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The bipartite graph property means that a walk starting in $V_0$ ends there precisely when its length is even. Thus the even-length walk generating function on a bipartite graph is $Z_G^0(x)={\sum }_{k\ge 0}{\sigma }_{2k}{x}^{2k}$. Deleting the last edge of an odd-length self-avoiding walk leaves an even-length one; each such prefix has at most $\Delta$ possible last-edge choices. Hence ${\sigma }_{2k+1}\le \Delta {\sigma }_{2k}$, and for $x\ge 0$,These inequalities also hold with infinite values. Their finite positive prefactor shows that the two power series have the same radius of convergence $1/\mu$; alternatively apply the root formula to the even subsequence.

Let the bipartite graph have parts $L,R$. Add a source $s$, a sink $t$, capacity-one edges $s\to u$ for $u\in L$ and $v\to t$ for $v\in R$, and capacity $M=|V|+1$ on each original edge directed $L\to R$. Use the max-flow min-cut theorem: maximum flow value equals minimum cut capacity. Also use Integrality of the Ford-Fulkerson algorithm: integral capacities admit an integral maximum flow, found by integral augmenting paths.

An integral flow selects a matching in a graph, because each left and right vertex carries at most one unit. Conversely every matching gives a unit flow along its selected $s\to u\to v\to t$ paths. Hence maximum flow value equals maximum matching cardinality.

A minimum cut has capacity at most $|L|$, whereas crossing even one original edge would cost $M>|L|$. For its source side $Z$, no edge of the original graph runs from $L\cap Z$ to $R\setminus Z$. Thereforeis a vertex cover, and its cardinality is exactly the cut capacity. Conversely, given any cover $U$, use $Z=\{s\}\cup (L\setminus U)\cup (R\cap U)$. No original edge crosses this cut, because both its endpoints would otherwise be outside the cover; its capacity is $|U|$. Thus minimum cut capacity equals minimum cover size, proving König's theorem for bipartite matching:For the algorithm, repeatedly find augmenting paths in the residual network, then take $Z$ to be the vertices reachable from $s$. Each integral augmentation increases flow by at least one; the total value is at most $\min (|L|,|R|)$. Each reachability search takes $O(|V|+|E|)$ time, so this procedure takes $O(|V|(|V|+|E|))$ time. The network uses only polynomially many edges and integer capacities, yielding the requested polynomial-time algorithm and an explicit cover.

On a connected bipartite graph, every exchange bond can attain its lower classical energy $-J{S}^2$. Set ${\mathbf{S}}_i=S\mathbf{n}$ on one sublattice and ${\mathbf{S}}_j=-S\mathbf{n}$ on the other, for any unit vector $\mathbf{n}$. This Néel state minimizes all bonds simultaneously and hasThe direction $\mathbf{n}\in S^2$ parametrizes the continuous orientation degeneracy; disconnected components can choose their orientations independently.

A triangular lattice illustrates geometric frustration. For three fixed-length spins on a triangle,The minimum requires their sum to vanish, giving coplanar $120$-degree spins rather than antiparallel alignment on every bond. A three-sublattice pattern realizes this condition on the nearest-neighbour triangular lattice. Its energy per bond is $-J{S}^2/2$, and global rotations produce equivalent classical states.

We will prove a polynomial progression in a high-energy fourfold difference set. The route is to extract a large subset with a small difference set, construct a dense Freiman s-isomorphism model, and use the Bogolyubov lemma and the pigeonhole principle. To respect the proof requirement, every ingredient beyond the elementary rules for Freiman homomorphisms is established below.

Assume $n\ge 1$. Since three entries of an additive quadruple determine the fourth, $E(A)\le n^3$, so a nonvacuous hypothesis has $0<\theta \le 1$. Let $r(t)=|\{(a,b)\in A^2:a+b=t\}|$. Then $E(A)={\sum }_{t}r(t{)}^2$ and ${\sum }_{t}r(t)=n^2$. Define the popular sum set $S=\{t:r(t)\ge \theta n/2\}$. The contribution to additive energy from its complement is at most $\theta n^3/2$. Since $r(t)\le n$, the bipartite graph on two copies of $A$ whose edges have sums in $S$ has at least $\theta n^2/2$ edges. Moreover $|S|\le 2n/\theta$.

