Abstract 1 Introduction 2 Preliminaries 3 From triangulations to Heegaard diagrams 4 Retriangulating with constant edge valence and controlled treewidth 5 Efficient evaluation of Kuperberg’s tensor networks References

On Sparse Representations of 3-Manifolds

Kristóf Huszár ORCID Institute of Geometry, Graz University of Technology, Austria    Clément Maria ORCID Inria d’Université Côte d’Azur, Sophia Antipolis, France
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 networks
Funding:
Clément Maria: Partially supported by the ANR project ANR-20-CE48-0007 (AlgoKnot).
Copyright and License:
[Uncaptioned image] © Kristóf Huszár and Clément Maria; licensed under Creative Commons License CC-BY 4.0
2012 ACM Subject Classification:
Mathematics of computing Geometric topology
; Theory of computation Fixed parameter tractability
Related Version:
Full Version: https://arxiv.org/abs/2512.05779 [18]
Editors:
Hee-Kap Ahn, Michael Hoffmann, and Amir Nayyeri

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 𝒯 as the treewidth of its dual graph Γ(𝒯). 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 𝒯 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 𝒯. More concretely, we prove

Theorem 1.

Let 𝒯 be a triangulation of a closed, orientable 3-manifold with n tetrahedra and dual graph Γ(𝒯). Let 𝒟:=𝒟(𝒯) be the Heegaard diagram of induced by 𝒯. Then, for the number of vertices and for the treewidth555The number V(𝒟) of vertices and the treewidth tw(𝒟) of a Heegaard diagram 𝒟=(𝒮,𝛂,𝛃) 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 α- and β-curves and placing a vertex at each crossing. of 𝒟 and Γ(𝒯) we have


Moreover, given 𝒯, the induced Heegaard diagram 𝒟 can be constructed in O(n) 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.

The converse of Theorem 1, i.e., building a triangulation from a given Heegaard splitting in a width-preserving way, has been studied in [19] and, very recently, in [14], where an explicit algorithm for constructing a triangulation from a Heegaard diagram is provided.

Our second contribution investigates the interplay between the maximum edge valence and the treewidth of a 3-manifold triangulation 𝒯. Analogous to the notion of vertex degree in graphs, the valence of an edge in 𝒯 is defined as the number of tetrahedra in 𝒯 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 𝒯 with small maximum edge valence can be computationally advantageous even when 𝒯 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 𝒯 can be modified into a triangulation 𝒯 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 𝒯 contains edges with large valence, the retriangulation procedure introduces large grid-like structures in 𝒯. In Section 4, we show how to circumvent this and obtain a different retriangulation 𝒯 that also achieves Δ(𝒯)9, while controlling the increase in treewidth by a polylogarithmic factor of the maximum edge valence of 𝒯.

Theorem 2.

There is an algorithm which, given a triangulation 𝒯 of a closed 3-manifold with n tetrahedra, 𝐯 vertices, tw(Γ(𝒯))=𝐭𝐰, and maximum edge valence Δ(𝒯)=𝚫, constructs a triangulation 𝒯 of with O((n+𝐯)poly(log2(𝚫))) vertices and tetrahedra, tw(Γ(𝒯))𝐭𝐰poly(log2(𝚫)), and Δ(𝒯)9. The algorithm runs in O(nloglogn) 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 𝒯 of a closed, orientable 3-manifold with n tetrahedra, tw(Γ(𝒯))=𝐭𝐰, and maximum edge valence Δ(𝒯)=𝚫, constructs a Heegaard diagram 𝒟=(𝒮,𝛂,𝛃) of of size and genus O(npoly(log(𝚫))), treewidth O(𝐭𝐰poly(log(𝚫)), where any α-curve intersects at most 9 β-curves, and any β-curve intersects at most 3 α-curves.

2 Preliminaries

2.1 Graphs and their treewidth

By a graph we generally mean a multigraph G=(V,E) with a finite set V=V(G) of vertices and of a multiset E=E(G) of two-element submultisets of V called edges. A loop is an edge of the form {v,v}, and a multiedge is an edge with multiplicity larger than one. A graph without loops or multiedges is simple. The degree deg(v) of vV is the number of edges containing v, counted with multiplicity. A graph is k-regular if deg(v)=k for all vV.

Introduced in [36] (cf. [12]), the treewidth of a graph measures its similarity to any tree. A tree decomposition 𝒳 of a graph G=(V,E) is a pair 𝒳=(T,) of a tree T=(I,F) and a collection ={Bi:iI} of bags, where BiV and the following three properties hold: 1. iIBi=V(vertex coverage), 2. for every {u,v}E there exists iI with {u,v}Bi (edge coverage), and 3. for every vV, the set Tv={iI:vBi} spans a connected subtree of T (subtree property). The width of the tree decomposition 𝒳 equals maxiI|Bi|1, and the treewidth tw(G) is defined as the smallest width of any tree decomposition of G.

