On Sparse Representations of 3-Manifolds
Abstract
3-manifolds are commonly represented as triangulations, consisting of abstract tetrahedra whose triangular faces are identified in pairs. The combinatorial sparsity of a triangulation, as measured by the treewidth of its dual graph, plays a fundamental role in the design of parameterized algorithms. In this work, we investigate algorithmic procedures that transform or modify a given triangulation while controlling specific sparsity parameters. First, we revisit a standard, linear-time algorithm that converts a given triangulation into a Heegaard diagram of the underlying 3-manifold, showing that the construction preserves treewidth. We apply this construction to exhibit a fixed-parameter tractable framework for computing Kuperberg’s quantum invariants of 3-manifolds. Second, we present a quasi-linear-time algorithm that retriangulates a given triangulation into one with maximum edge valence of at most nine, while only moderately increasing the treewidth of the dual graph. Combining these two algorithms yields a quasi-linear-time algorithm that produces, from a given triangulation, a Heegaard diagram in which every attaching curve intersects at most nine others.
Keywords and phrases:
computational 3-manifold topology, fixed-parameter tractability, Heegaard splittings and diagrams, triangulations, edge valence, treewidth, quantum invariants, tensor networksFunding:
Clément Maria: Partially supported by the ANR project ANR-20-CE48-0007 (AlgoKnot).Copyright and License:
2012 ACM Subject Classification:
Mathematics of computing Geometric topology ; Theory of computation Fixed parameter tractabilityEditors:
Hee-Kap Ahn, Michael Hoffmann, and Amir NayyeriSeries and Publisher:
Leibniz International Proceedings in Informatics, Schloss Dagstuhl – Leibniz-Zentrum für Informatik
1 Introduction
Structural properties of triangulations – which are commonly used to encode 3-manifolds both in theory and in practice – can dramatically affect the feasibility of computations. Over the past decade, several fixed-parameter tractable (FPT) algorithms have been developed that efficiently solve provably hard problems on 3-manifolds, provided they are represented by triangulations that are sufficiently “thin” [5, 6, 7, 8, 9].111See [3, 27, 28, 29] for related FPT algorithms in knot theory, and the survey [25] for a broader context. On input triangulations with bounded treewidth222Treewidth is a graph parameter that quantifies the similarity of a given graph to any tree. We define the treewidth of a triangulation as the treewidth of its dual graph . See Section 2 for details. these algorithms run in time polynomial in the number of tetrahedra.
Motivated by these algorithms, several recent papers have investigated the quantitative relationship between the treewidth (and other width parameters) of triangulations and the corresponding quantities in various related representations of 3-manifolds. It has been shown that 3-manifolds with small Heegaard genus [14, 19], as well as hyperbolic 3-manifolds with small volume [17, 30], admit triangulations with small treewidth. At the same time, for certain 3-manifolds, a large Heegaard genus or a “complicated” JSJ decomposition can entirely preclude the existence of triangulations with small treewidth [20, 21].333See [11, 26] for related structural results about knots and links and their diagrams.
In this work, we also focus on algorithmic transformations of 3-manifold triangulations with a view toward parameterized algorithms and sparsity. We provide two main contributions. First, we revisit and analyze a classical construction that turns a triangulation of a closed 3-manifold into a Heegaard splitting444A Heegaard splitting is a decomposition of a 3-manifold into two identical handlebodies, cf. Section 2.2. and show that it yields a Heegaard diagram of , whose size and treewidth are linearly bounded by those of . More concretely, we prove
Theorem 1.
Let be a triangulation of a closed, orientable -manifold with tetrahedra and dual graph . Let be the Heegaard diagram of induced by . Then, for the number of vertices and for the treewidth555The number of vertices and the treewidth of a Heegaard diagram are, by definition, respectively equal to those of its underlying graph, which is the 4-regular multigraph geometrically obtained by taking the union of the - and -curves and placing a vertex at each crossing. of and we have
Moreover, given , the induced Heegaard diagram can be constructed in time.
Guided by this result, in Section 5 we investigate the complexity of computing Kuperberg’s quantum invariants of oriented 3-manifolds [23], which are obtained from a Heegaard diagram by evaluating an associated tensor network. First, we show that this construction is width-preserving (Lemma 18). This insight, combined with Theorem 1 and results on the complexity of evaluating tensor networks [31, 34] (cf. Theorem 19), provides a framework for computing Kuperberg’s invariants from triangulations that is FPT in the treewidth (Theorem 15).
Remark.
Our second contribution investigates the interplay between the maximum edge valence and the treewidth of a 3-manifold triangulation . Analogous to the notion of vertex degree in graphs, the valence of an edge in is defined as the number of tetrahedra in that contain it. While treewidth can be viewed as a measure of global sparsity, the maximum edge valence captures local sparsity. The maximum edge valence of a triangulation can also provide valuable insights into geometric properties of the underlying 3-manifold [13, Sec. 3.6]. Having a triangulation with small maximum edge valence can be computationally advantageous even when already has small treewidth; see the full version [18] for a discussion.