Put $\delta =\theta /2$ and $\tau ={\delta }^2/16$. Here is a dependent random choice argument producing the small difference set. Independently choose two right vertices, allowing repetition, and let $X$ be their common left neighbourhood. The Cauchy-Schwarz inequality gives $\mathbb{E}|X|\ge {\delta }^{2}n$. Call an ordered pair of left vertices bad if its common right neighbourhood has fewer than $\tau n$ elements. The expected number $b(X)$ of bad ordered pairs in $X$ is at most ${\tau }^2{n}^2$, because a fixed bad pair survives both random choices with probability at most ${\tau }^2$. ThusChoose a realization attaining at least this expectation. Then $|X|\ge 3{\delta }^{2}n/4$, and $b(X)\le {\delta }^{2}n|X|/64\le |X{|}^2/48$. Remove from $X$ every vertex having more than $|X|/4$ bad partners in $X$. At most $|X|/12$ vertices are removed. The remaining set $B$ has $|B|\ge {\delta }^{2}n/2$, and any $a,b\in B$ have at least $|X|/2$ vertices $z\in X$ for which both $(a,z)$ and $(z,b)$ are good.

For such a $z$, there are at least $\tau n$ right vertices $y$ adjacent to $a,z$, and at least $\tau n$ right vertices $y^{\prime }$ adjacent to $z,b$. These paths givea representation with four members of $S$. For fixed $a,b$, the tuple of four sums determines $y,z,y^{\prime }$ uniquely, so there are at least $|X|{\tau }^2{n}^2/2$ distinct tuples. Select one ordered pair $a,b$ for each member of $B-B$. Tuples belonging to different differences are disjoint. Counting all possible tuples in $S^4$ provesIn particular, with $m=|B|$, we have $m\ge {\theta }^{2}n/8$ and $|B-B|\le Km$ for $K=2^{25}{\theta }^{-12}$. This is the required small-difference set form of the Balog-Szemerédi-Gowers theorem, proved by counting paths rather than cited.

We next control higher iterated sumsets. Choose a nonempty $X\subseteq B$ minimizing $\rho =|X-B|/|X|$, so $\rho \le K$. We prove the Petridis minimal-growth lemma in the form $|X-B+C|\le \rho |X+C|$ for finite $C$. Order $C=\{c_1,\dots ,c_t\}$, and let $X_i$ consist of those $x\in X$ for which $x+c_i$ is new in the union of the translates $X+c_j$. Then ${\sum }_i|X_i|=|X+C|$. Every member of $(X\setminus X_i)-B+c_i$ already occurs in an earlier translate of $X-B$. By minimality, $|(X\setminus X_i)-B|\ge \rho |X\setminus X_i|$, also when the complement is empty. Thus the new contribution from $X-B+c_i$ is at most $\rho |X_i|$. Sum over $i$ to prove the lemma. Iterating with $C=-(j-1)B$ gives $|X-jB|\le K^j|X|$.

For completeness, the Ruzsa triangle inequality in the needed form isFor each $d\in U-W$, fix $d=u_d-w_d$. The map $(d,v)\mapsto (u_d-v,v-w_d)$ is injective: adding the coordinates recovers $d$, and then $v$. Take $U=kB$, $W=\ell B$, $V=X$ and apply the preceding bounds. We obtain the Plünnecke-Ruzsa inequalityIn particular $T=8B-8B$ has at most $K^{16}m$ elements.

We now prove a slightly wasteful version of the Ruzsa modeling lemma, avoiding any assumption about the diameter of $B$. Set $q=8|T|$. Choose a prime $p$ larger than all $|t|$, $t\in T$, and much larger than $q$. Arbitrarily large primes exist by the elementary argument that a prime divisor of one plus the product of all primes up to a given bound exceeds that bound. For a uniformly chosen nonzero multiplier $r$ modulo $p$, each nonzero $t\in T$ has $rt$ uniform among the nonzero residues. Call a multiplier forbidden if some such $rt$ agrees modulo $p$ with $jq$, where $|jq|<p$. There are at most $2p/q+1\le 3p/q$ such residues. For $p\ge 4$, a union bound therefore makes the probability of being forbidden less thanChoose a nonforbidden $r$. Represent $rB$ by integers in $[0,p-1]$ and partition that interval into sixteen consecutive pieces of diameter less than $p/16$. One piece contains the images of a subset $B^{\prime }\subseteq B$ with $|B^{\prime }|\ge m/16$. Let $\varphi (b)$ be the integer representative of $rb$ in that piece, reduced modulo $q$.

A difference of eight sums of these representatives has absolute value less than $p/2$. If its original difference in $B$ is zero, it is a multiple of $p$, hence zero. Conversely, if its reduction modulo $q$ is zero, it equals $jq$ with $|jq|<p$; our choice of $r$ forces its original difference to be zero. This proves that $\varphi$ is a Freiman s-isomorphism of order eight. Injectivity follows by padding a one-term equality to eight terms with a fixed element. Consequently $D=\varphi (B^{\prime })\subseteq G=\mathbb{Z}/q\mathbb{Z}$ has subset densityNo primality of $q$ is needed.