2.2 3-Manifolds and their representations

A d-dimensional topological manifold with boundary (hereafter d-manifold) is a topological space666Some technical requirements about the space are intentionally omitted here, cf. [39, Definition 1.1.1]. locally homeomorphic to d, i.e., every point of has a neighborhood homeomorphic to d or to the upper half-space {(x1,,xd)d:xd0}. The boundary of consists of all points of that have no open neighborhood homeomorphic to d. In this paper we only consider compact, orientable d-manifolds with d3. A manifold is closed if it is compact and =. A surface is just a 2-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 (3-dimensional) triangulation as a quotient space 𝒯=Σ/Φ, where Σ={σ1,,σn} is a set of labeled and vertex-labeled abstract tetrahedra, and Φ={φ1,,φm} is a set of simplicial isomorphisms, called gluing maps, each of which identifies two triangles of the simplices in Σ.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 𝒯′′ of any triangulation 𝒯 is always a simplicial complex. For i{0,1,2,3}, let 𝒯(i) denote the set of i-dimensional faces of the resulting quotient 𝒯, and let 𝒯(i), its i-skeleton, be 𝒯(i):=j=0i𝒯(j). The valence val(e) of an edge e𝒯(1) is the number of tetrahedra in 𝒯 that contain it and Δ(𝒯):=maxe𝒯(1)val(e). 𝒯 triangulates the manifold if the geometric realization of 𝒯 is homeomorphic to . Triangulations of surfaces are defined analogously. Every surface and 3-manifold has a triangulation [33, 35].

Given a triangulation 𝒯=Σ/Φ, its dual graph (or face-pairing graph) Γ(𝒯) is the graph with V(Γ(𝒯))=Σ, and {σ1,σ2}E(Γ(𝒯)) if and only if there is a gluing map φΦ that identifies a triangle of σ1 with a triangle of σ2 (where σ1 and σ2 may coincide). See Figure 1. We define the treewidth of a triangulation 𝒯 as the treewidth of its dual graph Γ(𝒯).

Figure 1: A triangulation 𝒯=Σ/Φ with tetrahedra Σ={σ1,σ2}, gluing maps Φ={φ1,φ2,φ3} and dual graph Γ(𝒯). φ1 is explicitly defined as σ1(123)σ2(103). Based on [20, Figure 1].

Handlebodies and Heegaard splittings.

A handlebody is a compact 3-manifold homeomorphic to a regular neighborhood of a bouquet of circles embedded in 3. Every closed, orientable 3-manifold admits a Heegaard splitting [15, 16], i.e., a decomposition into two homeomorphic handlebodies 1 and 2 with a shared boundary. That is, =12 and 12=1=2=𝒮. The surface 𝒮 is called a splitting surface, and its genus g(𝒮) 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 (𝒮,𝜸) of a closed orientable surface 𝒮 and a collection 𝜸={γ1,,γ} of pairwise disjoint simple closed curves embedded in 𝒮 that divide 𝒮 into planar regions.888Because of this requirement the number of curves in 𝜸 is at least the genus g(𝒮) of the surface 𝒮, and =g(𝒮) is commonly assumed in the literature. However, we will generally have >g(𝒮). (Figure 2).

Figure 2: Illustrations of some handlebody diagrams. The surfaces are meant to be hollow.

A handlebody diagram (𝒮,𝜸) can be seen as a prescription for gluing a handlebody to one side of 𝒮. Specifically, consider the thickening 𝒮×[0,1], and for each i{1,,} attach to its upper boundary 𝒮×{1} a thickened disk (called a 2-handle) along the curve γi.999More precisely, we attach the 2-handle along the copy of γi in 𝒮×{1}. Because of the assumption about 𝜸, 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 𝒮.

With that, a Heegaard diagram is a triple 𝒟=(𝒮,𝜶,𝜷) such that (𝒮,𝜶) and (𝒮,𝜷) are handlebody diagrams relative to different sides of 𝒮. That is, the 2-handles corresponding to 𝜶 (resp. 𝜷) are attached to the upper boundary 𝒮×{1} (resp. the lower boundary 𝒮×{0}) of the thickening 𝒮×[0,1]. We refer to the curves in 𝜶 (resp. 𝜷) as α-curves (resp. β-curves) and assign the same color to each family in illustrations; see Figure 3. A Heegaard diagram 𝒟 can naturally be viewed as a 4-regular, surface-embedded graph, obtained geometrically by taking the union of the α- and β-curves and placing a vertex at each crossing.

Figure 3: Two Heegaard diagrams of the 3-sphere, and one of the real projective 3-space 3.