Every closed orientable 3-manifold has a triangulation with maximum edge valence at most six [2]. Frick has shown by an explicit construction that any triangulation can be modified into a triangulation of the same manifold with edge valences at most nine [13, Theorem 3.36]. However, this construction may significantly increase the treewidth of the resulting triangulation, because if contains edges with large valence, the retriangulation procedure introduces large grid-like structures in . In Section 4, we show how to circumvent this and obtain a different retriangulation that also achieves , while controlling the increase in treewidth by a polylogarithmic factor of the maximum edge valence of .
Theorem 2.
There is an algorithm which, given a triangulation of a closed -manifold with tetrahedra, vertices, , and maximum edge valence , constructs a triangulation of with vertices and tetrahedra, , and . The algorithm runs in time.
Finally, the execution of the algorithms in Theorem 2 and Theorem 1 (in this order) yields the following corollary, which we believe to be of independent interest.
Corollary 3.
There is a quasi-linear time algorithm that, given a triangulation of a closed, orientable -manifold with tetrahedra, , and maximum edge valence , constructs a Heegaard diagram of of size and genus , treewidth , where any -curve intersects at most -curves, and any -curve intersects at most -curves.
2 Preliminaries
2.1 Graphs and their treewidth
By a graph we generally mean a multigraph with a finite set of vertices and of a multiset of two-element submultisets of called edges. A loop is an edge of the form , and a multiedge is an edge with multiplicity larger than one. A graph without loops or multiedges is simple. The degree of is the number of edges containing , counted with multiplicity. A graph is -regular if for all .
Introduced in [36] (cf. [12]), the treewidth of a graph measures its similarity to any tree. A tree decomposition of a graph is a pair of a tree and a collection of bags, where and the following three properties hold: 1. (vertex coverage), 2. for every there exists with (edge coverage), and 3. for every , the set spans a connected subtree of (subtree property). The width of the tree decomposition equals , and the treewidth is defined as the smallest width of any tree decomposition of .
2.2 3-Manifolds and their representations
A -dimensional topological manifold with boundary (hereafter -manifold) is a topological space666Some technical requirements about the space are intentionally omitted here, cf. [39, Definition 1.1.1]. locally homeomorphic to , i.e., every point of has a neighborhood homeomorphic to or to the upper half-space . The boundary of consists of all points of that have no open neighborhood homeomorphic to . In this paper we only consider compact, orientable -manifolds with . A manifold is closed if it is compact and . A surface is just a -manifold. We consider manifolds up to homeomorphism. See [39] for general background on 3-manifolds.
Triangulations and their dual graphs.
As is common in algorithmic topology, we define a (-dimensional) triangulation as a quotient space , where is a set of labeled and vertex-labeled abstract tetrahedra, and is a set of simplicial isomorphisms, called gluing maps, each of which identifies two triangles of the simplices in .777Each triangle is identified with at most one other triangle. We allow two pairs of triangles to be glued between the same pair of tetrahedra, as well as gluing two triangles within a single tetrahedron. Hence the triangulations considered here are not simplicial complexes but regular simplicial cell complexes. Nevertheless, the second barycentric subdivision of any triangulation is always a simplicial complex. For , let denote the set of -dimensional faces of the resulting quotient , and let , its -skeleton, be . The valence of an edge is the number of tetrahedra in that contain it and . triangulates the manifold if the geometric realization of is homeomorphic to . Triangulations of surfaces are defined analogously. Every surface and 3-manifold has a triangulation [33, 35].
Given a triangulation , its dual graph (or face-pairing graph) is the graph with , and if and only if there is a gluing map that identifies a triangle of with a triangle of (where and may coincide). See Figure 1. We define the treewidth of a triangulation as the treewidth of its dual graph .
Handlebodies and Heegaard splittings.
A handlebody is a compact -manifold homeomorphic to a regular neighborhood of a bouquet of circles embedded in . Every closed, orientable -manifold admits a Heegaard splitting [15, 16], i.e., a decomposition into two homeomorphic handlebodies and with a shared boundary. That is, and . The surface is called a splitting surface, and its genus is referred to as the genus of the Heegaard splitting. The minimum genus of any Heegaard splitting of is called the Heegaard genus of . We refer to [38] for an extensive survey.
Heegaard diagrams.
Heegaard diagrams were developed alongside Heegaard splittings to describe them. They also provide the basis for computing Kuperberg’s invariants (Section 5). We follow the definitions of [23, Section 4]. In particular, we consider Heegaard diagrams in a sense more flexible than usual. A handlebody diagram is an ordered pair of a closed orientable surface and a collection of pairwise disjoint simple closed curves embedded in that divide into planar regions.888Because of this requirement the number of curves in is at least the genus of the surface , and is commonly assumed in the literature. However, we will generally have . (Figure 2).
