# Intersection forests for fixed horizontal labels **Historical research record (updated 2026-10-12).** The [standalone proof](cubic-bound.en.md) now establishes the general cubic bound. The derivations, remainders, and counterexamples below retain their historical order. Statements that a problem is unresolved refer to that stage or local method; stronger auxiliary claims do not automatically follow from the general bound. An area potential proves $W\le2nN$ when every nonempty horizontal translation intersection of the query is connected. This covers straight comb queries with arbitrary roots and discovery orders. Section 15 also proves a host subclass with unrestricted queries: a constant bound on the multiplicity of vertical-edge column differences between consecutive rows gives $O(nN)$ scans. At the time of this investigation, the bound for general labels was unproved and general worst-case complexity lay between $\Omega(n^3+m)$ and $O(n^3\log(n+1)+m)$; the later general proof closes this gap. ## 1. Successful events and earliest stars Let the induced road forest be $F$, with $N$ vertices in a board of side length $n$. The query root is zero, and its connected prefixes grow in first-discovery order. Write these prefixes as $P_j$. A candidate succeeds at time $j$ only when its entire translated prefix lies in the road set. For each road target $v$, retain all successful nonroot query points and group them by: - the first child edge from the query root; - the row of the query point. The earliest successful point of a group is its star $e$. Each later successful point $f$ forms a marker with that star. Define its label and late candidate by $$ h=f-e=(0,d),\quad d\ne0,\qquad a=v-f. $$ Alternatively, retain only global root-height records and choose the stars again. This gives the height-record variant. It does not count all successful events and must not be confused with the all-success variant. ## 2. The intersection forest and its total resource For a fixed nonzero horizontal label, define $$ G_h=F\cap(F-h)=\{z\in F:z+h\in F\}. $$ This is an induced forest. The two successful prefixes of a genuine marker give $$ a+P_f\subseteq F,\qquad a+h+P_e\subseteq F. $$ Here a query-point subscript denotes the prefix ending at its first discovery. Since the early prefix is contained in the late prefix, $$ \boxed{a+P_e\subseteq G_h.} $$ Thus a marker can be associated with the directed edge $a\to a+e$ and the unique tree path joining its endpoints in the intersection forest. The entire early prefix is in the intersection, including its other branches. The associated edge need not be a grid edge. If row $r$ contains $k_r$ road vertices, summing over all signed horizontal labels counts exactly the ordered pairs of distinct road vertices in the same row: $$ \boxed{\sum_{d\ne0}|G_{(0,d)}| =\sum_r k_r(k_r-1)\le(n-1)N.} $$ Let $M_h$ be the number of markers with label $h$ in the all-success variant, and let $S$ be the total number of successful checks. There are at most four times the board side length stars per target, and each candidate fails at most once. Therefore $$ W\le N+S\le(4n+1)N+\sum_hM_h. $$ Consequently, a uniform constant satisfying $$ M_h\le C|G_h| $$ would imply $$ W\le[4n+1+C(n-1)]N. $$ **This fixed-label inequality remains a conjecture.** The representation and total-resource identity do not themselves bound the marker multiplicity. ## 3. An exact local condition for path capacity Allow each marker to be assigned to any vertex of its associated path, with at most a positive integer $C$ markers assigned to each vertex. Such an assignment exists if and only if, for every nonempty connected vertex set $K$ of the intersection forest, the number of markers whose entire paths lie in $K$ is at most $C|K|$. Necessity is immediate. For sufficiency, take any subset of markers and split the union of their paths into connected components. Each path is contained in one component, and every component is a connected subtree of the intersection forest. Applying the stated condition in each component shows that the total available vertex capacity is at least the number of markers in the subset. Replace each vertex by $C$ copies and apply Hall's theorem. This is an equivalent formulation, not a proof of the local density bound. It is also stronger than the global inequality $M_h\le C|G_h|$: failure of local capacity need not disprove the global count. Section 9 disproves a general constant path capacity for all-success markers. That counterexample does not disprove the unit-label result or the height-record variant. ## 4. Unit horizontal displacements can be paid rigorously **Proposition.