3 From triangulations to Heegaard diagrams

In this section, we revisit a classical construction that converts a triangulation 𝒯 into a corresponding Heegaard diagram 𝒟=(𝒮,𝜶,𝜷). 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 𝒯𝒟 can be performed in time linear in the size of 𝒯. 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 𝒯 of a 3-manifold induces a canonical handle decomposition chd(𝒯) of , in which the k-handles (all 3-balls) correspond to the (3k)-simplices of 𝒯. Informally, chd(𝒯) is the “thickening” of 𝒯 (see Figure 4). For each tetrahedron σ𝒯(3), take a 0-handle centered at its barycenter. For each triangle t𝒯(2), attach a 1-handle along a pair of disjoint disks connecting the 0-handles of the tetrahedra incident to t. For each edge e𝒯(1), attach a 2-handle along an annulus to the union of the 0- and 1-handles corresponding to the tetrahedra and triangles incident to e. Finally, for each vertex v𝒯(0), attach a 3-handle along a 2-sphere to fill the void surrounding v.

0-handle𝒟(𝒯)|σ

1-handle𝒟(𝒯)|σ

2- and 3-handles𝒟(𝒯)|σ

(a) The building blocks of the canonical handle decomposition chd(𝒯). Meridian curves of the 1- and the 2-handle are also drawn.

𝒟(𝒯)|σ

(b) The α- and β-curves of 𝒟(𝒯) restricted to a tetrahedron σ of 𝒯.
Figure 4: The canonical handle decomposition and the induced Heegaard diagram.

The Heegaard diagram induced by 𝓣.

The union 1 of the 0- and 1-handles and the union 2 of the 2- and 3-handles of chd(𝒯) are both handlebodies that together form a Heegaard splitting of the 3-manifold triangulated by 𝒯. Letting 𝒮:=12 and taking the meridional curves of the 2-handles and those of the 1-handles as α- and β-curves, respectively (Figure 4), we obtain the Heegaard diagram 𝒟(𝒯)=(𝒮,𝜶,𝜷), where 𝜶={αe:e𝒯(1)} and 𝜷={βt:t𝒯(2)}. We call 𝒟(𝒯) the Heegaard diagram induced by the triangulation 𝒯.

Proof of inequalities (1a) and (1b) in Theorem 1.

For (1a), note that each triangle of 𝒯 contains exactly three vertices of the Heegaard diagram 𝒟:=𝒟(𝒯) induced by 𝒯 (Figure 4), and each tetrahedron has four triangular faces identified in pairs, hence |V(𝒟)|=34n/2=6n. To show (1b), take an optimal tree decomposition 𝒳=(T,) of Γ(𝒯), where T=(I,F) is a tree, ={Bi:iI} is the corresponding set of bags, and max{|Bi|:iI}=tw(Γ(𝒯))+1. We turn 𝒳 into a tree decomposition 𝒳=(T,) of 𝒟 as follows.

  • T=T, i.e., the tree structure of the decomposition remains the same.

  • ={Bi:iI} and for each iI, the bag Bi is obtained from Bi by replacing each σBi with the (at most) 12 vertices of 𝒟 incident to σ, see Figure 4.

Clearly, |Bi|12|Bi|. We now check that 𝒳=(T,) is a tree decomposition of 𝒟.

Vertex coverage.

Consider a vertex vV(𝒟). By construction, there exists a tetrahedron σ𝒯, such that v is incident to σ. Thus, for any iI, vBiσBi. However, since iIBi=V(Γ(𝒯)), this implies iIBi=V(𝒟) as well.

Edge coverage.

Let e={u,v}E(𝒟) be any arc of the diagram. Again, by construction of 𝒟, there exists a tetrahedron σ𝒯 that entirely contains e. Let Bi be a bag that contains σ. Then Bi must contain both u and v.

Subtree property.

Fix a vertex vV(𝒟) and consider Iv:={iI:vBi}. We need to show that Iv spans a connected subtree of T=T. Let σ,τ𝒯 be the tetrahedra containing v on their common triangular face (note that σ and τ may coincide) and define Iσ:={iI:σBi} and Iτ:={iI:τBi}. From the definition of it follows that Iv=IσIτ. Since 𝒳 is a tree decomposition of Γ(𝒯), each of Iσ and Iτ spans a connected subtree in T. Moreover, IσIτ: either σ=τ, or {σ,τ}E(Γ(𝒯)), so there exists a bag Bj containing both σ and τ. Thus, the connected subtrees spanned by Iσ and Iτ overlap, hence their union Iv spans a connected subtree as well.

Algorithmic aspects of Theorem 1.

We briefly comment on the computational cost of extracting the Heegaard diagram 𝒟(𝒯) from a given triangulation 𝒯 with n tetrahedra. Recall that for an abstract simplicial complex 𝒞, its barycentric subdivision 𝒞 is the simplicial complex whose ground set is 𝒞, and a collection {τ0,,τk} forms a k-simplex in 𝒞 precisely when the simplices τi𝒞 are nested, that is, when τ0τk. Although a triangulation 𝒯 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 𝒯′′ naturally contains both the canonical handle decomposition chd(𝒯) and the induced Heegaard diagram 𝒟(𝒯). As the barycentric subdivision of a tetrahedron contains 24 tetrahedra, |𝒯′′|=242|𝒯|=576|𝒯|.

Extracting chd(𝓣) from 𝓣′′.