Here is the cyclic Bogolyubov lemma with all its Fourier analysis on a finite abelian group details. Use $\hat{f}(r)={\mathbb{E}}_{x}f(x)e(-rx/q)$, $f=1_D$, and normalized convolution on a finite group. A finite geometric series proves orthogonality, and expanding the finite sums proves the Parseval identity on a finite group, Fourier inversion on a finite group, and $\widehat{f\ast g}=\hat{f}\hat{g}$. For $\tilde{f}(x)=f(-x)$, the nonnegative functionhas support exactly $2D-2D$ and Fourier coefficients on a finite abelian group $|\hat{f}(r){|}^4$. Put $\Gamma =\{r\ne 0:|\hat{f}(r)|\ge {\alpha }^{3/2}/\sqrt{8}\}$. The Parseval identity on a finite group gives $|\Gamma |\le 8{\alpha }^{-2}$. The total fourth moment of the frequencies outside $\Gamma \cup \{0\}$ is at most ${\alpha }^4/8$.

If $\Vert rx/q\Vert \le 1/16$ for every $r\in \Gamma$, then $\mathrm{Re}e(rx/q)\ge \cos (\pi /8)>3/4$. The zero frequency contributes ${\alpha }^4$ with no loss. Separating the large and small frequencies in Fourier inversion on a finite group yieldsThus $2D-2D$ contains the Bohr set expressed in distance coordinates by $\Vert rx/q\Vert \le 1/16$. This is consistent with the existing character-distance convention for a Bohr set: here it is enough that each character lies in the corresponding short arc around one.

We finally prove the needed nonwrapping progression in a cyclic Bohr set, including for composite $q$. Write $d=|\Gamma |$ and $Q=\lfloor q^{1/(d+1)}\rfloor$. Partition the $d$-dimensional unit cube into $Q^d$ boxes. The $Q^d+1$ points with coordinates $jr/q$ modulo one, $0\le j\le Q^d$, give by the pigeonhole principle an integer $1\le t\le Q^d$ with $\Vert rt/q\Vert \le 1/Q$ for all $r\in \Gamma$. ThenThese points are distinct modulo $q$, since their integer representatives lie between zero and $Q^{d+1}/16\le q/16$. Their number is at least $q^{1/(d+1)}/32$. For $d=0$ the same argument simply chooses $t=1$.

The Freiman s-isomorphism induces a bijection $\Phi :2B^{\prime }-2B^{\prime }\to 2D-2D$: define it on a representation by taking the same two positive and two negative images. Equality of representations uses an order-four relation, and injectivity uses the converse relation. If three consecutive members $y_{j-1},y_j,y_{j+1}$ of $P$ satisfy $y_{j-1}+y_{j+1}=2y_j$, their preimages satisfy the same equality, since its expansion is an equality of eight-term sums in $B^{\prime }$. Hence the inverse image of $P$ is an ordinary arithmetic progression in $2B^{\prime }-2B^{\prime }\subseteq 2A-2A$, with distinct terms.

To remove the multiplicative constant from the length bound, let $R=\lceil 8{\alpha }_0^{-2}\rceil$ and $\beta =1/(R+1)$. The length just proved is at least $c_{\theta }{n}^{\beta }$, where $c_{\theta }={\theta }^{2\beta }/32>0$. Choose $N_0\ge 3$ so that $c_{\theta }{n}^{\beta }\ge n^{\beta /2}$ for $n\ge N_0$, and set $\gamma =\min \{\beta /2,\log 3/\log N_0\}$. For $2\le n<N_0$, two distinct members of $A$ give a nonzero $u\in A-A$, and $\{-u,0,u\}\subseteq 2A-2A$ has length three, at least $n^{\gamma }$. For $n=1$, the singleton $\{0\}$ suffices. In every nonempty case,with $\gamma >0$ depending only on $\theta$. If empty sets are permitted, the required length is zero and there is no substantive assertion.

Form a bipartite graph with one vertex for each row and one for each column, putting an edge $ij$ exactly where $a_{ij}>0$. For a set $S$ of row vertices, let $N(S)$ be its neighbouring column vertices. Since $A$ is a doubly stochastic matrix,The Hall marriage theorem therefore supplies a perfect matching. Its incidence entries define a permutation matrix $P$ supported on the positive entries of $A$, hence on the ones of $B$. Entrywise $P\le B$, so

Add missing cross-edges to a hypothetical non-Hamiltonian balanced bipartite graph until it is maximal with that property. The complete bipartite graph is Hamiltonian for $n\ge 2$, so a missing cross-edge $uv$ remains. Adding it creates a Hamilton cycle, and removing it gives a Hamilton pathFor each $i$, consider the conditions $u{B}_i\in E$ and $A_{i}v\in E$. Since $\mathrm{deg}u+\mathrm{deg}v>n$, they hold together for some $i$. Following the path from $u$ to $A_i$, crossing to $v$, following the remaining path backwards to $B_i$, and crossing back to $u$ gives a Hamilton cycle already in the original maximal graph. This contradiction proves the stated Hamiltonicity criterion.