** For $h=(0,1)$ and $h=(0,-1)$, both variants can assign their markers to distinct source vertices. Thus both satisfy unit capacity on the complete associated paths. It suffices to prove the positive case. The intersection forest cannot contain a vertical edge: that edge and its translate one column to the right would form a unit square cycle in the road forest. Hence every intersection component is a horizontal path. Consider a marker. Since its entire early prefix is connected, that prefix must be a horizontal interval. Write $$ e=(0,k),\qquad f=(0,k+1). $$ The late point is discovered later and belongs to the same first-child group, so $k\ge1$ and both points lie in the right root branch. Write the early prefix as $[-L,k]$. For the all-success variant, take $j=1$. For the height-record variant, let $(0,j)$ be the first global root-height record in the right root branch. Since the early point is selected, this point exists and satisfies $1\le j\le k$. At its discovery, the prefix is $[-L_j,j]$, where $L_j\le L$. Set $$ b=v-(0,j)=a+(0,k+1-j). $$ On the horizontal line containing these points, this candidate's entire prefix image is $$ [a_x+k+1-j-L_j,\ a_x+k+1], $$ which lies inside the interval already covered by the successful late candidate: $$ [a_x-L,\ a_x+k+1]. $$ Thus this candidate genuinely succeeds at query point $(0,j)$. The event belongs to the same target, first-child group, and row as the original early event. The earliest-star condition forces $k=j$. For the whole fixed positive unit label, the early point and the late point are therefore fixed query points. A source cannot produce two different markers. Assign each marker to its source, which lies on its associated path. Horizontal reflection gives the negative case. This pays only the two unit labels. It does not establish the bound for other horizontal displacements. ## 5. The association graph can have arbitrarily many cycles Acyclicity of the intersection forest does not imply acyclicity of the association graph. In the periodic family from the [historical third-arm counterexample](complexity-branches.en.md), take a multiple of three $H\ge12$. In the normalized row-column coordinates, set $$ h=(0,6),\quad A=(-2,0),\quad B=(-4,-4),\quad w_y=(y,-4). $$ The previously verified inner and outer markers produce $$ A\to w_y,\qquad B\to w_y. $$ For the height-record variant, one can take $$ y\in\{H-2\}\cup\{H-3,H-6,\ldots,3\}, $$ giving a copy of $K_{2,H/3}$. The all-success variant works for every $3\le y\le H-2$, giving $K_{2,H-4}$. For the all-success variant, one must additionally exclude an earlier point that is not a height record. In the original Cartesian coordinates, point $(-2,y)$ would hit $(2,y)$ using translation $(4,0)$, but the query root image $(4,-2)$ is absent. The earlier point on the zero column requires translation $(2,0)$ and misses the leaf beside the root; the extra earlier point on the top row requires translation $(5,0)$ and also misses that leaf image. The early star therefore does not move earlier. The outer early point is still the first discovered point in its row, and the complete prefixes are those of the original family. Since $K_{2,k}$ has $2k$ edges and $k+2$ active vertices, these association graphs are neither forests nor pseudoforests as the parameter grows. Assigning each edge only to one of its two endpoints, with unit capacity, also fails. However, the same family satisfies $$ |G_{(0,6)}|=6H. $$ Thus it does not disprove constant linear capacity using all intersection vertices, nor the cubic conjecture for the original algorithm. Duplicate directed edges are impossible for a fixed label: the source and endpoint uniquely determine the early point, late point, and road target. In the height-record variant, an edge and its reverse cannot both occur either. Their two root paths would have to be the same host path in opposite directions, making the distinct early points have equal root depths. Global height records have strictly increasing depths. These restrictions still allow the undirected cycles above. ## 6. Area potentials and query overlap components Let $Q$ be the last complete query prefix with a surviving candidate, excluding a possible final point that empties the list. It is a tree that fits in a translated board. Define $$ J_h=Q\cap(Q-h). $$ For a grid-embedded forest $X$, choose an arbitrary potential constant in each component and define it along edges by $$ \Phi_X(y)-\Phi_X(x)=\det(x,y). $$ Acyclicity makes the potential well-defined. At intersection vertices, set $$ c_h^X(z)=\Phi_X(z+h)-\Phi_X(z)-\det(h,z). $$ Along an intersection edge, the difference between the increments of the first two terms equals the increment of the last term. Thus this value is constant on each connected component of $X\cap(X-h)$. A marker's associated host endpoint is $w=a+e$. Its late candidate's complete prefix contains the path between the early and late points. Summing determinants along the translated path gives $$ \boxed{c_h^F(w)=c_h^Q(e)-2\det(h,a).