Every vertex v of 𝒯 is of the form v={τ} for some simplex τ𝒯. Let ι:𝒯(0)𝒯′′(0) be the natural inclusion defined by ι({τ})={{τ}}. For every wim(ι), let hw be the smallest subcomplex of 𝒯′′ containing all 3-faces incident to w. If w corresponds to a simplex σ𝒯 of dimension 3k, then hw is regarded as a k-handle. The collection {hw:wim(ι)} forms the canonical handle decomposition chd(𝒯). See Figure 5.

𝒯

𝒯

𝒯′′

chd(𝒯)

Figure 5: A 2-dimensional triangulation 𝒯 with two triangles, its first and second barycentric subdivisions 𝒯 and 𝒯′′ (regarded geometrically), and the canonical handle decomposition chd(𝒯).

Extracting 𝓓(𝓣) from 𝓣′′.

To extract the induced Heegaard diagram 𝒟(𝒯) from 𝒯′′, we need to pinpoint its α- and β-curves, as well as the splitting surface 𝒮 in 𝒯′′. We illustrate this via concrete examples; see Figure 6. We start with the α-curves. Let e𝒯(1) be an edge of 𝒯, and assume that e is contained in four distinct tetrahedra σ1,σ2.σ3,σ4 of 𝒯. Let tij denote the triangular face shared by σi and σj. Consider the subcomplex Ce of 𝒯 spanned by the nine vertices {e},{σ1},{σ2},{σ3},{σ4},{t12},{t23},{t34}, and {t14}. This complex Ce triangulates the dual 2-cell transverse to e (Figure 6, top left). Taking the second barycentric subdivision 𝒯′′ (Figure 6, top middle), we see that the α-curve αe corresponding to e is readily obtained as the polygonal curve spanned by the vertices of Ce adjacent to {{e}} (Figure 6, top right). The β-curves can be located analogously (Figure 6, bottom row).

Figure 6: Locating the α- and β-curves 𝒟(𝒯) in the second barycentric subdivision 𝒯′′ of 𝒯.

A triangulation of the splitting surface 𝒮 can also be readily obtained as the boundary of the subcomplex of 𝒯′′ formed by the union of the triangulated 2- and 3-handles of chd(𝒯). 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 n=|𝒯|.

 Remark 4.

Often it is assumed – and in certain applications even required, cf. [24] – that a Heegaard diagram 𝒟=(𝒮,𝛂,𝛃) be minimal, i.e. |𝛂|=|𝛃|=g(𝒮). In our setting, we can ensure this by first choosing arbitrary spanning trees T1 and T2 for the 1-skeleton 𝒯(1) and the dual graph Γ(𝒯) of 𝒯, respectively, and then retaining only those α-curves (resp. β-curves) that correspond to edges of 𝒯(1) (resp. Γ(𝒯)) not contained in T1 (resp. T2).

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 𝒯 into a triangulation 𝒯 with maximum edge valence at most 9 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 𝒯 of a closed 3-manifold with n tetrahedra, 𝐯 vertices, tw(Γ(𝒯))=𝐭𝐰, and maximum edge valence Δ(𝒯)=𝚫, yields a triangulation 𝒯 of with O((n+𝐯)log2(𝚫)5.32) vertices and tetrahedra, tw(Γ(𝒯))<(𝐭𝐰+1)log2(𝚫)5.17, and Δ(𝒯)9. The algorithm runs in O(nloglogn) 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 𝒯 of a closed 3-manifold with n tetrahedra, 𝐯 vertices, tw(Γ(𝒯))=𝐭𝐰, and Δ(𝒯)=𝚫, constructs a triangulation 𝒯 of with at most (28+46)n+(16+46)𝐯 tetrahedra, (6+6)(n+𝐯) vertices, Δ(𝒯)max{𝚫+4,9}, and tw(Γ(𝒯))36𝐭𝐰. The algorithm runs in O(n) time.

The proof of Theorem 6 is the core of this section. We prove Theorem 5 at the end of it.

Setup.

Let us fix a triangulation 𝒯 of a closed 3-manifold with n tetrahedra, |𝒯(0)|=𝐯 vertices, treewidth tw(Γ(𝒯))=𝐭𝐰, and maximum edge valence Δ(𝒯)=𝚫. Let S=S(𝒯) be the spine of dual to 𝒯. It is a 2-dimensional polyhedral cell complex whose 1-skeleton S(1) is the dual graph Γ(𝒯), and for each edge e𝒯(1), S contains a polygonal 2-face Fe glued along the cycle in Γ(𝒯) formed by the vertices corresponding to the tetrahedra that contain e. Locally, at each tetrahedron of 𝒯, the spine S looks like the configuration shown in Figure 7.

 Remark.

Spines, and in particular special spines, offer a perspective on 3-manifolds that is dual to that provided by triangulations. We refer to [32, Chapter 1] and [37] for details.

Overall strategy.