For $n=2m$, two disjoint copies of $K_{m,m}$ have $n$ vertices in each class and minimum degree $m$. For $n=2m+1$, the disjoint union $K_{m,m+1}\bigsqcup K_{m+1,m}$ has $n$ vertices in each class and minimum degree $m$. Both are disconnected and hence non-Hamiltonian. Thus the sharp counterexamples have $\boxed{\delta =\lfloor n/2\rfloor }$ for every $n\ge 2$.

A matching in a graph from $X$ to $Y$ is a collection of edges with disjoint endpoints covering every vertex of $X$; equivalently it chooses a distinct neighbour in $Y$ for each $x\in X$. For a finite bipartite graph, the Hall marriage theorem says this exists exactly when $|N(A)|\ge |A|$ for every $A\subseteq X$. Necessity follows by counting the distinct matched neighbours.

For sufficiency, induct on $|X|$. If a nonempty proper subset $A$ is tight, $|N(A)|=|A|$, Hall's condition holds on $(A,N(A))$. It also holds on $(X\setminus A,Y\setminus N(A))$: for $B\subseteq X\setminus A$, the original condition applied to $A\cup B$ gives $|N(B)\setminus N(A)|\ge |B|$. Induction provides two disjoint matching in a graph whose union covers $X$. If no nonempty proper subset is tight, choose an edge $xy$, possible by Hall's condition. Delete its endpoints. Each nonempty subset of $X\setminus \{x\}$ had at least one extra neighbour, so deleting $y$ leaves Hall's condition intact. Induction and then the edge $xy$ finish the proof. The single-vertex case is immediate.

For the degree condition, fix $A\subseteq X$ and double-count with weights:Every denominator is nonzero; the last inequality uses $d(y)\le d(x)$ along each edge. The Hall marriage theorem therefore proves the required matching exists. Finiteness, as in the usual course version of the theorem, is understood; the same proof covers a finite $X$ with arbitrary $Y$ and finite degrees.

An extreme point of a convex set cannot be written as a nontrivial convex combination of two distinct members. If a permutation matrix $P=\theta B+(1-\theta )C$ with $0<\theta <1$ and $B,C$ doubly stochastic, each zero entry of $P$ forces the corresponding entries of $B,C$ to be zero by nonnegativity. The unique possible nonzero entry in each row must then be one by the row sum. Thus $B=C=P$, proving that every permutation matrix is extreme.

Conversely, let $A$ be a doubly stochastic matrix that is not a permutation matrix. At least one entry lies strictly between zero and one. Form a bipartite graph whose two vertex classes are rows and columns, with edges precisely at these fractional entries. Every incident row has at least two fractional entries: a single fractional entry, with all other entries zero or one, could not give row sum one. The same holds for columns.

A finite nonempty graph whose incident vertices all have degree at least two contains a cycle. In a bipartite graph that cycle has even length. Assign alternating signs $+1,-1$ to its entries, giving a nonzero matrix $D$ with every row and column sum zero. Choose $\epsilon >0$ smaller than the distance of each cycle entry from both zero and one. Then $A+\epsilon D$ and $A-\epsilon D$ remain doubly stochastic matrices, are distinct, and satisfySo $A$ is not extreme. ThereforeThis alternating-cycle perturbation of a doubly stochastic matrix proves the extreme-point part of the Birkhoff-von Neumann theorem directly.

For a family $\mathcal{F}\subseteq \left(\genfrac{}{}{0ex}{}{[n]}{r}\right)$, let its lower shadow $\partial \mathcal{F}$ consist of all $(r-1)$-sets contained in members of $\mathcal{F}$. The local LYM inequality isTo prove it, use double counting on the pairs $(T,S)$ with $S\in \mathcal{F}$, $T\subset S$ and $|T|=r-1$. Each $S$ contributes $r$ pairs; each $T\in \partial \mathcal{F}$ contributes at most $n-r+1$. Hence $r|\mathcal{F}|\le (n-r+1)|\partial \mathcal{F}|$, exactly the displayed Local LYM inequality after using $r\left(\genfrac{}{}{0ex}{}{n}{r}\right)=(n-r+1)\left(\genfrac{}{}{0ex}{}{n}{r-1}\right)$.