A handlebody diagram can be seen as a prescription for gluing a handlebody to one side of . Specifically, consider the thickening , and for each attach to its upper boundary a thickened disk (called a -handle) along the curve .999More precisely, we attach the 2-handle along the copy of in . Because of the assumption about , each resulting new boundary component is a 2-sphere, each of which we fill in with a 3-ball. (Importantly, these fillings are unique up to isotopy; see [39, Lemma 2.5.3].) The union of the attached 2-handles and the filling 3-balls is a handlebody , which we have just glued to .
With that, a Heegaard diagram is a triple such that and are handlebody diagrams relative to different sides of . That is, the -handles corresponding to (resp. ) are attached to the upper boundary (resp. the lower boundary ) of the thickening . We refer to the curves in (resp. ) as -curves (resp. -curves) and assign the same color to each family in illustrations; see Figure 3. A Heegaard diagram can naturally be viewed as a 4-regular, surface-embedded graph, obtained geometrically by taking the union of the - and -curves and placing a vertex at each crossing.
3 From triangulations to Heegaard diagrams
In this section, we revisit a classical construction that converts a triangulation into a corresponding Heegaard diagram . We prove that this construction preserves both size and width up to a constant factor, as stated in Theorem 1. Moreover, using standard data structures, the conversion can be performed in time linear in the size of . We first review the construction via handles, then prove the inequalities (1a) and (1b) in Theorem 1, and finally discuss the algorithmic aspects of the construction.
Handle decompositions.
Any triangulation of a 3-manifold induces a canonical handle decomposition of , in which the -handles (all 3-balls) correspond to the -simplices of . Informally, is the “thickening” of (see Figure 4). For each tetrahedron , take a 0-handle centered at its barycenter. For each triangle , attach a 1-handle along a pair of disjoint disks connecting the 0-handles of the tetrahedra incident to . For each edge , attach a 2-handle along an annulus to the union of the 0- and 1-handles corresponding to the tetrahedra and triangles incident to . Finally, for each vertex , attach a 3-handle along a 2-sphere to fill the void surrounding .
-handle
-handle
- and -handles
The Heegaard diagram induced by .
The union of the 0- and 1-handles and the union of the 2- and 3-handles of are both handlebodies that together form a Heegaard splitting of the 3-manifold triangulated by . Letting and taking the meridional curves of the 2-handles and those of the 1-handles as - and -curves, respectively (Figure 4), we obtain the Heegaard diagram , where and . We call the Heegaard diagram induced by the triangulation .
Proof of inequalities (1a) and (1b) in Theorem 1.
For (1a), note that each triangle of contains exactly three vertices of the Heegaard diagram induced by (Figure 4), and each tetrahedron has four triangular faces identified in pairs, hence . To show (1b), take an optimal tree decomposition of , where is a tree, is the corresponding set of bags, and . We turn into a tree decomposition of as follows.
-
, i.e., the tree structure of the decomposition remains the same.
-
and for each , the bag is obtained from by replacing each with the (at most) 12 vertices of incident to , see Figure 4.
Clearly, . We now check that is a tree decomposition of .
- Vertex coverage.
-
Consider a vertex . By construction, there exists a tetrahedron , such that is incident to . Thus, for any , . However, since , this implies as well.
- Edge coverage.
-
Let be any arc of the diagram. Again, by construction of , there exists a tetrahedron that entirely contains . Let be a bag that contains . Then must contain both and .
- Subtree property.
-
Fix a vertex and consider . We need to show that spans a connected subtree of . Let be the tetrahedra containing on their common triangular face (note that and may coincide) and define and . From the definition of it follows that . Since is a tree decomposition of , each of and spans a connected subtree in . Moreover, : either , or , so there exists a bag containing both and . Thus, the connected subtrees spanned by and overlap, hence their union spans a connected subtree as well.
Algorithmic aspects of Theorem 1.
We briefly comment on the computational cost of extracting the Heegaard diagram from a given triangulation with tetrahedra. Recall that for an abstract simplicial complex , its barycentric subdivision is the simplicial complex whose ground set is , and a collection forms a -simplex in precisely when the simplices are nested, that is, when . Although a triangulation is generally not a simplicial complex, we can still form its barycentric subdivision by first subdividing each tetrahedron and then applying the gluing maps to identify the subdivided triangular faces. Performed twice, the resulting complex naturally contains both the canonical handle decomposition and the induced Heegaard diagram . As the barycentric subdivision of a tetrahedron contains 24 tetrahedra, .
Extracting chd() from .
Every vertex of is of the form for some simplex . Let be the natural inclusion defined by . For every , let be the smallest subcomplex of containing all -faces incident to . If corresponds to a simplex of dimension , then is regarded as a -handle. The collection forms the canonical handle decomposition . See Figure 5.
Extracting from .
To extract the induced Heegaard diagram from , we need to pinpoint its - and -curves, as well as the splitting surface in . We illustrate this via concrete examples; see Figure 6. We start with the -curves. Let be an edge of , and assume that is contained in four distinct tetrahedra of . Let denote the triangular face shared by and . Consider the subcomplex of spanned by the nine vertices , and . This complex triangulates the dual -cell transverse to (Figure 6, top left). Taking the second barycentric subdivision (Figure 6, top middle), we see that the -curve corresponding to is readily obtained as the polygonal curve spanned by the vertices of adjacent to (Figure 6, top right). The -curves can be located analogously (Figure 6, bottom row).