} $$ The candidate need not embed the whole query intersection component. The host may be disconnected, but a successful prefix connects the relevant points, so the component potential constant cancels. For a fixed host intersection component and query potential value, the sources lie in one horizontal row. Fixing the host endpoint and first-child group also fixes the query early point's row. The earliest star for that target, group, and row is unique, so these markers inject into their host endpoints. Different query intersection components with the same potential value can be combined in this injection. A further fact does not require earliest stars: for a fixed candidate and label, all its marker early points lie in one query intersection component. Take two early points and their respective late points. The early candidate survives both early points, and the late candidate survives both late points. The translated images of the two connecting query paths have the same host endpoints and must coincide. Hence the whole path between the early points and its label translate belong to the query tree. That path lies in the query intersection. ## 7. A new subclass: queries with connected horizontal intersections This section defines a separate all-success variant that groups only by query row: each target and row has one earliest successful star, without first-child splitting. Write its marker count as $\widetilde M_h$ and the number of distinct query intersection potential values as $\kappa_h$, with zero for an empty intersection. These are not the earlier four-group marker counts. The potential argument does not require first-child grouping. Fixing a query potential value and host endpoint fixes the query early point's row. The earliest star for that target and row is unique. Therefore $$ \boxed{\widetilde M_h\le\kappa_h|G_h|.} $$ There are now at most the board side length stars per target, so $$ \boxed{W\le(n+1)N+\sum_h\kappa_h|G_h|.} $$ If every nonempty query intersection $J_h$ is connected, then $\kappa_h=1$, yielding $$ \boxed{W\le2nN.} $$ More generally, if every nonempty query intersection has at most $b$ potential values, then $$ W\le[n+1+b(n-1)]N. $$ A uniform constant bound on the number of connected components is sufficient. These conditions concern the final effective query tree. They allow any root and discovery order, and the host forest may branch arbitrarily. For a concrete example, take a complete horizontal spine with arbitrarily long straight teeth extending upward or downward in its columns, subject to the induced-tree requirement. Each column is an integer interval containing the spine row. The column range of a horizontal intersection is the overlap of the two spines, and each intersection of vertical intervals still contains the spine row. Thus every nonempty intersection is connected. These straight comb queries satisfy the cubic bound on every road forest, regardless of the starting point or how visits to the spine and teeth are interleaved. Every connected subtree is again such a comb or a single straight tooth, so failure after a partial visit does not invalidate the result. Rotating coordinates and using vertical labels with column stars gives the corresponding vertical-spine subclass. Events count only first discoveries of nonroot points; revisits contribute to the move count. A final check that empties the candidate list is included in the allowance of at most one failure per candidate. The bound also holds directly when there are no successful nonroot events. ## 8. Resources on both sides and the remaining gap The query side has a total-resource bound as well: $$ \sum_{d\ne0}|J_{(0,d)}|\le(n-1)|Q|\le(n-1)N. $$ Each marker may be represented by a bipartite edge from its early query point to its associated host endpoint. A constant bound using all intersection vertices on both sides would also remove the general logarithmic gap. This total bound remains unproved. The bipartite graph need not be a forest: in the periodic family, one host endpoint already has two query early points. Duplicate the host into two nonadjacent road components while keeping the query unchanged. This gives a four-cycle. Complete prefixes are connected, so successful candidates for an old target must remain in its original component, preserving the earliest stars. This counterexample does not disprove the total bound using all intersection resources on both sides. Another sufficient, weaker form is $$ M_{(0,d)}\le C N\left(1+\log\frac n{|d|}\right), \qquad 1\le|d|\le n-1. $$ Indeed, $$ \sum_{d=1}^{n-1}\log\frac nd =n\log n-\log(n!)\le n-1, $$ so the total over positive and negative labels would still be at most $4C(n-1)N$. This scale-dependent form is also unproved. Complete-path assignments succeeded on the earlier fixed examples, but the infinite family in Section 9 disproves a general constant path capacity. Assignments using each marker's entire early prefix, or direct bounds on the whole label resource, remain possible directions. These reductions do not change the scanning algorithm or the problem constraints. The two resource targets are asymptotically equivalent: the final effective query has a complete valid translate, so $$ a_0+Q\subseteq F\quad\Longrightarrow\quad a_0+J_h\subseteq G_h,\qquad |J_h|+|G_h|\le2|G_h|. $$ Resources on both sides may help construct an assignment, but they do not weaken the whole-label counting target. ## 9. No uniform complete-path capacity for all-success markers This section uses Cartesian coordinates. Take integers $$ k\ge2,\qquad H=2k,\qquad d=2k+2,\qquad h=(d,0). $$ The query root is the origin. A vertical spine has long teeth at positive even heights: $$ Q=\{(0,y):0\le y\le H\} \cup\{(x,2i):1\le i\le k,\ 0\le x\le d+k\}. $$ First visit the teeth from bottom to top: move two steps up the spine, move right by $k$ steps, and return. At the top, visit the teeth from top to bottom, traversing each full tooth and returning to the spine before moving two steps down. The walk ends at the root. The roads are $$ \begin{aligned} F={}&\{(0,y):-H\le y\le H\} \cup\{(d,y):-H\le y\le0\}\\ &\cup\{(x,-2i):1\le i\le k,\ 0\le x\le k\}\\ &\cup\{(x,-2i):1\le i\le k,\ d\le x\le d+k\}\\ &\cup\{(x,2i):0\le i7(p_K+1),\qquad t(e)\ge p_K,\qquad |E(S_{a,e}\cap L)|\ge1. $$ Their components must still satisfy the high-exponent, fork, and nondegenerate-axis-intersection conditions of Section 23. Then $$ \boxed{W\le(9n-7)N+\sum_{(h,K)\in\mathcal C}R_{h,K}.