To deduce the LYM inequality, start with an antichain $\mathcal{A}$ in the Boolean lattice and assign it weight ${\sum }_{S\in \mathcal{A}}{\left(\genfrac{}{}{0ex}{}{n}{|S|}\right)}^{-1}$. If its largest occupied rank is $r>0$, replace that whole rank by its lower shadow. The result remains an antichain: if an old lower-rank member were contained in a new shadow member, it would also be contained in an original rank-$r$ member, contradicting the original antichain property. Nor can a new member be contained in an old one, since every old member has size at most $r-1$ and equality would give the same contradiction. The Local LYM inequality shows that this replacement does not decrease the weight. Repeating eventually leaves an antichain on rank zero, whose weight is at most one. ThereforeFor the empty family the conclusion is immediate; the same argument includes the singleton family containing the empty set.

The antichains of maximum size are exactly the full middle levels. More precisely, for even $n$ only $\left(\genfrac{}{}{0ex}{}{[n]}{n/2}\right)$ attains the bound in Sperner theorem; for odd $n$ either $\left(\genfrac{}{}{0ex}{}{[n]}{(n-1)/2}\right)$ or $\left(\genfrac{}{}{0ex}{}{[n]}{(n+1)/2}\right)$ does. To prove that there are no others, put $M=\left(\genfrac{}{}{0ex}{}{n}{\lfloor n/2\rfloor }\right)$. If $|\mathcal{A}|=M$, the LYM inequality and $\left(\genfrac{}{}{0ex}{}{n}{r}\right)\le M$ imply equality in every term's bound $1/\left(\genfrac{}{}{0ex}{}{n}{r}\right)\ge 1/M$. Thus every member lies on a middle level. For even $n$, there is only one such level, so it must be full.

For odd $n=2r+1$, let $X$ be the rank-$r$ members and $Y$ the rank-$(r+1)$ members. Consider the bipartite graph of inclusions between those levels. Both parts have size $M$, and the degree of a vertex is $r+1$. If $N(X)$ is the neighbourhood of $X$, double counting gives $|N(X)|\ge |X|$. Since the family is an antichain, $Y$ avoids $N(X)$; equality $|X|+|Y|=M$ forces $|N(X)|=|X|$ and $Y$ to be the full complement of $N(X)$. Equality in the degree count means that every edge into $N(X)$ comes from $X$, so there are no edges between $X\cup N(X)$ and its complement.

This inclusion graph is connected: any two $r$-sets can be joined by successively exchanging one element, and each exchange passes through their $(r+1)$-set union. Every upper vertex has a lower neighbour. Thus $X$ must be empty or the whole lower level, proving the classification. For $n=1$ the graph is just one edge, and for $n=0$ the unique maximum family is $\{\varnothing \}$. This establishes equality in Sperner theorem without assuming that equality in the LYM inequality alone always forces a middle level.

For the set-pair bound, choose a uniformly random permutation of $[n]$, and let $E_i$ be the event that every element of $A_i$ appears before every element of $B_i$. Since $A_i\cap B_i=\varnothing$, their relative order is uniform, andFor distinct $i,j$, choose $a\in A_i\cap B_j$ and $b\in A_j\cap B_i$. These are distinct because $A_i\cap B_i$ is empty. On $E_i$, $a$ precedes $b$; on $E_j$, $b$ precedes $a$. Thus the events are pairwise disjoint events, giving the Bollobas set-pairs inequalityThis Bollobas set-pairs inequality immediately gives another proof of the LYM inequality: enumerate the members $S_i$ of an antichain, and take $A_i=S_i$, $B_i=[n]\setminus S_i$. For $i\ne j$, incomparability means $S_i\setminus S_j\ne \varnothing$, while $A_i\cap B_i=\varnothing$. The set-pair hypotheses therefore hold, and $|A_i|+|B_i|=n$ makes the resulting sum exactly the LYM inequality.

Let ${\sigma }_1=\gamma ,{\sigma }_2,\dots$ be the singular values of the normalized adjacency operator of a bipartite graph, with the uniform inner products used above. Its ordinary matrix in an orthonormal basis on each side is $G/\sqrt{|X||Y|}$. Expanding the trace of $({\theta }_G{\theta }_G^{\ast }{)}^2$ proves the box norm singular-value identityTherefore (ii) immediately implieswhich is (iii).

Conversely, the square of the Hilbert-Schmidt norm of this operator issince a graph indicator function takes values zero and one. Under (iii), every ${\sigma }_j$ with $j\ge 2$ is at most $c_3$, soThus (iii)$\Rightarrow$(ii) with $\boxed{c_2=c_3^2/4}$. This bound also covers the empty and complete bipartite graphs.