A triangulation of the splitting surface can also be readily obtained as the boundary of the subcomplex of formed by the union of the triangulated 2- and 3-handles of . Using standard data structures to represent these objects (such as in Regina [4]), all of these operations can be performed in linear time in terms of .
Remark 4.
Often it is assumed – and in certain applications even required, cf. [24] – that a Heegaard diagram be minimal, i.e. . In our setting, we can ensure this by first choosing arbitrary spanning trees and for the 1-skeleton and the dual graph of , respectively, and then retaining only those -curves (resp. -curves) that correspond to edges of (resp. ) not contained in (resp. ).
4 Retriangulating with constant edge valence and controlled treewidth
In this section, we describe and analyze a quasi-linear time procedure that retriangulates any 3-manifold triangulation into a triangulation with maximum edge valence at most and treewidth increased only by a polylogarithmic factor of the original maximum edge valence.
Theorem 5 (Theorem 2; with explicit polylog-factors).
There is an algorithm which, given a triangulation of a closed -manifold with tetrahedra, vertices, , and maximum edge valence , yields a triangulation of with vertices and tetrahedra, , and . The algorithm runs in time.
The construction in Theorem 5 is based on an iterative application of the following result.
Theorem 6.
There is an algorithm which, given a triangulation of a closed -manifold with tetrahedra, vertices, , and , constructs a triangulation of with at most tetrahedra, vertices, , and . The algorithm runs in time.
Setup.
Let us fix a triangulation of a closed 3-manifold with tetrahedra, vertices, treewidth , and maximum edge valence . Let be the spine of dual to . It is a -dimensional polyhedral cell complex whose -skeleton is the dual graph , and for each edge , contains a polygonal -face glued along the cycle in formed by the vertices corresponding to the tetrahedra that contain . Locally, at each tetrahedron of , the spine looks like the configuration shown in Figure 7.
Overall strategy.
Note that, given the spine , we can recover by first thickening and then filling in the resulting -sphere boundary components with -balls (which may be viewed as centered at the vertices of ). In what follows, we triangulate and fill in these missing balls combinatorially. Throughout, the term -face refers to the faces of the spine , whereas triangle refers to the faces of the triangulation. Our strategy is similar to that of [13, Theorem 3.36], but we employ a different – and necessarily more intricate – triangulation of the -faces of in order to control the treewidth of the resulting triangulation.
Triangulating the faces of .
Consider a -face of the spine transverse to an edge . This face is a -gon, where , whose vertices are the centers of the tetrahedra of containing . We triangulate as follows (see Figure 8). If , we add a vertex at the center of and connect it to all boundary vertices, as in Figure 8 (left). If , we proceed as follows. Fix an arbitrary orientation of the boundary of , and choose positive integers and such that . Label the boundary vertices in accordance with this orientation. Introduce a ring of interior vertices , and connect each to and (indices ). For each , connect to the boundary vertices . The final interior vertex is connected to . The inequalities ensure that the vertices and , together with these edges, form a triangulated annulus. Finally, we place a central vertex inside and connect it to all , see Figure 8 (right).
The next proposition follows directly from this construction; , , and are as above.
Proposition 7.
The triangulation of the -face described above consists of triangles. Each boundary vertex is incident to or edges, each interior vertex is incident to at most edges, and the central vertex is incident to edges. In particular, the maximum degree of a vertex in the -skeleton of is .
Building the triangulation in Theorem 6.
Let denote the triangulation of the spine obtained by triangulating each -face of as described above. We construct the triangulation by first taking , considered as embedded in the geometric realization of , and then adding the vertices . Each vertex lies in the interior of a connected component of , which is an open -ball denoted by . Its boundary is a subpolyhedron of comprised of certain -faces of . Let denote the subtriangulation of formed by the union of the triangulations of these -faces of . To complete the construction, for each we cone over from the vertex . We denote the resulting triangulation by . By construction, triangulates .
Remark.
In the above construction, for each -face we fix integers and that depend solely on the number of boundary vertices of in , or equivalently, on the valence of the edge of transverse to . When the context requires, we write and .
Definition 8 (type of a vertex of ).
The vertices of fall into the following three types. 1. vertices , 2. vertices lying on the boundary of exactly six -faces of , and 3. vertices and lying in the interior of exactly one -face of .
We proceed with investigating the maximum edge valence and the treewidth of .
Lemma 9.
The triangulation has edge valences at most .
Proof.
We consider, case by case, the different types of edges in . Let denote a vertex of , and let , , and denote vertices in a -face , see Figure 8. (We keep this labeling convention throughout this section.) The next valence-bounds follow from Proposition 7.
- Type .
-
The valence of the edge of this type is equal to the degree of in the triangulation of the 2-face, i.e., .
- Type .
-
The valence of the edge of this type is equal to the degree of in the triangulation of the 2-face, i.e., .
