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In cylindrical coordinates the saddle-focus linearization isUse a small incoming neighborhood of the stated section point $(\rho ,0,-\mu )$. A nearby incoming cylinder $r=\rho$ is smoothly equivalent to that section for this calculation. Denote the positive unstable passage coordinate by $x=z_{\mathrm{in}}>0$ and leave at $z=h$. ThenThe global map is smooth in the outgoing Cartesian coordinates $r_{\mathrm{out}}\cos {\theta }_{\mathrm{out}}$ and $r_{\mathrm{out}}\sin {\theta }_{\mathrm{out}}$. Its returned unstable coordinate therefore has the leading formCombining the two trigonometric terms, absorbing the fixed scales into the amplitude and phase, and using the evenness of cosine givesThe returned radial section coordinate is $\rho +O(x^{\delta })$, supplying the thin transverse direction of the full two-dimensional return. In particular its determinant has order $x^{2\delta -1}$; the exponent is also obtained by integrating the flow divergence ${\lambda }_{+}+2{\lambda }_{-}$ over the local flight. Thus $\delta >1/2$ is the volume-contracting range. Corrections from the returned radial deviation enter at order $x^{2\delta }$, smaller than the fixed-point term $x$ in this range. Only positive returned $x$ on the chosen branch belong to the scalar return domain.

For $\delta >1$,For small $\mu <0$, there is one small attracting fixed point $x=-\mu +O(|\mu {|}^{\delta })$, representing a stable long-period periodic orbit. It ends in the homoclinic connection at $\mu =0$; for $\mu >0$ there is no sufficiently small positive fixed point. The oscillations alone do not create expanding chaos when their derivative tends to zero.

For $1/2<\delta <1$, there is both net volume contraction and a positive saddle equilibrium value ${\lambda }_{+}+{\lambda }_{-}>0$. At the connection, fixed points satisfyThe right side tends to zero, while the phase runs through infinitely many rotations. There are therefore infinitely many positive fixed points accumulating at zero near successive cosine zeros. Their successive size ratios tend to $e^{-\pi /q}$ and their derivative magnitudes diverge. In the full return they are saddle equilibrium periodic orbits: one multiplier expands and the thin transverse direction contracts. Their flow periods grow as ${\lambda }_{+}^{-1}\log (h/x)$.

The oscillatory graph also supplies the complicated itineraries. Take a sufficiently small positive return interval. Near successive zero crossings, narrow monotone subintervals map across that interval with arbitrarily large slope. Two or more inverse branches contract into it, so repeated inverse choices give symbolic invariant sets just as in part (a); lifting the strips to the thin two-dimensional return gives horseshoes and infinitely many periodic orbits. This explains the Shilnikov chaotic mechanism rather than only naming it.

For nonzero splitting, the graph shifts vertically. Fixed-point tangencies with slope $+1$ create saddle-node bifurcations of periodic orbits; crossings of slope $-1$ give period doubling. Near an oscillatory extremum the derivative can be small, allowing stable periodic windows. Such thresholds accumulate geometrically toward the homoclinic parameter, interspersed with expanding returns. Hence the unfolding can contain complicated switching, arbitrarily long periods and chaos, rather than a single attracting periodic branch. This is log-periodic accumulation of Shilnikov cycles. The conclusion concerns invariant sets and possible attractors allowed by the return geometry; it does not assert that a homoclinic connection alone makes all nearby trajectories chaotic.

A symplectic manifold is a smooth even-dimensional manifold $X^{2n}$ with a closed, nondegenerate differential two-form $\omega$. A Lagrangian submanifold $L\subset X$ has dimension $n$ and $\omega {|}_{TL}=0$; equivalently $T_{x}L=(T_{x}L{)}^{\omega }$ at every point.

On $T^{\ast }M$, let $\pi :T^{\ast }M\to M$ and define the canonical one-form on a cotangent bundle by ${\theta }_{(q,p)}(v)=p(d\pi (v))$. In local coordinates $\theta ={\sum }_i{p}_{i}d{q}_i$, so our sign convention givesThe intrinsic definition of $\theta$ makes this form globally defined. It is closed because $d^2=0$, and its displayed coordinate matrix is invertible. The zero section pulls $\theta$, and therefore ${\omega }_0$, back to zero and has half the total dimension. It is a Lagrangian submanifold.

We prove the Weinstein neighborhood theorem, rather than merely invoking it. Along a Lagrangian submanifold $L\subset (X,\omega )$, choose a compatible almost complex structure $J$; its existence is proved by the metric construction in Question 5. Then $JL$ at the tangent-bundle level means $J(TL)$, andIndeed, $Jv\in TL$ with $v\in TL$ would imply $0=\omega (v,Jv)$, forcing $v=0$. Also $\omega (Ju,Jv)=\omega (u,v)=0$ for $u,v\in TL$, so $J(TL)$ is a Lagrangian complement. Identify a normal vector $n\in J(TL)$ with the covector $\eta (v)=\omega (v,n)$. This is a vector-bundle isomorphism with $T^{\ast }L$, and under itwhich is exactly the form ${\omega }_0$ along the zero section. The tubular neighborhood theorem therefore supplies a smooth map $F$ from a neighborhood of that section to a neighborhood of $L$, restricting to the identity and with this derivative along $L$.