Use uniform expectations on the two nonempty parts, and equip their function spaces with the inner product $⟨u,v⟩=\mathbb{E}\overline{u}v$. Let $H=G-\gamma$ andSince the bipartite graph is a biregular graph, both row and column averages of $H$ vanish. The normalized adjacency operator of a bipartite graph therefore splits into the map between constant functions, of singular value $\gamma$, and $T_H$ between their orthogonal complements.

There is no singular value larger than $\gamma$. Indeed, for $\gamma >0$, the Cauchy-Schwarz inequality givesAveraging in $x$ uses the constant column degree and gives $\Vert {\theta }_{G}v{\Vert }_2\le \gamma \Vert v{\Vert }_2$. For $\gamma =0$ every operator is zero. Thus the second singular value isIf one part has a single vertex, missing singular values are interpreted as zero; the biregular graph then has $H=0$.

The discrepancy in (i) is exactly $\mathbb{E}H{1}_A{1}_B$. Its supremum over $A,B$ is the cut norm $\delta =\Vert H{\Vert }_{\mathrm{cut}}$. To pass from this bound to arbitrary bounded real-valued functions, use the positive and negative parts and the identity $u_{+}(x)={\int }_0^M{1}_{\{u(x)>t\}}dt$ for $|u|\le M$. Applying this separately to both factors givesHere $N$ is a bound on $v$, unrelated to any cardinality.

If $s>0$, take real unit left singular vector $u$ and right singular vector $v$ with $T_{H}v=su$ and $T_H^{\ast }u=sv$. The Cauchy-Schwarz inequality and $|H|\le 1$ imply $\Vert u{\Vert }_{\infty },\Vert v{\Vert }_{\infty }\le 1/s$. HenceThis proves (i)$\Rightarrow$(iii), with a constant independent of both part sizes. The case $s=0$ satisfies the same conclusion immediately.

Use a directed bipartite graph with one vertex for each job and one for each agent. Job vertices have supply $1$ and agent vertices demand $1$. An arc from job $i$ to agent $j$ has cost $c_{ij}$ and nonnegative flow $x_{ij}$; an upper bound $1$ may be added, but is already implied by the balances. The minimum-cost flow formulation of the assignment problem isInteger supplies and demands give an integral optimum by integrality of the transportation problem. Its $n$ positive arcs form a perfect matching, hence give one job per agent.

A network simplex algorithm basis for this connected $2n$-vertex network has $2n-1$ tree arcs, whereas an integral assignment has only $n$ positive flows. For $n>1$, at least $n-1$ basic tree arcs therefore carry zero flow. This unavoidable degeneracy in linear programming can cause zero-step pivots, extra bookkeeping and cycling unless an appropriate pivot rule is used. The Hungarian algorithm exploits the assignment structure directly rather than maintaining many zero-flow basic arcs.

Suppose the assignment dual potentials satisfy ${\lambda }_i-{\mu }_j\le c_{ij}$. For every feasible assignment $y$,If the selected assignment $x$ uses only arcs with ${\lambda }_i-{\mu }_j=c_{ij}$, its cost equals this lower bound. Weak duality and complementary slackness certify optimality. The PDF correctly denotes the feasible assignment by $x_{ij}$; the TeX aid mistakenly replaces it with ${\lambda }_{ij}$.

The Hungarian algorithm maintains feasible assignment dual potentials and a matching in a graph of zero reduced cost edges, where $r_{ij}=c_{ij}-{\lambda }_i+{\mu }_j\ge 0$. Search for an augmenting path in a matching in this equality graph. If there is none, let $S$ be the reachable jobs and $T$ the reachable agents in the alternating search from unmatched jobs. Every agent in $T$ is matched to a job in $S$. SetReduced costs from $S$ to its complement decrease by $\Delta$, those from outside $S$ into $T$ increase, and the remaining ones do not change. Thus feasibility and current matching equalities are preserved, while at least one new equality edge appears. Continue until an augmenting path in a matching increases the matching size. A perfect matching in the equality graph then has the same value as the dual linear program and is optimal.

For the example, start with the row minima $\lambda =(10,50,50)$ and $\mu =(0,0,0)$. The reduced cost matrix isMatch job $1$ to agent $1$. Searching from both unmatched jobs gives $S=\{1,2,3\}$ and $T=\{1\}$; the minimum cost to an agent outside $T$ is $\Delta =10$. Update to $\lambda =(20,60,60)$ and $\mu =(10,0,0)$:The new equality edge $(2,3)$ augments the matching. From unmatched job $3$, the next alternating search reaches agent $1$ and its matched job $1$, giving $S=\{1,3\}$ and $T=\{1\}$. Now $\Delta =15$. The updated feasible assignment dual potentials and reduced costs areThe augmenting path in a matching $J_3\to A_1\to J_1\to A_2$ uses job $3$ to agent $1$, the reversed matched edge to job $1$, then the new edge to agent $2$. It gives the optimal assignmentThe dual linear program value is $35+60+75-25=145$, an independent optimality certificate.