- Type .
-
is incident to at most tetrahedra per 2-face containing , and there are at most three 2-faces containing and bounding the ball containing , so .
- Type or .
-
are incident to at most tetrahedra, two on either side of ,
- Type .
-
is incident to one tetrahedra per 2-face that contains it, and is contained in at most three 2-faces, therefore .
Hence, for the maximum edge valence of we have .
Lemma 10.
The dual graph of the triangulation has treewidth .
Proof.
Consider a tree decomposition of the graph with optimal width .
By construction, every tetrahedron of contains a vertex of and at least one triangle from the triangulation of a -face of . Following the notation of Figure 8, these triangles are of the form , , or . For any 2-face of , the boundary vertices correspond to nodes of the graph , and consequently each of them appears in some bag of this tree decomposition .
We now construct a tree decomposition for the dual graph of , with the same underlying tree as for and . We initialize as for all , and consider all types of tetrahedra in :
-
1.
If has a triangular face , then add to all bags such that .
-
2.
If has a face , then add to all bags such that . Similarly, for , add to all bags such that .
-
3.
If has a face , then add to all bags such that contains any with .
Claim 11.
is a valid tree decomposition of the dual graph of .
Proof.
We verify the three defining properties of a tree decomposition (Section 2.1).
- Vertex coverage.
-
By construction, any tetrahedron of contains a triangle from a 2-face of the spine , and in consequence appears in some bag of .
- Edge coverage.
-
Showing that every edge of is contained in some bag of can be carried out by a tedious case analysis. In the triangulation , two tetrahedra may be adjacent along seven types of shared triangles, classified by the types of the triangle’s vertices; all possible configurations are shown in Figure 9. See the full version [18] for all the details.
- Subtree property.
-
By 1 and 2, tetrahedra of type , and appear exactly in the bags such that contain a certain fixed tetrahedron (respectively , , and ); the bags containing them are consequently connected in . By 3, a tetrahedron of type is inserted in all bags such that contains any with . Call the subtree of spanned by the nodes such that in . The subtree of spanned by the nodes in such that is, in consequence, . Because is a tree decomposition, each is connected. Additionally, for any , and are adjacent, and must consequently appear in a common bag of . Hence . In consequence, is a connected subtree of .
Claim 12.
has width less than .
Proof.
Let be a bag of of size . Every occurrence of a tetrahedron in will induce the insertion of at most tetrahedra in , per 2-face incident to , namely tetrahedra , tetrahedra if or , and tetrahedra with ; where indicates at most two possible vertices and of , on either side of the 2-face. Adding the fact that at most six 2-faces are incident to a given tetrahedron , the size of a bag is at most times the size of . In consequence, the width of is at most . This concludes the proofs of Claim 12 and Lemma 10.
From now on, for the -face transverse to the edge with valence , we set and , which satisfy the condition whenever . The next two lemmas provide bounds on the number of tetrahedra (Lemma 13) and the number of vertices (Lemma 14) in . These rely on standard counting arguments for triangulations; see the full version [18].
Lemma 13.
The triangulation has at most tetrahedra.
Proof.
Each 2-face, transversal to an edge of valence , contributes to tetrahedra ( triangles in the transversal 2-face , holding a tetrahedron on either side of ). In consequence,
Lemma 14.
The triangulation has at most vertices.
Proof.
By construction, the vertex set consist of the vertices , the vertices (lying on the boundaries of the -faces), and, for each , the interior vertices on the triangulated -face . The vertices are in bijection with the tetrahedra of , hence there are exactly of them. The total number of interior vertices over all -faces is
With and the vertices , this gives at most vertices in .
We are now ready to prove the main theorems of this section.
Proof of Theorem 6.
If the maximum edge valence of is at most , the algorithm simply returns . Otherwise, we apply the construction described above; the bounds on the number of tetrahedra, the number of vertices, the treewidth, and the edge valence follow from Lemmas 13, 14, 10, and 9, respectively. Note that the construction runs in time linear in the size of , which is .
Proof of Theorem 5.
If the maximum edge valence of satisfies , we are done. Otherwise, we construct a sequence of triangulations by iterating the construction of Theorem 6. The triangulation has tetrahedra and vertices [18, Lemma 23], treewidth (Lemma 10), and maximum edge valence (Lemma 9, with and ), where is the sequence of iterated radicals of [18, Lemma 21], with , , and . By [18, Lemma 22], choosing ensures that the edge valence of is at most . We therefore set . Since and , the triangulation has tetrahedra and vertices, treewidth at most , and edge valence at most . The algorithm performs iterations of the algorithm of Theorem 6, yielding the stated complexity bound.
5 Efficient evaluation of Kuperberg’s tensor networks
In this section we present a fixed-parameter tractable (FPT) scheme for computing Kuperberg’s quantum invariants of closed, oriented101010In this section we assume to be an oriented, not merely orientable, 3-manifold. 3-manifolds [23]. This quantity depends on an oriented Heegaard diagram111111An oriented Heegaard diagram is a Heegaard diagram together with an orientation for the surface and for each of the - and -curves. The quantity does not depend on the choice of orientation for the - and -curves, however, it generally does depend on the chosen orientation for . and a finite-dimensional involutory Hopf algebra over a field , which is considered fixed. By construction, .
