Abstract 1 Introduction 2 Preliminaries 3 Super-Polynomial Growth of the GPD 4 Super-Polynomial Growth of the GPDs Induced by Finite Metric Spaces 5 Conclusion References

Super-Polynomial Growth of the Generalized Persistence Diagram

Donghan Kim ORCID Department of Mathematical Sciences, KAIST, Daejeon, South Korea Woojin Kim ORCID Department of Mathematical Sciences, KAIST, Daejeon, South Korea Wonjun Lee ORCID Department of Mathematical Sciences, KAIST, Daejeon, South Korea
Abstract

The Generalized Persistence Diagram (GPD) for multi-parameter persistence naturally extends the classical notion of persistence diagram for one-parameter persistence. However, unlike its classical counterpart, computing the GPD remains a significant challenge. The main hurdle is that, while the GPD is defined as the Möbius inversion of the Generalized Rank Invariant (GRI), computing the GRI is intractable due to the formidable size of its domain, i.e., the set of all connected and convex subsets in a finite grid in d with d2. This computational intractability suggests seeking alternative approaches to computing the GPD.

In order to study the complexity associated to computing the GPD, it is useful to consider its classical one-parameter counterpart, where for a filtration of a simplicial complex with n simplices, its persistence diagram contains at most n points. This observation leads to the question: Given a d-parameter simplicial filtration, could the cardinality of its GPD (specifically, the support of the GPD) also be bounded by a polynomial in the number of simplices in the filtration? This is the case for d=1, where we compute the persistence diagram directly at the simplicial filtration level. If this were also the case for d2, it might be possible to compute the GPD directly and much more efficiently without relying on the GRI.

We show that the answer to the question above is negative, demonstrating the inherent difficulty of computing the GPD. More specifically, we construct a sequence of d-parameter simplicial filtrations where the cardinalities of their GPDs are not bounded by any polynomial in the number of simplices. Furthermore, we show that several commonly used methods for constructing multi-parameter filtrations can give rise to such “wild” filtrations.

Keywords and phrases:
Persistent homology, Möbius inversion, Multiparameter persistence, Generalized persistence diagram, Generalized rank invariant
Copyright and License:
[Uncaptioned image] © Donghan Kim, Woojin Kim, and Wonjun Lee; licensed under Creative Commons License CC-BY 4.0
2012 ACM Subject Classification:
Mathematics of computing Algebraic topology
; Theory of computation
Related Version:
Full Version: https://arxiv.org:2412.04889 [38]
Acknowledgements:
WK thanks Jisu Kim and Facundo Mémoli for their feedback on parts of an earlier draft of this paper.
Funding:
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (RS-2025-00515946).
Editors:
Oswin Aichholzer and Haitao Wang

1 Introduction

(Multi-parameter) Persistent Homology.

Persistent homology is a central concept in Topological Data Analysis (TDA), which is useful for studying the multi-scale topological features of datasets [16, 17, 27]. In the classical one-parameter setting, topological features in datasets are summarized in the form of persistence diagrams or barcodes [23, 65], which serve as complete, discrete invariants of the associated persistence modules.

Multi-parameter persistent homology generalizes persistent homology. In the d-parameter setting, topological features of datasets are indexed by the poset d or a subposet of d [11, 18]. This generalization allows for a finer extraction of topological features, enabling a more detailed analysis of complex datasets [19, 24, 46, 47, 59, 63, 64]. However, the algebraic structure of multi-parameter persistence modules, i.e. functors from the poset d (d2) to the category 𝐯𝐞𝐜𝔽 of finite dimensional vector spaces over a field 𝔽, is significantly more complex, and in fact no complete discrete invariant exists for multi-parameter persistence modules [18].

Generalized Persistence Diagram (GPD).

Many incomplete, but potentially useful invariants for multi-parameter persistence modules have been studied; e.g. [3, 4, 8, 12, 21, 34, 35, 44, 45, 51, 54, 58]. The Generalized Persistence Diagram (GPD) is one such invariant and is a natural extension of the persistence diagram for one-parameter persistence [39, 55]. The GPD is defined as the Möbius inversion of the Generalized Rank Invariant (GRI)111The term “generalized persistence diagram” sometimes refers to different concepts; e.g. [14, 52, 56]. Also, we note that the notion of the GRI stems from the concept of the rank invariant [18]. , which captures “persistence” in multi-parameter persistence modules or, more generally, any linear representations of posets [40]. Many aspects of the GPD and GRI–such as stability, discriminating power, computation, connections to other invariants, and generalizations–have been studied; e.g. [5, 12, 22, 25, 26, 31, 41, 42]. Also, a vectorization method for the (restricted) GRI has recently been proposed and utilized in a machine learning context [53, 64]. There are also other works on invariants of multi-parameter persistence modules that are closely related to the GPD and GRI; e.g. [3, 4, 5, 8, 15, 34, 36].