Write ${\omega }_1=F^{\ast }\omega$ and $\delta ={\omega }_1-{\omega }_0$. This closed differential form vanishes as an entire bilinear form along the zero section. The relative Poincaré lemma gives $\delta =d\beta$ with $\beta$ zero along the section. Explicitly, if $r_s(q,p)=(q,sp)$ and $R=\sum p_i{\partial }_{p_i}$, useThe homotopy identity gives $d\beta =\delta -r_0^{\ast }\delta =\delta$; the vanishing at the section ensures smoothness of this integral. The forms ${\omega }_t={\omega }_0+t\delta$ are nondegenerate on a sufficiently small neighborhood of the section for all $0\le t\le 1$. Solve uniquelyThe vector field $Y_t$ vanishes on the section. After another neighborhood shrink its flow ${\varphi }_t$ exists up to time one and fixes the section. For noncompact $L$, the sizes of these neighborhoods may vary with the base point; no compactness of $L$ is required for the local conclusion. By Cartan's magic formula,Thus $(F\circ {\varphi }_1{)}^{\ast }\omega ={\omega }_0$. This establishes the universal neighborhood model, with the Lagrangian submanifold identified with the zero section.

For the section $s_{\alpha }(q)=(q,{\alpha }_q)$, the canonical differential one-form satisfies $s_{\alpha }^{\ast }\theta =\alpha$. HenceIts dimension is already half that of $T^{\ast }M$, so vanishing of this pullback is sufficient as well as necessary.

Suppose now that a smooth open six-dimensional region were a fiber bundle with Lagrangian submanifolds diffeomorphic to $S^3$ as its fibres. Fix one compact fibre $L$. Smooth local triviality and compactness imply that the other sufficiently nearby fibres are $C^1$-close embeddings of $L$. In the Weinstein neighborhood, projection to $L$ restricts on each such fibre to a local diffeomorphism close to the identity. It has degree one, and compactness makes it a covering map, so it is a diffeomorphism. Each nearby fibre is therefore a graph of a closed differential one-form $\alpha$ on $S^3$. Since $H^1(S^3;\mathbb{R})=0$, this is $df$ for a smooth real function $f$. A maximum of $f$ exists by compactness, and there $df=0$. The graph meets the original zero section, contradicting disjointness of different fibres. No such Lagrangian three-sphere fibration exists. More generally this is the compact first-cohomology obstruction to a Lagrangian fibration.

Orient each edge both ways. A unit flow $j$ from $x$ to $y$ is antisymmetric, $j(u,v)=-j(v,u)$, with divergence of a flow equal to $+1$ at $x$, $-1$ at $y$ and zero elsewhere. Its energy iswhere each unoriented edge is counted once. Put $c_e=1/r_e$. The electrical unit current is $i(u,v)=c_{uv}(V(u)-V(v))$, where the potential $V$ solves the Kirchhoff node law with those source and sink divergences. Because $G$ is a connected graph, this potential is unique up to an additive constant. The effective resistance is the electric potential difference needed for unit current,Discrete summation by parts gives ${\mathcal{E}}_r(i)={\sum }_{u}V(u)\mathrm{div}i(u)=R(x,y)$.

The Thomson principle says that this current minimizes energy among all unit flows. Indeed write any other unit flow as $j=i+k$, where $\mathrm{div}k=0$. ThenConsequentlyThis also proves uniqueness of the minimizing current.

If $r_e^{\prime }\ge r_e$ for every edge, then ${\mathcal{E}}_{r^{\prime }}(j)\ge {\mathcal{E}}_r(j)$ for every admissible flow. The admissible set is unchanged, so taking its minimum proves the Rayleigh monotonicity principle:Deletion is the limiting operation $r_e\to \infty$: finite-energy flows must then carry zero current on that edge. If the terminals become disconnected, the effective resistance is infinite.

Take a finite directed flow network with distinct source $s$, sink $t$ and finite nonnegative flow network edge capacities. A flow assigns $f_e$ to each edge with $0\le f_e\le c_e$ and obeys flow conservation at every vertex except $s,t$. Its value is net outflow from the source, $|f|={\sum }_{s\to v}{f}_e-{\sum }_{v\to s}{f}_e$. A maximal flow here means a maximum flow: one with greatest value among feasible flows. A source-to-sink cut of a flow network is a partition $(S,S^c)$ with $s\in S$, $t\notin S$; its cut capacity is $c(S)={\sum }_{u\in S,v\notin S}{c}_{uv}$, counting directed edges leaving $S$.