Note that, given the spine S, we can recover by first thickening S and then filling in the resulting 2-sphere boundary components with 3-balls (which may be viewed as centered at the vertices of 𝒯). In what follows, we triangulate S and fill in these missing balls combinatorially. Throughout, the term 2-face refers to the faces of the spine S, 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 2-faces of S in order to control the treewidth of the resulting triangulation.

Figure 7: The intersection of the spine S with a tetrahedron of 𝒯. The vertices of S bijectively correspond to the centers of tetrahedra of 𝒯, and each 2-face of S is transverse to an edge of 𝒯.

Triangulating the faces of 𝑺.

Consider a 2-face F:=Fe of the spine S transverse to an edge e𝒯(1). This face F is a k-gon, where k=val(e), whose vertices are the centers of the tetrahedra of 𝒯 containing e. We triangulate F as follows (see Figure 8). If k9, we add a vertex w at the center of F and connect it to all boundary vertices, as in Figure 8 (left). If k>9, we proceed as follows. Fix an arbitrary orientation of the boundary of F, and choose positive integers m:=mF and d:=dF such that km(d1). Label the boundary vertices u0,,uk1 in accordance with this orientation. Introduce a ring of m interior vertices v0,,vm1, and connect each vi to vi1 and vi+1 (indices modm). For each 0i<m1, connect vi to the boundary vertices ui(d1),,u(i+1)(d1). The final interior vertex vm1 is connected to u(m1)(d1),,uk1,u0. The inequalities (m1)(d1)<km(d1) ensure that the vertices ui and v, together with these edges, form a triangulated annulus. Finally, we place a central vertex w inside F and connect it to all vi, see Figure 8 (right).

The next proposition follows directly from this construction; k, m, and d are as above.

Proposition 7.

The triangulation of the 2-face F described above consists of k+2m triangles. Each boundary vertex ui is incident to 3 or 4 edges, each interior vertex vj is incident to at most d+3 edges, and the central vertex w is incident to m edges. In particular, the maximum degree of a vertex in the 1-skeleton of F is max{m,d+3}.

Figure 8: Triangulating a 2-face F (a k-gon) of the spine S of 𝒯 if k9 (left) and if k>9 (right).

Building the triangulation 𝓣 in Theorem 6.

Let 𝒯S denote the triangulation of the spine S obtained by triangulating each 2-face F of S as described above. We construct the triangulation 𝒯 by first taking 𝒯S, considered as embedded in the geometric realization 𝒯 of 𝒯, and then adding the vertices 𝒯(0). Each vertex a𝒯(0) lies in the interior of a connected component of 𝒯S, which is an open 3-ball denoted by Ba. Its boundary Ba:=Ba¯Ba is a subpolyhedron of S comprised of certain 2-faces of S. Let 𝒯Ba denote the subtriangulation of 𝒯S formed by the union of the triangulations of these 2-faces of S. To complete the construction, for each a𝒯(0) we cone over 𝒯Ba from the vertex a. We denote the resulting triangulation by 𝒯. By construction, 𝒯 triangulates .

 Remark.

In the above construction, for each 2-face F we fix integers m=mF and d=dF that depend solely on the number of boundary vertices ui of F in S, or equivalently, on the valence of the edge of 𝒯 transverse to F. When the context requires, we write dF and mF.

Definition 8 (type of a vertex of 𝒯).

The vertices of 𝒯 fall into the following three types. 1. vertices a𝒯(0), 2. vertices ui lying on the boundary of exactly six 2-faces of S, and 3. vertices v and w lying in the interior of exactly one 2-face of S.

We proceed with investigating the maximum edge valence and the treewidth of 𝒯.

Lemma 9.

The triangulation 𝒯 has edge valences at most maxFSmax{dF+3,mF,9}.

Proof.

We consider, case by case, the different types of edges in 𝒯. Let a denote a vertex of 𝒯(0), and let ui, v, and w denote vertices in a 2-face F, see Figure 8. (We keep this labeling convention throughout this section.) The next valence-bounds follow from Proposition 7.

Type {a,w}.

The valence of the edge of this type is equal to the degree of w in the triangulation of the 2-face, i.e., val({a,w})=m.

Type {a,v}.

The valence of the edge of this type is equal to the degree of v in the triangulation of the 2-face, i.e., d+3.

Type {a,ui}.

is incident to at most 3 tetrahedra per 2-face containing ui, and there are at most three 2-faces containing ui and bounding the ball containing a, so val({a,ui})9.

Type {w,v} or {v,ui}.

are incident to at most 4 tetrahedra, two on either side of F,

Type {ui,ui+1}.

is incident to one tetrahedra {a,v,ui,ui+1} per 2-face that contains it, and is contained in at most three 2-faces, therefore val({ui,ui+1})3.

Hence, for the maximum edge valence of 𝒯 we have Δ(𝒯)max{dF+3,mF,9}.

Lemma 10.

The dual graph of the triangulation 𝒯 has treewidth tw(Γ(𝒯))<36(𝐭𝐰+1).

Proof.

Consider a tree decomposition 𝒳=(T,) of the graph Γ(𝒯) with optimal width 𝐭𝐰.