Let $R$ interchange the two complete graphs, sending $v_i$ to $v_i^{\prime }$ and fixing $w$. This involution preserves the transition matrix of the simple random walk. A mirror coupling under an involution starts $X$ at $v_i$, keeps $Y_t=R(X_t)$ until the hitting time $\tau$ of $w$, and then makes the two walks move identically. Each coordinate has the correct transition probabilities, and they coalesce precisely at $\tau$. The coupling inequality for total variation gives

There is a genuine error in the printed expected hitting time bound, as well as an unspecified initial law. For $n\ge 2$, write $a={\mathbb{E}}_{v_1}\tau$ and $b={\mathbb{E}}_{v_i}\tau$ for $i\ne 1$. From every clique vertex there is a positive chance of reaching $w$ within two steps, uniformly over the finite state space for each fixed $n$, so $\tau$ has finite expected value. First-step analysis, using the degree of a vertex $n$ at $v_1$ and $n-1$ at the other clique vertices, givesSolving these linear equations yieldsIn particular even the attachment vertex exceeds the printed bound by one. The valid uniform replacement is ${\max }_x{\mathbb{E}}_x\tau \le n^2$, the hitting time of the bridge vertex between two cliques formula.

We must also handle arbitrary starting states, including $w$, before applying the mirror argument. Identify related vertices and consider the lumped Markov chain $Z$ on $\{1,\dots ,n,w\}$. Its transition matrix $Q$ has $Q(1,j)=1/n$ for $j\ne 1$, $Q(1,w)=1/n$, $Q(i,j)=1/(n-1)$ for $i\ne 1$ and $j\ne i$, and $Q(w,1)=1$, with all other entries zero. Here the row for $i\ne 1$ only ranges over $j\in \{1,\dots ,n\}$.

For $n\ge 3$ and $j\in \{2,\dots ,n\}$, direct two-step calculation givesAll these entries are at least $1/(2n)$. Thus $Q^2(z,\cdot )\ge \alpha \nu (\cdot )$ for every $z$, where $\nu$ is the uniform distribution on a finite set $\{2,\dots ,n\}$ and $\alpha =(n-1)/(2n)\ge 1/3$. This is a Doeblin condition. At each two-step block couple the two quotient endpoints to the same sample from $\nu$ with probability $\alpha$, using the residual probability distributions otherwise. The first successful block has expected value at most $1/\alpha$, so the alignment time $A$ has $\mathbb{E}A\le 6$. Lift each endpoint coupling of probability distributions to the original walks by their conditional two-step path laws; this preserves every marginal path law. The success test uses fresh block randomness and so permits restarting the walks with their original transition matrix at the aligned endpoints.

At alignment the original walks are equal or related. Use identical transitions in the first case and the mirror coupling under an involution in the second. The resulting coalescing coupling has coalescence time $T$ satisfying $\mathbb{E}T\le 6+n^2$ for every pair of initial states. Therefore Markov inequality and the pairwise mixing diameter implyFor the hint's particular starting states, the quotient one-step laws from two different clique indices have a common component of mass at least $1-2/n$: for two ordinary indices it is $(n-2)/(n-1)$; for one attachment index it is $(n-2)/n$. A maximal coupling therefore aligns those indices with probability $1-O(1/n)$, as suggested. The two-step argument above additionally covers $w$.

The nonlazy walk is an aperiodic Markov chain for $n\ge 3$, because the connected graph contains a triangle. For $n=1,2$ it is a periodic Markov chain on a bipartite graph; each bipartition class has stationary mass $1/2$, and the walk stays on a single class at each time. Hence $d(t)\ge 1/2$ and the $1/4$ mixing time is infinite. The asymptotic conclusion is valid for $n\ge 3$.

For a finite bipartite graph with left vertex set $L$, Hall marriage theorem says that a matching in a graph covering $L$ exists exactly when $|N(S)|\ge |S|$ for every $S\subseteq L$. Necessity follows because distinct matched neighbors of $S$ lie in $N(S)$.

For sufficiency, induct on $|L|$, the empty case being immediate. If a nonempty proper subset $S$ has $|N(S)|=|S|$, apply the induction hypothesis to the graph on $S,N(S)$. For the remaining graph, every $T\subseteq L\setminus S$ satisfiesso induction matches the remaining vertices too. If there is no such tight subset and $|L|>1$, every nonempty proper subset has at least one extra neighbor. Select an edge and remove its endpoints. Each subset of the remaining left vertices loses at most one neighbor, so it still satisfies the required condition; induction supplies the rest of the matching in a graph. The case $|L|=1$ follows directly from the condition.