The max-flow min-cut theorem statesSumming conservation over $S$ cancels internal edges and givesThis is the upper bound for every flow and every cut. To prove equality, a maximum exists: the feasible edge vectors form a nonempty closed bounded subset of a finite-dimensional real space, and flow value is continuous.

For a maximum $f$, construct its residual network. Each edge has a forward residual edge of capacity $c_e-f_e$ and a backward residual edge of capacity $f_e$; retain those of positive capacity. If a residual source-to-sink path existed, augment by the smallest residual capacity on that finite path. Increasing original forward flows and decreasing backward flows preserves all feasibility conditions and increases value, contradicting maximality. Thus no such augmenting path exists.

Let $S$ be the vertices reachable from $s$ in the residual network. Then $t\notin S$. Every original edge leaving $S$ is saturated, since otherwise its positive forward residual edge would make its endpoint reachable. Every original edge entering $S$ has zero flow, since otherwise its backward residual edge would give the same contradiction. HenceTogether with the universal upper bound this proves equality and identifies a minimum cut. This proof covers real capacities without assuming that an augmenting-path algorithm terminates after finitely many steps. Merely being impossible to increase all edge flows coordinatewise is not the optimization meaning of “maximal” used in the theorem.

Label the two intermediate vertices $1,2$. The four outer edges have capacity $M$ and the middle edge has capacity one. The cut separating $s$ from the other vertices has capacity $2M$, and the two paths $s\to 1\to t$ and $s\to 2\to t$ can each carry $M$. Thus the maximum flow is $2M$.

A fast run of the Ford-Fulkerson algorithm chooses those two direct paths and augments by $M$ on each: it terminates in two augmentations. One augmentation cannot suffice, because every initial path has bottleneck at most $M$.

For a run with $M+1$ augmentations, first choose $s\to 1\to 2\to t$ and augment by one. The middle edge then has net flow $1$ from $1$ to $2$. Its reverse residual capacity is $1-(-1)=2$, not one. Alternate crossing paths, next $s\to 2\to 1\to t$, then $s\to 1\to 2\to t$, and so on. Each of the next $M-1$ augmentations has bottleneck two. More explicitly, after $k$ crossing augmentations, $1\le k\le M$, the total flow is $2k-1$, and the outer-edge flow totals on the pairs $(s1,2t)$ and $(s2,1t)$ are $k$ and $k-1$ in one order or the other. The middle net flow is $\pm 1$. The next opposite crossing path uses the less-loaded outer pair and has reverse-middle capacity two. Until $k=M$, its outer residual capacities are at least two.

After these $M$ augmentations, one outer pair is full and the other has one unit left. One final opposite crossing augmentation of one reaches $2M$. The total amounts are $1$, then $M-1$ copies of $2$, then $1$, giving exactly $M+1$ augmentations. For $M=1$ the middle block is empty and this gives two augmentations as well. These are explicit requested path-choice histories. In an undirected network, $M+1$ need not be a bound on every possible history: for $M=2$, choosing the crossing path, the two direct paths, and then the crossing path again gives four successive unit augmentations.

For a general undirected network, let $y_{ij}=x_{ij}-x_{ji}$ be the antisymmetric net flow. Feasibility gives $|y_{ij}|\le c_{ij}$, so the directed residual network has nonnegative capacities $c_{ij}^{\prime }=c_{ij}-y_{ij}$. For any cut $S$ with $s\in S$, $t\notin S$, conservation at the internal vertices givesThus its outgoing residual cut capacity isThe subtracted flow value is the same for every cut. Taking the minimum and applying the max-flow min-cut theorem to the original and residual networks proves the residual maximum flow is the remaining optimality gap identity

Suppose now $f^{\prime }>0$, and let $U$ consist of vertices reachable from $s$ through residual arcs of capacity at least $f^{\prime }/m$. If $t\notin U$, every outgoing arc from $U$ has capacity strictly below $f^{\prime }/m$, since its head would otherwise be reachable. At most $m$ original undirected edges cross this cut, and each supplies exactly one outgoing directed arc. Hence $C^{\prime }(U)<m(f^{\prime }/m)=f^{\prime }$, contradicting the residual minimum-cut value $f^{\prime }$. Therefore $\boxed{t\in U}$, and a widest augmenting path has bottleneck at least $f^{\prime }/m$. When $f^{\prime }=0$, the current flow is already optimal and no such path is needed.