Remark.
We emphasize that understanding the results in this section does not require knowledge of Hopf algebras or tensors, since the following proofs are purely graph theoretical. Nevertheless, we provide some basic definitions and examples in the full version [18]. We refer to Kuperberg’s paper [23] (cf. its open-access version [22]) for further details.
Even if is originally derived from an oriented Heegaard diagram, it can also be computed from an oriented triangulation. This is briefly hinted at in [23, Section 4], however, with the machinery developed in Section 3 we can make it fully explicit: Any triangulation of a 3-manifold gives rise to a Heegaard diagram of , moreover, in a width-preserving way (Theorem 1). Picking an orientation for induces an orientation also for . Then choosing orientations for the - and -curves arbitrarily yields an oriented diagram . Next, from we build a tensor network following Kuperberg’s construction [23, Section 5], which we finally evaluate to obtain . From now on, we will use the notation to indicate when we regard the invariant as computed from a triangulation, where denotes the oriented Heegaard diagram induced by .
Building on Theorem 1 and bounding the treewidth of the tensor network (Lemma 18), together with work of O’Gorman [34] (cf. Markov–Shi [31]) we prove the following result:
Theorem 15.
Let be a fixed finite-dimensional involutory Hopf algebra over a field . Let be an oriented triangulation of a closed oriented -manifold with tetrahedra and treewidth . The invariant can be computed in time .
Before discussing the proof of Theorem 15 in detail, we provide an overview on Figure 10.
Remark 16.
Theorem 15 asserts that computing is FPT in the treewidth of . In particular, for bounded-treewidth triangulations it can be computed in linear time. However, since tensor network contraction – the last part of the computation – is generally -hard [10], we expect this to hold for computing for general triangulations as well.
As motivation, let us recall the formula for the invariant from [23, Section 5]:
| (2) |
Here is the genus of the surface , and and denote the number of - and -curves of , respectively. The “complicated” term is defined as the evaluation of a specific tensor network associated to , built from (several copies of) the structure tensors of the Hopf algebra . We now very briefly and selectively review these notions.
Hopf algebras and their structure tensors.
A Hopf algebra is a vector space over a field together with three -linear maps (multiplication), (comultiplication) and (antipode) satisfying certain axioms (cf. [23, Section 3]). We will assume that and is involutory, i.e., . The maps , and can be regarded as tensors of type , and , respectively, see Figure 11.
Example 17.
The group algebra of a finite group is naturally a Hopf algebra: the multiplication is defined as , the comultiplication as , and the antipode as . In [23, Sections 1 and 6] it is shown that equals the number of homomorphisms from the fundamental group of the 3-manifold described by to the group . (In this case is independent of the chosen orientation for .)
5.1 Kuperberg’s construction and the proof of Theorem 15
Following [23, Section 5], first we explain how the tensor network – whose evaluation appears in (2) – is constructed from an oriented Heegaard diagram . Then we prove Lemma 18, which – together with Theorem 19 – implies Theorem 15.
The construction of .
As already mentioned, the building blocks of are the structure tensors , and of the Hopf algebra (Figure 11). The shorthands in Figure 12 – which are justified by the fact that both abbreviated tensor networks, called the tracial product and tracial coproduct in [23], are cyclically symmetric121212This is analogous to the fact that for the trace of matrices. – will be useful:
Let be an oriented Heegaard diagram. For every oriented -curve , we take a copy of the tracial product tensor , where the abstract indices correspond to the crossings on (with the -curves of ) in the order they are encountered when traversing following its orientation. We assign a copy of the tracial coproduct tensor to each oriented -curve analogously. Note that each crossing between an - and a -curve of appears exactly twice as an abstract index of the above tensors: once at a product and once at a coproduct. The construction of is concluded by contracting these indices (i.e., joining the respective arrows with wires) with a caveat: if the tangent vectors of the - and -curves intersecting at form (in that order) a negatively oriented basis of the tangent space , then the antipode tensor is interposed before contracting (Figure 13).
A fully contracted tensor network (such as ) can be seen as a graph in the obvious way: corresponds to the coupons of , whereas to its wires. (We emphasize that is considered here without any diagrammatic abbreviations.)
Lemma 18.
Let be an oriented Heegaard diagram and be the Kuperberg tensor network induced by . Then, the number of vertices and the treewidth of and satisfy
Proof.
Both inequalities (3a) and (3b) follow directly from the construction of . In fact, the local configurations shown in Figure 14 already reveal the close structural relationship between and . We refer to the full version [18] for the complete proof.
Proof of Theorem 15.
With Theorem 1 and Lemma 18 at hand, Theorem 15 is a consequence of the following general result about the computational cost of evaluating tensor networks.
Theorem 19 ([34, Theorem 1], cf. [31, Theorem 4.6]).