For a doubly stochastic matrix $A=(a_{ij})$, make a bipartite graph joining row $i$ to column $j$ when $a_{ij}>0$. For a row subset $S$,Hall marriage theorem therefore gives a perfect matching, or a permutation $\sigma$, with $\boxed{a_{i,\sigma (i)}>0\text{ for every }i}$.

A cut is a partition $(S,T)$ of the vertices with the source in $S$ and sink in $T$; its capacity is the sum of capacities of directed edges from $S$ to $T$. The max-flow min-cut theorem says that maximum flow value equals minimum cut capacity. With integral capacities, there is an integral max-flow theorem attaining the maximum.

Construct a bipartite graph with one vertex for each row and column and an edge $r_i\to c_j$ whenever $A_{ij}=1$. Add source-to-row and column-to-sink edges of capacity $1$, and give row-to-column edges infinite capacity. An integral flow is precisely a set of independent $1$s, so its maximum value is the largest such set.

A finite-capacity cut places some rows on the sink side and some columns on the source side; these lines cover every $1$, since an uncovered row-to-column edge would cross the cut with infinite capacity. Its capacity is the number of selected lines. Conversely every line cover defines such a cut. Max-flow min-cut therefore proves the maximum number of independent $1$s equals the minimum number of covering lines, the matrix form of König's theorem for bipartite matching.

Symmetrization for an arbitrary real coefficient. Among graphs maximizing $f(G)=e(G)-c{k}_3(G)$, choose one maximizingFor a vertex $x$, put $L(x)=d(x)-ce(G[N(x)])$. This is the contribution of edges and triangles in a graph containing $x$. If $u,v$ are nonadjacent, Zykov symmetrization replacing $u$ by a clone of $v$ changes $f$ by $L(v)-L(u)$; the opposite replacement changes it by $L(u)-L(v)$. Maximality implies $L(u)=L(v)$, so both changes preserve $f$.

Let $S=N(v)\setminus N(u)$ and $T=N(u)\setminus N(v)$. In the first replacement the vertex degrees in $S$ increase by one and those in $T$ decrease by one; in the opposite replacement these changes reverse. The changes to $d(u{)}^2+d(v{)}^2$ cancel when the two replacements are added. Since $(d+1{)}^2+(d-1{)}^2-2d^2=2$,If the two vertex neighbourhoods differ, one replacement increases $Q$, a contradiction. Thus every pair of nonadjacent vertices has the same vertex neighbourhood. Nonadjacency, with equality allowed, is an equivalence relation: if $u$ and $v$ are nonadjacent and $v$ and $w$ are nonadjacent, their identical vertex neighbourhoods forbid $uw$ as well. Its classes are independent sets and every cross-class edge is present. ThereforeThis edge-triangle symmetrization works for either sign of $c$.

The exact supporting line. For $n\ge 3$, writeWe prove the triangle support line between bipartite and tripartite Turan graphs by maximizing $e-c_{\ast }{k}_3$. First $c_{\ast }\ge 2/n$. For $n=3,4,5$, its values are respectively $1,1/2,1/2$. For $n\ge 6$, the exact balancing of the Turan graph gives $e_3\ge n^2/3-1/3$, while $e_2\le n^2/4$ and the arithmetic-geometric mean inequality gives $t_3\le n^3/27$. Hence

By edge-triangle symmetrization a maximizing graph can be taken complete multipartite graph; among such maximizers use one with the fewest nonempty parts. If there are at least four parts, let $a,b$ be the two smallest sizes. Then $a+b\le n/2$. Merging them loses $ab$ edges and $ab(n-a-b)$ triangles in a graph, so the objective changes byThis contradicts the choice of the number of parts. Thus at most three parts remain.

For three part sizes $a\ge b\ge d>0$, the objective isIf $1-c_{\ast }b\le 0$, merging the parts of sizes $a,d$ does not decrease it, again contradicting minimality. If $1-c_{\ast }b>0$ and $a-d\ge 2$, transferring one vertex from the largest to the smallest part raises $ad$ by $a-d-1>0$ and strictly increases the objective. Thus a three-part maximizer has all sizes differing by at most one, and is $T_3(n)$. A maximizer with at most two parts has objective at most $e_2$, since it has no triangles in a graph and the Mantel theorem bounds its edges. Finally,Therefore every graph satisfies $e(G)-c_{\ast }{k}_3(G)\le e_2$. At the prescribed edge count this givesFor $n\le 2$, the conclusion is simply the nonnegative lower bound zero. All rounding in the Turan graphs has been retained.