Let $F_k$ be the remaining residual maximum flow after $k$ augmentations of the modified rule, starting from zero flow. Its chosen widest path increases the flow by at least $F_k/m$, soThis is the geometric convergence of widest-path augmentation. For $m\ge 2$, $F_k\le e^{-k/m}{f}^{\ast }$. Starting from zero with integer capacities keeps all flow values and residual optimality gaps integer. Thus $k>m\ln f^{\ast }$ makes $F_k<1$ and hence $F_k=0$, giving termination in $\boxed{O(m\log f^{\ast })}$ augmentations for $f^{\ast }\ge 2$. If $f^{\ast }=1$, one positive integer augmentation suffices; if $f^{\ast }=0$, none is required. A uniform statement is $O(m\log (1+f^{\ast }))$. With $m=1$, a nonzero flow is also completed in one augmentation, consistent with the recurrence's zero contraction factor.

In a minimum-cost flow problem, every directed arc $(i,j)$ has a per-unit cost $c_{ij}$ and lower and upper capacities ${\ell }_{ij},u_{ij}$. Each vertex has a prescribed net supply $b_i$, with ${\sum }_i{b}_i=0$. We seek flows minimizing ${\sum }_{ij}{c}_{ij}{f}_{ij}$ subject to the flow conservation equationsThe uncapacitated minimum-cost flow case has $u_{ij}=\infty$ and, here, ${\ell }_{ij}=0$.

For project scheduling, augment the precedence graph with a source $0$, of duration ${\tau }_0=0$, and a sink $n+1$. Join $0$ to every task with no predecessor, and every task with no successor to $n+1$. Extend the precedence matrix to these dummy arcs. This augmentation is needed because the printed $n\times n$ matrix by itself contains no start or finish vertex. Assuming the precedence graph is a Directed acyclic graph, every task lies on a source-to-sink path. Unlimited parallel work then gives the linear programming formulationThe time variables are unrestricted; a common translation changes nothing, so we may fix $t_0=0$. These inequalities say that each successor starts after its predecessor finishes. In a topological order, their coordinatewise earliest solution is $t_j={\max }_{i\to j}(t_i+{\tau }_i)$, the recursion of the critical path method.

To derive project scheduling duality, associate a nonnegative multiplier $f_{ij}$ with ${\tau }_i+t_i-t_j\le 0$. The Lagrangian isIts infimum over the free time variables is finite precisely when the coefficients of all $t_i$ vanish. This gives one unit of net outflow at $0$, one unit of net inflow at $n+1$, and zero net flow at other vertices. Hence the dual isEquivalently, minimize $\sum c_{ij}{f}_{ij}$ with $c_{ij}=-{\tau }_i$. The project duration is the negative of the optimal minimum-cost flow value. The sign is essential: the dual of the minimization problem maximizes total duration, selecting a longest precedence path.

The network simplex algorithm is a general method for minimum-cost flow. After shifting lower bounds to zero, first find a feasible flow, using artificial arcs and a phase-one objective if needed. A network simplex tree basis fixes each non-tree arc at a bound and determines the tree flows by flow conservation. Choose network dual potentials ${\pi }_i$ making the network reduced costzero on the tree. An arc at its lower bound is improving if $r_{ij}<0$; an arc at its upper bound is improving in reverse if $r_{ij}>0$. Adding that residual arc creates one fundamental cycle. Increase flow around this cycle until an arc reaches a bound, then exchange the entering and leaving tree arcs, or flip the entering arc to its other bound. The flow conservation equations remain satisfied. Use an anti-cycling rule for degenerate pivots. If a negative-cost residual cycle has no finite limiting capacity, the objective is unbounded below; if phase one cannot remove artificial flow, the problem is infeasible. Otherwise, termination with no negative residual network reduced costs certifies optimality, since potentials cancel around cycles and every residual network circulation has nonnegative cost.

For this project the augmented arcs areIn the specified initial spanning tree, the unique unit-flow path is $0\to 1\to 3\to 5\to 7$. The flow on its arcs is one and that on all other tree arcs is zero. Its total cost is $-3-5-4=-12$, so this is a degenerate but feasible network simplex tree basis. Normalizing ${\pi }_0=0$, the tree equations giveThere are two nonbasic arcs. Their network reduced costs areBring $(0,2)$ into the tree. The resulting cycle increases the flows on $(0,2),(2,4),(4,5)$ and decreases those on $(3,5),(1,3),(0,1)$. The three decreasing arcs initially carry one unit, so the maximal step is one. Resolve the leaving-arc tie by removing $(0,1)$. The resulting unit flow follows $0\to 2\to 4\to 5\to 7$ and has cost $-4-6-4=-14$.

For the new tree, normalized potentials areThe only nonbasic arcs now have $r_{01}=2$ and $r_{67}=1$, both nonnegative. All tree network reduced costs vanish, proving optimality after this single pivot. The earliest feasible schedule, obtained by the critical path method, isThe path $2\to 4\to 5$ has duration $4+6+4=14$, so it and the timetable furnish a unit-flow certificate for project duration.