Any tensor network with tensors can be evaluated in time, where denotes the vertex congestion of .
Vertex congestion is a graph parameter similar to treewidth, discussed in [1, p. 135]. For a graph with maximum degree , we have , see [1, Theorem 1 and Remark 3]. Since Kuperberg’s tensor networks are 3-regular graphs, we have
Corollary 20.
Any Kuperberg tensor network can be evaluated in time , where denotes the treewidth and the number of tensors of .
Now, if is induced by an oriented triangulation with tetrahedra, then and by Lemma 18, and and by Theorem 1. Combining these inequalities with Corollary 20, the Theorem 15 follows.
References
- [1] D. Bienstock. On embedding graphs in trees. J. Comb. Theory, Ser. B, 49(1):103–136, 1990. doi:10.1016/0095-8956(90)90066-9.
- [2] N. Brady, J. McCammond, and J. Meier. Bounding edge degrees in triangulated 3-manifolds. Proc. Amer. Math. Soc., 132(1):291–298, 2004. doi:10.1090/S0002-9939-03-06981-8.
- [3] B. A. Burton. The HOMFLY-PT polynomial is fixed-parameter tractable. In 34th Int. Symp. Comput. Geom. (SoCG 2018), volume 99 of LIPIcs. Leibniz Int. Proc. Inform., pages 18:1–18:14. Schloss Dagstuhl–Leibniz-Zent. Inf., 2018. doi:10.4230/LIPIcs.SoCG.2018.18.
- [4] B. A. Burton, R. Budney, W. Pettersson, et al. Regina: Software for low-dimensional topology, 1999–2025. Version 7.4.1. URL: https://regina-normal.github.io.
- [5] B. A. Burton and R. G. Downey. Courcelle’s theorem for triangulations. J. Comb. Theory, Ser. A, 146:264–294, 2017. doi:10.1016/j.jcta.2016.10.001.
- [6] B. A. Burton, T. Lewiner, J. Paixão, and J. Spreer. Parameterized complexity of discrete Morse theory. ACM Trans. Math. Softw., 42(1):6:1–6:24, 2016. doi:10.1145/2738034.
- [7] B. A. Burton, C. Maria, and J. Spreer. Algorithms and complexity for Turaev–Viro invariants. J. Appl. Comput. Topol., 2(1–2):33–53, 2018. doi:10.1007/s41468-018-0016-2.
- [8] B. A. Burton and W. Pettersson. Fixed parameter tractable algorithms in combinatorial topology. In Proc. 20th Int. Conf. Comput. Comb. (COCOON 2014), volume 8591 of Lect. Notes Comput. Sci., pages 300–311. Springer, 2014. doi:10.1007/978-3-319-08783-2_26.
- [9] B. A. Burton and J. Spreer. The complexity of detecting taut angle structures on triangulations. In Proc. 24th Annu. ACM-SIAM Symp. Discrete Algorithms (SODA 2013), pages 168–183, 2013. doi:10.1137/1.9781611973105.13.
- [10] C. Damm, M. Holzer, and P. McKenzie. The complexity of tensor calculus. Comput. Complexity, 11(1-2):54–89, 2002. doi:10.1007/s00037-000-0170-4.
- [11] A. de Mesmay, J. Purcell, S. Schleimer, and E. Sedgwick. On the tree-width of knot diagrams. J. Comput. Geom., 10(1):164–180, 2019. doi:10.20382/jocg.v10i1a6.
- [12] D. Eppstein. What is … treewidth? Notices Amer. Math. Soc., 72(2):172–175, 2025. URL: https://www.ams.org/journals/notices/202502/rnoti-p172.pdf.
- [13] F. Frick. Combinatorial restrictions on cell complexes. PhD thesis, TU Berlin, 2015. doi:10.14279/depositonce-4545.
- [14] A. He, J. Morgan, and E. K. Thompson. An algorithm to construct one-vertex triangulations of Heegaard splittings. J. Comput. Geom., 16(1):635–693, November 2025. doi:10.20382/jocg.v16i1a18.
- [15] P. Heegaard. Forstudier til en topologisk Teori for de algebraiske Fladers Sammenhæng (in Danish). PhD thesis, Det Nordiske Forlag, 1898. URL: https://books.google.com/books?id=p9hMAAAAYAAJ. An English translation is available at https://webhomes.maths.ed.ac.uk/˜v1ranick/papers/heegaardenglish.pdf.
- [16] P. Heegaard. Sur l’“Analysis situs”. Bull. Soc. Math. France, 44:161–242, 1916. doi:10.24033/bsmf.968.
- [17] K. Huszár. On the pathwidth of hyperbolic 3-manifolds. Comput. Geom. Topol., 1(1):1–19, 2022. doi:10.57717/cgt.v1i1.4.
- [18] K. Huszár and C. Maria. On sparse representations of 3-manifolds, 2025. arXiv:2512.05779.