} $$ A summand is zero when its component fails the early-endpoint count condition. The coefficient is unchanged, but the final sum remains uncontrolled. ## 25. Query-side periodic axes and a common-period length budget Root the query at the identity and write $w_x$ for the free-group root word of a query vertex; write $a$ for the host source vertex in the free group. For a fixed host label component, let its left multiplication be $g=u^q$, with shortest period $p$. Every actual marker satisfies $$ g(a w_e)=a w_f,\qquad a^{-1}ga=w_f w_e^{-1}. $$ Thus each early endpoint determines a query axis, $$ I_e=\operatorname{Axis}(w_f w_e^{-1})=a^{-1}L. $$ This does not depend on which source is chosen for that early endpoint. All sources in one query-axis class send that axis to the host axis. Their relative left multiplications preserve the host axis and are powers of its shortest translation. All such sources lie in one row, giving unit capacity for this class. The complete late prefix contains the path between the early and late endpoints, whose central axial segment has length $$ |E(P_{t(f)}\cap I_e)|\ge qp. $$ The late prefix cannot be replaced by the early prefix here. ### Total length of axes with a common period Let $T$ be a finite Cayley subtree. Take distinct axes whose bidirectional direction words all have the same positive integer period $p$, with $$ A_I=T\cap I,\qquad |E(A_I)|\ge4p. $$ Then $$ \boxed{\sum_I|E(A_I)|\le4|T|.} $$ First, if two such axes share $p$ consecutive edges, reading that full period in one common direction determines every letter in both directions. Direction-labeled continuation is unique, so the axes coincide. Choose any tree root. Split each axial segment at its shallowest vertex and take the longer ancestor-descendant piece, of length $b_I$. Then $$ b_I\ge\frac{|E(A_I)|}{2}\ge2p. $$ From its deeper endpoint, take the first $\lfloor b_I/2\rfloor$ edges and their endpoints, forming a closed half-segment $H_I$. If two half-segments share a vertex, both original pieces still have at least $p$ edges toward the root from that vertex. Their axes share a full period, a contradiction. Hence the half-segments are vertex-disjoint, and $$ |H_I|=\left\lfloor\frac{b_I}{2}\right\rfloor+1 \ge\frac{|E(A_I)|}{4}. $$ Summing proves the budget. The period length is fixed; this argument does not sum axes of different periods together. For a fixed host label component with $q\ge4$, every actual query axis leaves at least $qp$ edges in the final valid query. Therefore $$ \sum_I|E(Q\cap I)|\le4|Q|,\qquad \#\{I\}\le\frac{4|Q|}{qp}. $$ Multiple markers on one axis do not count as multiple axes. ### Reversed order across axes bounds candidate counts Take distinct query axes $I,J$ and fix a marker $(e_J,f_J)$ of the latter class. Let $\mathcal A$ be the distinct late sources that produced a marker of the former class with early endpoint discovered before $e_J$. Distinct query axes belong to different query intersection components, so the reversal rule gives $$ t(e)p$, that unit edge and its period translate have strictly alternating endpoints along the axis: $$ i0. $$ Suppose an off-axis component, starting from its actual attachment $\beta$, first meets the infinite physical axis at index $t$. Take this road arc and its label translate. Both lie in the same host tree, attach at $\beta,\beta+\ell$, and belong to distinct abstract projection fibers. They are disjoint. Neither meeting point can lie on the actual axial segment: otherwise two distinct abstract vertices of one road tree would have identical grid coordinates. Hence $$ t\notin[l,r],\qquad t+\ell\notin[l,r]. $$ Both attachments lie on that segment, so $r-l\ge\ell$. A meeting point on the right or on the left respectively gives $$ \beta<\beta+\ell7(p_K+1),\ K\text{ has a fork},\ |E(K\cap L)|\ge1\}. $$ In each such component, pay for all short-span resources and any four long axis classes; choosing the four largest classes is allowed. Define the unpaid count as $$ R^{(24)}_{h,K} =\#\{(a,e):\operatorname{diam}\pi_L(S_{a,e})\ge2p_K,\ I_e\text{ is outside the four selected classes}\}. $$ Only actual markers remaining after the common cut are counted. The capacity already paid in every component is still at most seven, giving $$ \boxed{ W\le(9n-7)N+\sum_{(h,K)\in\mathcal D}R^{(24)}_{h,K}. } $$ The new remainder is contained in that of Section 24: a span of two periods also ensures a sufficiently large discovery index and a nondegenerate axial intersection. Existing unit-capacity criteria, such as distinct early endpoints or collinear sources, remain available. **The final sum is still uncontrolled.