Challenges in Computing the GPD.

While many properties of the GPD have been clarified in the aforementioned works, computing the GPD, unlike its classical counterpart, remains a significant challenge. The main hurdle is that, while the GPD is defined as the Möbius inversion of the GRI, computing the GRI is intractable mainly due to the formidable size of its domain. For instance, the domain of the GRI of a persistence module over a finite grid Gd is the set of all intervals in G (cf. Definitions 2 and 5). The cardinality of the domain is huge relative to the cardinality |G| of G even when d=2 ; cf. [2, Theorem 31]. This computational intractability suggests seeking alternative approaches to computing the GPD.

In order to study the complexity associated to computing the GPD, it is useful to consider its classical one-parameter counterpart, where for a filtration of a simplicial complex with N simplices, its persistence diagram contains at most N points. This observation leads to the question: Given a d-parameter simplicial filtration, could the cardinality of its GPD (more precisely, the support of the GPD) also be bounded by a polynomial in the number of simplices in the filtration? In what follows, we make this question more precise.

Size of the GPD.

Let K be an abstract simplicial complex, and let ΔK be the set of subcomplexes of K ordered by inclusion. A monotone map :dΔK such that there exists a pd with p:=(p)=K is called a (d-parameter simplicial) filtration (of K). The number of simplices in the filtration is defined as the number of simplices in K.

Definition 1 ([45]).

We call the filtration finite, if K is finite, and in , every simplex σK is born at finitely many points of d, i.e. there exist finitely many points q1,,qt(σ)d s.t. σp for pd if and only if qip in d for some i=1,,t(σ). We call those points q1,,qt(σ) the birth indices of σ. We also say that σ is born at q1,,qt(σ)d.

If is finite, then for each homology degree m0, the persistence module Hm(;𝔽):d𝐯𝐞𝐜𝔽 is finitely presentable (cf. Definition 3 and Remark 4). This guarantees that the 𝒎-th GPD of any finite d-parameter filtration is well-defined as an integer-valued function on a finite subset of intervals of d (cf. Definition 5 and Remark 7), denoted by dgmm(). By the size of dgmm() we mean the cardinality of the support of dgmm(), i.e. |{IInt(d):dgmm()(I)0}| (cf. Definition 2). Since the notion of the GPD reduces to that of the persistence diagram when d=1 [22, Section 3], in this case, the size of the GPD becomes the number of points in the persistence diagram. Our question is as follows.

Question.

Does there exist k0 such that for any homology degree m0, the size of the m-th GPD of any finite simplicial filtration over d is O(Nk) where N stands for the number of simplicies in ?

Note that when d=1, the answer to the question is yes, and k can be taken to be 1, in which case we compute the persistence diagram directly at the simplicial filtration level [28]. If the answer is also yes when d2, it might be possible to compute the GPD of multi-parameter filtrations directly and much more efficiently without relying on the GRI of the persistence module Hm(;𝔽):d𝐯𝐞𝐜𝔽.

Our contributions

  1. 1.

    We show that the answer to Question above is negative, demonstrating the inherent difficulty of computing the GPD (Theorem 13). More specifically, we construct a sequence (n) of finite d-parameter simplicial filtrations where the sizes of their GPDs are not bounded by any polynomial in the number of simplices in n.

  2. 2.

    We also show that several well-known methods for constructing multi-parameter filtrations – Sublevel-Rips, Sublevel-Čech, Degree-Rips, and Degree-Čech – can give rise to such “wild” filtrations (Theorems 25 and 24).

  3. 3.

    We find that computing the value of the GPD for a 2-parameter filtration containing O(ns) simplices, for some s, via the Möbius inversion of the GRI can result in the problem of summing Θ(2n) integers, which is an EXPTIME problem (Corollary 26). This implies that, even with the fully computed GRI, computing the GPD through Möbius inversion of the GRI remains computationally challenging.

It is noteworthy that in the proofs of some of our results, we employ techniques inspired by some recent works on the GRI [12, 22] as well as Rota’s Galois connections [33]; see the proof of Theorem 13 for the case of d>2 and that of Lemma 21.

Other related works.

Botnan, Oppermann, Oudot investigated the computational complexity of the minimal rank decomposition of the standard rank invariant as part of their results [12, Remark 5.3]. Also, Botnan, Oppermann, Oudot, Scoccola found an upper bound on the size of the rank exact decomposition of a persistence module, which is a polynomial in the size of the (usual) multigraded Betti numbers of the module [13].