- [19] K. Huszár and J. Spreer. 3-Manifold triangulations with small treewidth. In 35th Int. Symp. Comput. Geom. (SoCG 2019), volume 129 of LIPIcs. Leibniz Int. Proc. Inf., pages 44:1–44:20. Schloss Dagstuhl–Leibniz-Zent. Inf., 2019. doi:10.4230/LIPIcs.SoCG.2019.44.
- [20] K. Huszár and J. Spreer. On the width of complicated JSJ decompositions. Discrete Comput. Geom., 74(4):917–943, 2025. doi:10.1007/s00454-025-00746-1.
- [21] K. Huszár, J. Spreer, and U. Wagner. On the treewidth of triangulated 3-manifolds. J. Comput. Geom., 10(2):70–98, 2019. doi:10.20382/jogc.v10i2a5.
- [22] G. Kuperberg. Involutory Hopf algebras and 3-manifold invariants, 1990. arXiv:math/9201301.
- [23] G. Kuperberg. Involutory Hopf algebras and -manifold invariants. Internat. J. Math., 2(1):41–66, 1991. doi:10.1142/S0129167X91000053.
- [24] G. Kuperberg. Noninvolutory Hopf algebras and -manifold invariants. Duke Math. J., 84(1):83–129, 1996. doi:10.1215/S0012-7094-96-08403-3.
- [25] M. Lackenby. Algorithms in 3-manifold theory. In I. Agol and D. Gabai, editors, Surveys in -manifold topology and geometry, volume 25 of Surv. Differ. Geom., pages 163–213. Int. Press Boston, 2022. doi:10.4310/SDG.2020.v25.n1.a5.
- [26] C. Lunel and A. de Mesmay. A Structural Approach to Tree Decompositions of Knots and Spatial Graphs. In 39th Int. Symp. Comput. Geom. (SoCG 2023), volume 258 of LIPIcs. Leibniz Int. Proc. Inf., pages 50:1–50:16. Schloss Dagstuhl–Leibniz-Zent. Inf., 2023. doi:10.4230/LIPIcs.SoCG.2023.50.
- [27] J. A. Makowsky. Coloured Tutte polynomials and Kauffman brackets for graphs of bounded tree width. Discrete Appl. Math., 145(2):276–290, 2005. doi:10.1016/j.dam.2004.01.016.
- [28] J. A. Makowsky and J. P. Mariño. The parametrized complexity of knot polynomials. J. Comput. Syst. Sci., 67(4):742–756, 2003. Special issue on parameterized computation and complexity. doi:10.1016/S0022-0000(03)00080-1.
- [29] C. Maria. Parameterized complexity of quantum knot invariants. In 37th Int. Symp. Comput. Geom. (SoCG 2021), volume 189 of LIPIcs. Leibniz Int. Proc. Inf., pages 53:1–53:15. Schloss Dagstuhl – Leibniz-Zent. Inf., 2021. doi:10.4230/LIPIcs.SoCG.2021.53.
- [30] C. Maria and J. Purcell. Treewidth, crushing and hyperbolic volume. Algebr. Geom. Topol., 19(5):2625–2652, 2019. doi:10.2140/agt.2019.19.2625.
- [31] I. L. Markov and Y. Shi. Simulating quantum computation by contracting tensor networks. SIAM J. Comput., 38(3):963–981, 2008. doi:10.1137/050644756.
- [32] S. Matveev. Algorithmic Topology and Classification of -Manifolds, volume 9 of Algorithms Comput. Math. Springer, Berlin, 2nd edition, 2007. doi:10.1007/978-3-540-45899-9.
- [33] E. E. Moise. Affine structures in -manifolds. V. The triangulation theorem and Hauptvermutung. Ann. Math. (2), 56:96–114, 1952. doi:10.2307/1969769.
- [34] B. O’Gorman. Parameterization of tensor network contraction. In 14th Conf. Theory Quantum Comput. Commun. Cryptogr., volume 135 of LIPIcs. Leibniz Int. Proc. Inform., pages 10:1–10:19. Schloss Dagstuhl. Leibniz-Zent. Inform., 2019. doi:10.4230/LIPIcs.TQC.2019.10.
- [35] T. Radó. Über den Begriff der Riemannschen Fläche. Acta Sci. Math., 2(2):101–121, 1925.
- [36] N. Robertson and P. D. Seymour. Graph minors. II. Algorithmic aspects of tree-width. J. Algorithms, 7(3):309–322, 1986. doi:10.1016/0196-6774(86)90023-4.
- [37] J. H. Rubinstein, H. Segerman, and S. Tillmann. Traversing three-manifold triangulations and spines. Enseign. Math., 65(1-2):155–206, 2019. doi:10.4171/lem/65-1/2-5.
- [38] M. Scharlemann. Heegaard splittings of compact 3-manifolds. In Handbook of Geometric Topology, pages 921–953. North-Holland, 2001. doi:10.1016/B978-044482432-5/50019-6.
- [39] J. Schultens. Introduction to -Manifolds, volume 151 of Grad. Stud. Math. Am. Math. Soc., Providence, RI, 2014. doi:10.1090/gsm/151.