** The number of long axis classes can grow with the instance. Counting axes has not removed reuse of host resources across classes. Checks on the old fixtures and one new curved fixture cover 3,430 actual markers; the new rules pay for all their previous remainders. ## 30. Another periodic axis separates copies with the same axis image Take two different abstract query axes with the same shortest horizontal period displacement, the first having shortest edge period $p$, whose infinite physical axes are induced paths by Section 26. Two complete-prefix maps satisfy $$ I\ne J,\qquad aI=bI,\qquad a\ne b, $$ and both map an actual query-axis path $A\subseteq J$ into the same road tree. Then $$ \boxed{aA\cap bA=\varnothing.} $$ Intersection here first means intersection at actual grid vertices. Two copies already lying in the same road tree share an actual vertex exactly when they share a direction-word tree vertex. The relative left multiplication preserves the common axis image and translates it by a nonzero integer multiple of the shortest period. Its physical displacement is therefore $$ \Delta_{\rm grid}=s\delta,\qquad \Delta_{\rm axis}=sp,\qquad s\in\mathbb Z\setminus\{0\}. $$ The other infinite physical axis has that same horizontal period, so its two infinite physical images coincide. If the actual finite copies share a vertex, their full bidirectional direction continuations agree there. Directional continuation from a Cayley-tree vertex is unique, so the abstract axis images coincide as well. The relative left multiplication would preserve two distinct axes, contradicting uniqueness of the translation axis of a nonidentity free-group left multiplication. If both query axes also have the same edge period $p$, the finite copies are shifted by the corresponding number of edges along one physical axis. Their disjointness implies $$ \boxed{|\Delta_{\rm axis}|>|E(A)|.} $$ Within one host label component, sources of one query-axis class have the same axis image, so this applies directly. The next section also allows different intersection components, requiring only that the chosen reference-axis image coincide. Both sources must genuinely match the entire segment being used. ## 31. On-axis early endpoints in one conjugacy class fit reference-axis blocks Fix a horizontal label and its actual common cut. Use the common late prefix and smaller early tree from Section 12: $$ R\subseteq P,\qquad P\cap(R+h)=\varnothing. $$ Every remaining early endpoint belongs to the smaller early tree, and every late candidate matches the entire common late prefix. Group query-side label left multiplications by free-group conjugacy class. Their cyclically reduced words differ only by cyclic rotation, so the shortest edge period, exponent, and horizontal period displacement agree within a class. Consider any subfamily of remaining markers in one such class whose early endpoints themselves lie on their query axes: $$ q\ge4,\qquad e\in I_e. $$ This differs from requiring the early resource to contain a long axial segment. The early endpoint may lie off the axis, so this does not cover the entire remainder. ### Choose a reference marker Take a marker with the latest early endpoint in this family, and write its axis as $$ (e_*,f_*),\qquad J_*=I_{e_*}. $$ The reference query-axis class lies in one query translation-intersection component. The potential injection from Section 6 charges its markers to distinct host intersection endpoints. Denote its count by $E_{\rm ref}$. Other axis classes belong to different query intersection components. Global reversal gives $$ t(e)1\text{ or }a+e\notin L_K\}. $$ The general scan count then has the rigorous reduction $$ \boxed{ W\le(12n-10)N+R_{\rm curved/off}^{(25)}. } $$ All other earlier conditions remain, including the actual common cut, high exponent, sufficiently many long early axes, and at least two periods in every unpaid resource. This remainder is still uncontrolled. However, all period-one markers with on-axis early endpoints now fit a shared target-scale budget. Similarly, restricting on-axis early endpoints to axes whose shortest edge periods have a fixed constant upper bound leaves only finitely many primitive direction-word conjugacy types. Their Section 31 costs also combine into a constant multiple of the target budget, with the constant depending on the period bound. Growing curved-period types and markers with off-axis early endpoints still need to be handled in general. ## 34. The entire intersection domain cannot be completed periodically Section 26 only proves that an entire intersection domain together with its infinite axis is an induced tree. It does not permit adding every label translate of that domain simultaneously. Coordinates below are row and column. Uppercase direction letters denote unit moves down, right, and left. Set $$ h=(0,10),\qquad B_{\rm L}=D^2W^2D^3E^2,\qquad B_{\rm R}=D^2E^2D^3W^2. $$ Both paths start at the origin and have the same endpoint, but take opposite routes. The road contains row zero from columns zero through forty. Attach the left path at columns zero and ten, and the right path at columns thirty and forty. The four branches are separated, so the road is an induced tree. Its intersection domain is exactly $$ K=\{(0,c):0\le c\le30\}\cup B_{\rm L} \cup\bigl(B_{\rm R}+(0,30)\bigr), $$ where a direction word in a union denotes all its vertices, including its starting point. Directly, $$ N=77,\quad |K|=49,\quad p=1,\quad q=10,\quad K\cup(K+h)=F. $$ However, translating the left branch three times aligns it with the original right branch at column thirty. They form a fourteen-edge cycle. Thus $$ \bigcup_{j=0}^{3}(K+jh) $$ is already not a forest. The domain does carry genuine markers. The query first walks two axis edges right and returns, visits the entire left branch and returns along it, then walks ten edges right and visits the second left branch. Recomputing stars over all candidates gives nine strict common-cut markers. All their early endpoints are off the axis, and all their early resources have axis span two. The actual parameters are $$ n=45,\quad |Q|=29,\quad m=41,\quad W=228. $$ The standard program and independent answer oracle both pass. The union of resources used by this query has only twelve vertices and does not use the right branch. This example therefore does not refute a stronger property of active resources, and is not an algorithmic complexity counterexample. ## 35. All label translates of one cut resource still form an induced forest Unlike the preceding domain, a genuine cut resource satisfies an additional disjointness condition. This section requires neither a large exponent nor an early endpoint on the axis. ### A connected grid set injects into the cylinder Suppose a finite connected grid set and a nonzero horizontal integer translation satisfy $$ S\cap(S+h)=\varnothing,\qquad h=(0,d),\qquad d>0. $$ Reflection handles negative labels. Taking the horizontal coordinate modulo the label length gives the cylinder projection $$ \pi_d(r,c)=(r,[c]_d). $$ This projection is injective on the grid set. Equivalently, $$ \boxed{(S+ih)\cap(S+jh)=\varnothing\quad(i\ne j).} $$ To prove this, suppose two vertices have the same projection. Take a simple path between them in the connected grid set, then a shortest subpath whose endpoints have the same projection. Its cylinder projection is a simple closed curve. Unit grid-edge interiors cannot acquire crossings under the projection: lifting such a crossing would produce intersecting grid edges without a common grid vertex. The lift of this closed curve has endpoints differing by a nonzero integer multiple of the label. Identifying the cylinder with the punctured plane, this integer is its winding number about the missing origin. A simple closed curve has winding number zero, one, or minus one. The original vertices therefore differ by one positive or negative label, contradicting the assumed disjointness. The winding-number fact is stated in [Theorem 1 of the NTNU notes](https://www.math.ntnu.no/emner/TMA4175/2011v/continuousLogs2.pdf). For label lengths one or two, the cylinder grid may contain loops or parallel edges. They must be retained as the actual embedded edges rather than collapsed to a simple quotient graph. This does not affect the simple-curve argument. ### Extra grid adjacency cannot skip a copy Under the same assumptions, any unit grid edge between distinct copies joins consecutive copy indices: $$ \boxed{ \{x,y+kh\}\text{ is a unit grid edge},\quad x,y\in S,\quad k\ne0 \ \Longrightarrow\ |k|=1. } $$ Take a simple path inside the grid set between the two representative vertices. The injectivity just proved makes its projection a simple path. Adding the edge between copies forms a simple closed curve whose winding number is their index difference, so its absolute value is one. If both representative vertices are equal, the path is empty and the added edge itself is a simple closed curve; the conclusion still holds. In particular, if the set and its first translate are not grid-adjacent, no two distinct integer translates are grid-adjacent. ### From two actual copies to every copy Assume additionally that the original grid set is an induced tree and its union with its first translate is an induced forest. The two disjoint nonempty connected trees have at most one unit edge between them. The previous arguments exclude every collision and adjacency between nonconsecutive copies, so $$ \boxed{\mathcal P_h(S)=\bigcup_{j\in\mathbb Z}(S+jh) \text{ is an induced grid forest}.} $$ If the first two copies have no connecting edge, the copies are separate components. If they have one, the copies join in integer order and the entire union is an induced tree. A genuine strict common-cut marker satisfies $$ S=a+P_{t(e)},\qquad S\cap(S+h)=\varnothing,\qquad S\cup(S+h)\subseteq F. $$ Thus the conclusion applies to each complete early resource. It also applies to an entire fibre of a fixed axis-projection vertex in a high-exponent intersection domain. The fibre and its first label translate have different axis attachments, at axis distance at least two. In the actual road tree they are therefore disjoint and nonadjacent. All distinct label translates of this fibre remain disjoint and nonadjacent. Injectivity also gives a size bound. Writing the number of covered rows as the height, $$ \boxed{|S|\le H(S)\,d.