By construction, every tetrahedron of 𝒯 contains a vertex of 𝒯(0) and at least one triangle from the triangulation of a 2-face F of S. Following the notation of Figure 8, these triangles are of the form {v,ui1,ui}, {v1,u(d1),v+1}, or {w,v1,v}. For any 2-face of S, the boundary vertices u0,,uk1 correspond to nodes of the graph Γ(𝒯), and consequently each of them appears in some bag of this tree decomposition 𝒳.

We now construct a tree decomposition 𝒳=(T,) for the dual graph of 𝒯, with the same underlying tree T as for 𝒳 and ={Bτ:τV(T)}. We initialize Bτ as Bτ= for all τV(T), and consider all types of tetrahedra σ in 𝒯:

  1. 1.

    If σ has a triangular face {v,ui1,ui}, then add σ to all bags Bτ such that ui1Bτ.

  2. 2.

    If σ has a face {v1,u(d1),v+1}, then add σ to all bags Bτ such that u(d1)Bτ. Similarly, for σ={a,vm1,u0,v0}, add σ to all bags Bτ such that u0Bτ.

  3. 3.

    If σ has a face {w,v1,v}, then add σ to all bags Bτ such that Bτ contains any ui with (d1)i<max{(+1)(d1),k1}.

Figure 9: Illustrations of 7 possible triangles shared by tetrahedra in 𝒯 from the proof of Claim 11.
Claim 11.

𝒳=(T,) is a valid tree decomposition of the dual graph Γ(𝒯) of 𝒯.

Proof.

We verify the three defining properties of a tree decomposition (Section 2.1).

Vertex coverage.

By construction, any tetrahedron of 𝒯 contains a triangle from a 2-face F of the spine S, and in consequence appears in some bag of 𝒳=(T,).

Edge coverage.

Showing that every edge of 𝒯 is contained in some bag of 𝒳 can be carried out by a tedious case analysis. In the triangulation 𝒯, 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 {a,v,ui,ui+1}, {a,v1,u(d1),v} and {a,vm1,u0,v0} appear exactly in the bags Bτ such that Bτ contain a certain fixed tetrahedron (respectively ui, u(d1), and u0); the bags containing them are consequently connected in σ. By 3, a tetrahedron σ of type {a,w,v1,v} is inserted in all bags Bτ such that Bτ contains any ui with (d1)i<(+1)(d1). Call Ti the subtree of T spanned by the nodes τ such that uiBτ in 𝒳. The subtree of T spanned by the nodes τ in 𝒳 such that σBτ is, in consequence, (d1)i<(+1)(d1)Ti. Because 𝒳 is a tree decomposition, each Ti is connected. Additionally, for any i, ui and ui+1 are adjacent, and must consequently appear in a common bag of 𝒳. Hence TiTi+1. In consequence, (d1)i<(+1)(d1)Ti is a connected subtree of σ.

Claim 12.

𝒳=(T,) has width less than 36(𝐭𝐰+1).

Proof.

Let Bτ be a bag of 𝒳 of size r. Every occurrence of a tetrahedron ui in Bτ will induce the insertion of at most 6 tetrahedra in Bτ, per 2-face incident to ui, namely tetrahedra (,v,ui,ui+1}, tetrahedra (,v,ui,v+1} if i=(d1) or i=0, and tetrahedra (,w,v1,v} with (d1)imax{(+1)(d1)1,k1}; where indicates at most two possible vertices a and b of 𝒯(0), on either side of the 2-face. Adding the fact that at most six 2-faces are incident to a given tetrahedron ui, the size of a bag Bτ is at most 36 times the size of Bτ. In consequence, the width of 𝒳 is at most 36(𝐭𝐰+1)1. This concludes the proofs of Claim 12 and Lemma 10.

From now on, for the 2-face Fe transverse to the edge e𝒯(1) with valence k=val(e), we set m:=val(e)+4 and d:=val(e)+1, which satisfy the condition km(d1) whenever val(e)>6. The next two lemmas provide bounds on the number of tetrahedra (Lemma 13) and the number of vertices (Lemma 14) in 𝒯. These rely on standard counting arguments for triangulations; see the full version [18].

Lemma 13.

The triangulation 𝒯 has at most (28+46)n+(16+46)𝐯 tetrahedra.

Proof.

Each 2-face, transversal to an edge e of valence val(e), contributes to 2(k+2m)=2val(e)+4(val(e)+4) tetrahedra (k+2m triangles in the transversal 2-face F, holding a tetrahedron on either side of F). In consequence,

e𝒯(1)(2val(e)+4(val(e)+4))[18, Lem. 24, Cor. 25]12n+16(n+𝐯)+4eval(e)
[18, Lem. 26]12n+16(n+𝐯)+46(n+𝐯).

Lemma 14.

The triangulation 𝒯 has at most (6+6)(n+𝐯) vertices.

Proof.

