$ have the same positive encounter probability. Finite type and bounded degree allow a deterministic packing of mutually disjoint such translates whose centers have positive lower density in the interiors of the Følner sets $W_n$: every vertex is within a fixed distance of one chosen orbit, and a bounded-radius greedy packing discards only a bounded number of possible centers per chosen center. Boundary layers of any fixed thickness have size $o(|W_n|)$. The expected number of encounter boxes wholly inside $W_n$ is consequently at least $c|W_n|$ for a fixed $c>0$ and all large $n$.

On the other hand, contract the open encounter boxes in each cluster to vertices and retain the part inside $W_n$. Each contracted encounter box separates at least three branches that run to infinity, and each branch must leave $W_n$. Choose a minimal forest connecting all these boundary exits. Every encounter junction has degree at least three in that forest: its three infinite branches remain in different components after deleting the junction, so none can be omitted. The leaves are boundary exits. For each nontrivial tree, the degree-sum identity gives at most the number of leaves minus two vertices of degree at least three. Thus the number of encounter boxes is at most a constant times $|{\partial }^{+}{W}_n|$, where the constant accounts for the bounded boundary degrees. Taking expected values contradicts amenability. This excludes $N=\infty$ and provesThere is a genuine endpoint qualification if different orbit parameters are allowed to be $0$ or $1$. Subdivide each horizontal edge of the square lattice once. Open every original vertex deterministically and close every new midpoint deterministically. This is an invariant independent law on an amenable graph that is also a quasi-transitive graph, but its infinite open clusters are the distinct vertical columns. Thus the finite-energy property must be included when interpreting a general vector $\mathbf{p}$. The homogeneous endpoint laws themselves cause no problem: they give zero or one infinite cluster.

The conclusion is false for $k$-independent laws, even with all site marginals equal to $1/2$. Here is a fully specified monochromatic line-graph percolation counterexample. Form a graph $B$ by replacing each vertex of ${\mathbb{Z}}^2$ by a complete graph on ten vertices and putting every possible edge between the blocks of two neighboring lattice vertices. Every vertex of $B$ has degree $9+4\cdot 10=49$. The graph is connected, periodic and amenable: a square of blocks has volume of order $n^2$ and boundary of order $n$. Assign independent fair red/blue colors to the vertices of $B$.

Call a block good when it contains both colors. Good-block indicators are independent, withThey percolate. To verify this without presupposing a site threshold, put $q=1-g=1/512$. A finite nearest-neighbor good-block cluster around a good origin is surrounded by a circuit of bad blocks in the matching square graph, where horizontal, vertical and diagonal neighbors are allowed. A surrounding circuit of length $\ell$ has an anchor within $[-\ell ,\ell {]}^2$. Overcounting its choices by $9{\ell }^2{8}^{\ell }$ gives the Peierls argumentThe sum bound follows directly from ${\sum }_{\ell \ge 1}{\ell }^2{r}^{\ell }=r(1+r)/(1-r{)}^3$, with $r=1/64$. An infinite good-block cluster therefore exists with positive probability, and by part (i) it exists almost surely. Inside each of its blocks the red vertices are connected to one another, as are the blue vertices; between adjacent good blocks the complete bipartite joining edges connect each color. Hence $B$ has both an infinite red component and an infinite blue component almost surely.

Now use site percolation on $\Gamma =L(B)$, the line graph of $B$: its vertices are the edges $\{u,v\}$ of $B$, two adjacent when they share an endpoint. Declare such a site open exactly when $u,v$ have the same color. Each site has open probability $1/2$. Sets of sites at graph distance greater than one involve disjoint sets of underlying color variables, so this is a translation-invariant $1$-independent law. The line graph is again connected, locally finite, amenable and of finite type. The infinite red and blue components of $B$ yield infinite open clusters in $L(B)$. An open path in $L(B)$ cannot change color at a shared endpoint, so those two clusters are distinct. Thus $N\ge 2$ almost surely. Local color constraints destroy the finite-energy property, precisely the ingredient missing from the uniqueness proof.

A graph is Eulerian graph if it has a closed trail containing every edge exactly once. For a graph with at least three vertices, the Euler circuit criterion says that it is Eulerian exactly when it is connected and every vertex has even degree.

Necessity is immediate: each visit of a closed trail to a vertex uses one entering and one leaving edge, so the incident edges occur in pairs; the trail also joins every vertex incident with an edge. Conversely, start at any vertex and extend an edge-simple trail until no unused incident edge remains. Even degrees force this maximal trail to end where it began. If edges remain, connectedness supplies a vertex of this circuit incident with an unused edge. Construct another closed trail from there and splice it into the first. Repeating consumes every edge and gives an Euler circuit.

The line graph $L(G)$ has vertex set $E(G)$, with two vertices adjacent when the corresponding edges of $G$ share an endpoint. If $G$ is connected and $r$-regular, then $L(G)$ is connected, and the vertex corresponding to an edge $uv$ has degreeEvery degree is even, so the Euler circuit criterion makes $L(G)$ Eulerian.

A proper edge colouring gives different labels to any two distinct edges sharing a vertex. We work with finite undirected graphs without self-loops; distinct parallel edges in a multigraph must also have different colours. For a simple graph, whose edges are two-element sets, the condition isEvery colour class $M_i=\{e\in E(G):c(e)=i\}$ is a matching in a graph. Conversely, a set partition of the edges into matchings in a graph supplies a proper edge colouring. Thus minimizing colours means grouping all the edges into as few matchings in a graph as possible.

The line graph makes the relationship with proper vertex colouring explicit: replace each original edge by a vertex, joining two new vertices exactly when their original edges share an endpoint. A proper edge colouring of $G$ becomes a proper vertex colouring of its line graph $L(G)$, so $\chi \prime (G)=\chi (L(G))$. For a multigraph, retain a distinct new vertex for each parallel edge.^[ref]