} $$ The actual common early tree is also disjoint from its first translate, so it satisfies this size bound too. However, its two translates need not be matched simultaneously by one candidate; the induced-forest conclusion cannot be applied to it on that basis. These statements concern all translates of one resource. Different resources may overlap. They do not establish unit Hall capacity for a resource family, nor justify summing resource sizes to pay for scans. ## 36. The reference axis class can also pay for its off-axis early endpoints The reference marker in Section 31 can be chosen from all selected high-exponent strict markers of one conjugacy class, rather than only those with early endpoints on their axes. Again choose a marker with the latest early discovery time and write its reference axis as $$ J_*=I_{e_*}. $$ Now pay for every marker in the reference axis class, together with the on-axis early endpoints in other axis classes. The potential-based endpoint injection for the reference class did not require early endpoints to be on the axis. The nonreference part still has on-axis early endpoints, so its reversed time order, per-source count, and reference late-axis block argument all remain valid. Consequently, $$ M^{\rm paid}_{h,\mathfrak c} =\#\{(a,e):I_e=J_*\text{ or }e\in I_e\}, $$ $$ \boxed{ M^{\rm paid}_{h,\mathfrak c}\le E_{\rm ref}+T_{h,\mathfrak c}, \qquad T_{h,\mathfrak c}\le5N. } $$ The set is counted only within the selected conjugacy-class family. The maximum block span is taken only over nonreference axes with on-axis early endpoints that are actually being paid. Allowing the reference early endpoint to be off its axis does not change the nonemptiness of those intersections. Reference endpoints from different conjugacy classes still inject jointly. For the period-one subfamily, the disjoint actual horizontal axis intersections from Section 33 still give $$ \boxed{ M^{\rm paid}_{h,\rm straight}\le |G_h|+N,\qquad \sum_h M^{\rm paid}_{h,\rm straight}\le3(n-1)N. } $$ The same budget therefore additionally removes every off-axis early endpoint in the reference axis class. Specifically, inside the Section 29 remainder, choose the reference query axis by this rule for each label's period-one subfamily. An empty subfamily needs no choice. After removing all on-axis early endpoints and the chosen reference class, define $$ R^{(26)} =\#\{(h,K,a,e)\text{ in the Section 29 remainder}: p_K>1\text{ or }(a+e\notin L_K,\ I_e\ne J_{h,*})\}. $$ The reference axis is used only in the period-one branch. Rigorously, $$ \boxed{ W\le(12n-10)N+R^{(26)},\qquad R^{(26)}\le R_{\rm curved/off}^{(25)}. } $$ Off-axis early endpoints in other axis classes can genuinely occur. A fixed six-axis instance with added short hooks has 317 markers, including 56 with off-axis early endpoints. The enlarged reference class pays for 46 of these; each of the other five classes leaves two. These markers also have an explicit unit resource assignment, so this instance is still not an algorithmic counterexample. ## 37. A common late prefix enlarges each source block to a full label length Fix a horizontal label, its actual common cut, and any strict marker subfamily in one high-exponent conjugacy class. Use the latest-early reference marker and its query axis from Section 36. Write the label's axis length as $$ \ell=qp,\qquad q\ge4,\qquad J_*=I_{e_*}. $$ The entire reference query-axis class still injects into distinct host intersection endpoints. Below, consider the other axis classes, allowing off-axis early endpoints. ### Every nonreference source shares a later complete prefix If the nonreference family is nonempty, choose its marker with the earliest late discovery: $$ (a_\dagger,e_\dagger,f_\dagger),\qquad t_\dagger=\min_{\rm nonref}t(f),\qquad I_\dagger=I_{e_\dagger}\ne J_*. $$ Every nonreference source has a marker whose late time is at least this minimum. It therefore matches this entire prefix. The reversed time order between reference and nonreference markers also gives $$ t(f_*)|E(A)|\ge\ell. $$ Their own markers need not belong to the same query-axis class. The required facts are that both sources actually match this second axis segment, and that the second axis differs from the reference axis. ### One block can pay for arbitrary early endpoints The reference late prefix also contains a full label length on its axis. Fix a segment $$ V\subseteq P_{t(f_*)}\cap J_*, \qquad |E(V)|=\ell,\qquad |V|=\ell+1. $$ Every nonreference source matches it completely. The preceding separation makes these blocks pairwise disjoint within each actual reference-axis image. For each source, any set of markers no larger than its block can be charged to that block. Write the source count and the sum of road vertices on distinct actual reference-axis images as $$ r_a=\#\{\text{selected nonreference markers with source }a\},\qquad T_{h,\mathfrak c}=\sum_{\Lambda\in\mathcal A}|C_\Lambda\cap\Lambda|. $$ Then $$ \boxed{ \sum_a\min\{r_a,\ell+1\}\le |\{\text{nonreference sources}\}|(\ell+1) \le T_{h,\mathfrak c}\le5N. } $$ The reference class is paid separately by intersection endpoints. Early endpoints may be anywhere off the axis, making this stronger than Section 36's payment of only nonreference on-axis early endpoints. The new