By construction, the vertex set 𝒯(0) consist of the vertices 𝒯(0), the vertices ui (lying on the boundaries of the 2-faces), and, for each e𝒯(1), the val(e)+5 interior vertices on the triangulated 2-face Fe. The vertices ui are in bijection with the tetrahedra of 𝒯, hence there are exactly n of them. The total number of interior vertices over all 2-faces is

e𝒯(1)(val(e)+5)[18, Lemmas 24, 26](6+5)(n+𝐯).

With |𝒯(0)|=𝐯 and the n vertices ui, this gives at most (6+6)(n+𝐯) vertices in 𝒯.

We are now ready to prove the main theorems of this section.

Proof of Theorem 6.

If the maximum edge valence of 𝒯 is at most 9, the algorithm simply returns 𝒯:=𝒯. 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 𝒯, which is O(n).

Finally, the proof of Theorem 5 relies on standard calculations involving geometric series and iterated radicals, as detailed in the full version [18].

Proof of Theorem 5.

If the maximum edge valence of 𝒯 satisfies Δ(𝒯)9, we are done. Otherwise, we construct a sequence of triangulations 𝒯=𝒯0,𝒯1,,𝒯p by iterating the construction of Theorem 6. The triangulation 𝒯r has O((30+46)r(n+𝐯)) tetrahedra and vertices [18, Lemma 23], treewidth tw(Γ(𝒯r))<36r(𝐭𝐰+1) (Lemma 10), and maximum edge valence Δ(𝒯r)max{ar,9} (Lemma 9, with m=val(e)+4 and d=val(e)+1), where (ar)r is the sequence of iterated radicals of [18, Lemma 21], with a0=𝚫, c=4, and L<6.32. By [18, Lemma 22], choosing p=log2log2(𝚫) ensures that the edge valence of 𝒯p is at most 9. We therefore set 𝒯:=𝒯p. Since log2(30+46)<5.32 and log2(36)<5.17, the triangulation 𝒯 has O((n+𝐯)log2(𝚫)5.32) tetrahedra and vertices, treewidth at most (𝐭𝐰+1)log2(𝚫)5.17, and edge valence at most 9. The algorithm performs O(loglog(n)) 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 (𝒟,) 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 𝒟=(𝒮,𝜶,𝜷) together with an orientation for the surface 𝒮 and for each of the α- and β-curves. The quantity (𝒟,) does not depend on the choice of orientation for the α- and β-curves, however, it generally does depend on the chosen orientation for 𝒮. 𝒟=(𝒮,𝜶,𝜷) and a finite-dimensional involutory Hopf algebra over a field 𝔽, which is considered fixed. By construction, (𝒟,)𝔽.

 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 (𝒟,) 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 𝒯 of a 3-manifold gives rise to a Heegaard diagram 𝒟=(𝒮,𝜶,𝜷) of , moreover, in a width-preserving way (Theorem 1). Picking an orientation for 𝒯 induces an orientation also for 𝒮. Then choosing orientations for the α- and β-curves arbitrarily yields an oriented diagram 𝒟. Next, from 𝒟 we build a tensor network 𝒦 following Kuperberg’s construction [23, Section 5], which we finally evaluate to obtain (𝒟,). From now on, we will use the notation (𝒯,):=(𝒟,) to indicate when we regard the invariant as computed from a triangulation, where 𝒟 denotes the oriented Heegaard diagram induced by 𝒯.

Building on Theorem 1 and bounding the treewidth of the tensor network 𝒦 (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 𝔽. Let 𝒯 be an oriented triangulation of a closed oriented 3-manifold with n tetrahedra and treewidth tw(𝒯):=tw(Γ(𝒯))=t. The invariant (𝒯,) can be computed in time O(2O(t)n).

Before discussing the proof of Theorem 15 in detail, we provide an overview on Figure 10.

Figure 10: The algorithmic pipeline of computing (𝒯,) from an oriented triangulation 𝒯. The references on the arrows provide the theoretical backbone, and the framed results indicate our contributions. The running time of the computation is dominated by that of step 3. 𝒦(𝒯,).
 Remark 16.

Theorem 15 asserts that computing (𝒯,) is FPT in the treewidth of 𝒯. 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 𝐏-hard [10], we expect this to hold for computing (𝒯,) for general triangulations as well.

As motivation, let us recall the formula for the invariant (𝒟,) from [23, Section 5]:

(𝒟,):=𝒵(𝒟,)dim𝔽()g(𝒮)|𝜶||𝜷|. (2)

Here g(𝒮) is the genus of the surface 𝒮, and |𝜶| and |𝜷| denote the number of α- and β-curves of 𝒟, respectively. The “complicated” term 𝒵(𝒟,)𝔽 is defined as the evaluation 𝒵(𝒦) of a specific tensor network 𝒦 associated to 𝒟, 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 𝑯 over a field 𝔽 together with three 𝔽-linear maps 𝖬:𝑯𝑯𝑯 (multiplication), Δ:𝑯𝑯𝑯 (comultiplication) and 𝖲:𝑯𝑯 (antipode) satisfying certain axioms (cf. [23, Section 3]). We will assume that dim𝔽(𝑯)< and is involutory, i.e., 𝖲𝖲=id𝑯. The maps 𝖬, Δ and 𝖲 can be regarded as tensors of type (1,2), (2,1) and (1,1), respectively, see Figure 11.

Figure 11: The multiplication, comultiplication and antipode tensors represented as coupons.
Example 17.

The group algebra 𝒢=𝔽G of a finite group G is naturally a Hopf algebra: the multiplication is defined as 𝖬(gh)=gh, the comultiplication as Δ(g)=gg, and the antipode as 𝖲(g)=g1. In [23, Sections 1 and 6] it is shown that (𝒟,𝒢) equals the number of homomorphisms π1()G from the fundamental group of the 3-manifold described by 𝒟 to the group G. (In this case (𝒟,𝒢) is independent of the chosen orientation for 𝒟.)

5.1 Kuperberg’s construction and the proof of Theorem 15

Following [23, Section 5], first we explain how the tensor network 𝒦 – whose evaluation 𝒵(𝒦)=:𝒵(𝒟,) appears in (2) – is constructed from an oriented Heegaard diagram 𝒟. Then we prove Lemma 18, which – together with Theorem 19 – implies Theorem 15.

The construction of 𝓚.

As already mentioned, the building blocks of 𝒦 are the structure tensors 𝖬, Δ and 𝖲 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 Tr(A1A2An)=Tr(AnA1An1) for the trace of matrices. – will be useful:

Figure 12: Diagrammatic abbreviations of the tracial product and tracial coproduct tensors.

Let 𝒟=(𝒮,𝜶,𝜷) be an oriented Heegaard diagram. For every oriented α-curve αi𝜶, we take a copy of the tracial product tensor , where the abstract indices c1,,cp correspond to the crossings on αi (with the β-curves of 𝒟) in the order they are encountered when traversing αi following its orientation. We assign a copy of the tracial coproduct tensor to each oriented β-curve βj𝜷 analogously. Note that each crossing c between an α- and a β-curve of 𝒟 appears exactly twice as an abstract index of the above tensors: once at a product and once at a coproduct. The construction of 𝒦 is concluded by contracting these indices (i.e., joining the respective arrows with wires) with a caveat: if the tangent vectors of the β- and α-curves intersecting at c form (in that order) a negatively oriented basis of the tangent space T𝒮, then the antipode tensor is interposed before contracting (Figure 13).

Figure 13: Instruction manual for assembling the tensor network 𝒦 from its building blocks.

A fully contracted tensor network 𝒩 (such as 𝒦) can be seen as a graph (V(𝒩),E(𝒩)) in the obvious way: V(𝒩) corresponds to the coupons of 𝒩, whereas E(𝒩) to its wires. (We emphasize that 𝒩 is considered here without any diagrammatic abbreviations.)

Lemma 18.

Let 𝒟 be an oriented Heegaard diagram and 𝒦 be the Kuperberg tensor network induced by 𝒟. Then, the number of vertices and the treewidth of 𝒟 and 𝒦 satisfy

Proof.

Both inequalities (3a) and (3b) follow directly from the construction of 𝒦. In fact, the local configurations shown in Figure 14 already reveal the close structural relationship between 𝒟 and 𝒦. We refer to the full version [18] for the complete proof.

(a) Local picture of a Heegaard diagram 𝒟 near an α-curve α1.
(b) The corresponding local picture of the tensor network 𝒦
(c) …and the local picture of its underlying simple graph G𝒦.
(d) Local picture of a Heegaard diagram 𝒟 near an β-curve β1.
(e) The corresponding local picture of the tensor network 𝒦
(f) …and the local picture of its underlying simple graph G𝒦.
Figure 14: The local structural correspondence between a Heegaard diagram 𝒟 and the induced Kuperberg tensor network 𝒦.

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 𝒩 with n tensors can be evaluated in O(2O(vc(𝒩))n) time, where vc(𝒩) denotes the vertex congestion of 𝒩.

Vertex congestion is a graph parameter similar to treewidth, discussed in [1, p. 135]. For a graph G with maximum degree Δ, we have vc(G)(3/2)Δ(tw(G)+1), see [1, Theorem 1 and Remark 3]. Since Kuperberg’s tensor networks are 3-regular graphs, we have

Corollary 20.

Any Kuperberg tensor network 𝒦 can be evaluated in time O(2O(tw(𝒦))|𝒦|), where tw(𝒦) denotes the treewidth and |𝒦| the number of tensors of 𝒦.

Now, if 𝒦 is induced by an oriented triangulation 𝒯 with n tetrahedra, then |𝒦|3|V(𝒟)| and tw(𝒦)2tw(𝒟) by Lemma 18, and |V(𝒟)|6 and tw(𝒟)12tw(𝒯)+11 by Theorem 1. Combining these inequalities with Corollary 20, the Theorem 15 follows.

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