rule retains every old payment. A source's on-axis early endpoints are distinct and lie in the common early tree's intersection with its query axis. Cut disjointness limits that intersection to at most one label length of vertices. Pay for those endpoints first, then use the remaining block positions for off-axis endpoints. The cost still uses actual reference late-axis vertices, without requiring them to lie in the original early resources. No Hall capacity inside those resources is asserted. ### Complete common-early-tree copies are disjoint within one image The same separation has an independent geometric consequence. The common early tree has reference-axis projection span $$ \operatorname{diam}\pi_{J_*}(R)\le\ell-1. $$ If the early tree misses this axis, its projection is one vertex. If it meets the axis, its projection is the actual intersection segment, whose span is limited by cut disjointness. The sources' relative axis displacement exceeds one label length, so their entire projection intervals are disjoint. Axis projection is unique in a road tree. Hence $$ \boxed{ aJ_*=bJ_*,\quad a\ne b \quad\Longrightarrow\quad (a+R)\cap(b+R)=\varnothing } $$ for these nonreference sources. Different actual reference-axis images may still reuse road branches. Summing their complete-copy unions across images cannot replace the axis-vertex budget above. ## 38. Only the excess per source remains for straight axes For period one, a fixed label has one conjugacy class, and the road intersections of distinct actual reference axes are disjoint. The preceding block cost is therefore at most the number of road vertices. Reference-class and source-block payments still combine across labels within the existing Section 33 budget. Apply this rule to the original Section 29 remainder. Let its total number of curved-period markers be $$ R_{\rm curved}^{(24)} =\#\{(h,K,a,e)\text{ in the Section 29 remainder}:p_K>1\}. $$ For each label's period-one subfamily, choose the latest-early reference query axis and pay its whole class. Denote each remaining source count by $$ r_{h,a}. $$ An empty family needs no reference choice. Reference-class sources do not enter the inner sum below. Then $$ R^{(27)} =R_{\rm curved}^{(24)} +\sum_h\sum_a\bigl(r_{h,a}-(|h|+1)\bigr)_+, $$ $$ \boxed{ W\le(12n-10)N+R^{(27)},\qquad R^{(27)}\le R^{(26)}. } $$ The comparison uses the same Section 29 remainder and reference rule, prioritizing the on-axis markers paid previously. The new remainder is still uncontrolled. However, its period-one part counts only the excess beyond each source block, rather than all nonreference off-axis endpoints. ### The excess cannot simply be omitted Change the six-axis example of Section 36 to hook depth twenty and query-axis row spacing twenty-three. This gives a prescribed input within the official limits: $$ n=274,\quad N=16808,\quad |Q|=504,\quad m=1030,\quad W=325690. $$ It has 1,381 strict markers, including 1,120 off-axis early endpoints. In the entire high-exponent strict family, the reference class contains 1,151 markers. Each of the other ten sources has twenty-three markers, while its block capacity is sixteen. This example also undergoes the actual Section 29 filtering. Its six long-early-axis classes contain 1,059 markers in the bottom class and forty-two in each upper class. Paying the four largest classes leaves two classes with eighty-four markers. Choosing the reference class anew in this remainder pays forty-two; each of the other two sources has twenty-one markers and a block paying sixteen. Ten markers still remain. These ten markers also have an explicit unit resource assignment: the first previously visited deep hook of the same candidate provides distinct vertices at the corresponding depths. The complete assignment for every marker, genuine stars, induced forest, standard program, and independent answers all pass. The example establishes that excess can occur; it does not refute the algorithmic complexity. ## 39. Summing complete resources across reference images can overcount without bound Section 37 separates complete early-tree copies within one reference image. It does not provide a linear road budget for their sum across images. This remains false after paying the four largest long-axis classes and the reference class, even if each remaining source contributes only the largest early resource it actually uses. ### A family of nested combs Choose $$ k\ge6,\quad t\ge1,\quad w\ge3,\quad D=6w,\quad R=D+3,\quad s=2w+5,\quad d=3s,\quad h=(0,d), $$ $$ B=2w^2+6w,\qquad b=5(t-1)+1. $$ Each comb descends to the specified depth and has a horizontal tooth of the specified width every third row. Its number of nonroot vertices is the comb size above. The query descends one level at a time and fully visits a right-pointing comb two columns to the right of each level. At the bottom it visits a left-pointing comb at one phase, then another one label farther right. It then processes the upper levels in reverse order, extending each arm to the label length plus two and visiting a right-pointing comb there. Each excursion returns to the main stem, and the walk ends at the origin. The upper sources are $$ a_{i,j}=(-iR,5sj),\quad 1\le i