Clause, Kim, Mémoli identified a tame persistence module M over 2 (a concept introduced by Miller [51]) whose GRI does not admit a Möbius inversion [22, Theorem B]. Our construction of persistence modules in Section 3 is reminiscent of that of M, making it natural to interpret M as a limit object of the types of persistence modules we construct.

Morozov and Patel elucidated a connection between 1- and 2-parameter persistence settings in order to find an output-sensitive algorithm for computing the Möbius inversion of the birth-death function [52]. We also note that there are many recent examples of utilizing Möbius inversion to extract information from (multi-parameter) persistent (co)homology: see e.g. [7, 33, 34, 49, 50, 52, 54, 56, 62].

Alonso, Kerber, Skraba showed that many multi-parameter filtration constructions, such as density- or degree-Rips bifiltrations, and across a general category of point samples in Euclidean space, the probability of the homology-induced persistence module decomposing into interval modules approaches zero as the sample size tends to infinity [1].

Organization.

In Section 2, we review basic terminology and well-known theorems related to persistence modules, as well as the GPD and GRI. In Sections 3 and 4, we establish our main results, as mentioned above. Finally, in Section 5, we discuss future research directions.

2 Preliminaries

Persistence modules and barcodes.

Throughout this paper, P=(P,) is a poset, regarded as the category whose objects are the elements of P, and for any pair p,qP, there exists a unique morphism pq if and only if pq. All vector spaces in this paper are over a fixed field 𝔽. Let 𝐯𝐞𝐜𝔽 denote the category of finite-dimensional vector spaces and linear maps over 𝔽. A functor P𝐯𝐞𝐜𝔽 will be referred to as a persistence module over P or simply a 𝑷-module. A morphism between P-modules is a natural transformation between the P-modules. For any P-modules M and N, their direct sum MN is defined pointwisely. A P-module M is trivial if M(p)=0 for all pP, and we write M=0. A nontrivial P-module M is indecomposable if the assumption MMM′′ for some P-modules M and M′′ implies that either M=0 or M′′=0. By Krull-Remak-Schmidt-Azumaya’s theorem [6, 9], any P-module is isomorphic to a direct sum of indecomposable P-modules, and this decomposition is unique up to isomorphism and permutation of summands.

Definition 2.

An interval I of P is a subset IP such that:

  1. (i)

    I is nonempty.

  2. (ii)

    If p,qI and prq, then rI.

  3. (iii)

    I is connected, i.e. for any p,qI, there is a sequence p=p0,p1,,p=q of elements of I with pi and pi+1 comparable for 0i1.

By Int(P) we denote the set of all intervals of P.

For any pq in P, the set [p,q]:={rP:prq} is called a segment. The collection of all segments (resp. intervals) in P will be denoted by Seg(P) (rep. Int(P)). It is not difficult to see that Seg(P)Int(P).

Given any IInt(P), the interval module 𝔽I is the P-module, with

𝔽I(p):={𝔽ifpI0otherwise.,𝔽I(pq):={id𝔽ifpqI0otherwise (1)

Every interval module is indecomposable [10, Proposition 2.2]. A P-module M is called interval-decomposable if it is isomorphic to a direct sum of interval modules. The barcode of an interval decomposable P-module MjJ𝔽Ij is defined as the multiset barc(M):={Ij:jJ}.

For pP, let p (resp. p) denote the set of points qP such that pq (resp. qp). Clearly, both p and p belong to Int(P).

Definition 3.

A P-module is called finitely presentable if it is isomorphic to the cokernel of a morphism bB𝔽pbaA𝔽pa, where {pa:aA} and {pb:bB} are finite multisets of elements of P.

 Remark 4.

It is well known that, for any finite d-parameter simplicial filtration (Definition 1), the induced d-module Hm(;𝔽), for each m0, is finitely presentable. Namely, Hm(;𝔽) is isomorphic to the cokernel of a morphism jJ𝔽pjiI𝔽pi, where {pj:JJ}{pi:iI} is a subset of the smallest finite d-d grid in d that contains all the birth indices of m- and (m+1)-simplices in . See, e.g. [45].

Generalized Rank invariant and Generalized Persistence Diagram.

Any P-module M admits both a limit and a colimit [48, Chapter V]: A limit of M, denoted by limM, consists of a vector space L together with a collection of linear maps {πp:LM(p)}pP such that

M(pq)πp=πqfor every pq in P. (2)

A colimit of M, denoted by limM, consists of a vector space C together with a collection of linear maps {ip:M(p)C}pP such that

iqM(pq)=ipfor every pq in P. (3)

Both limM and limM satisfy certain universal properties, making them unique up to isomorphism.

Let us assume that P is connected. The connectedness of P alongside the equalities given in Equations (2) and (3) imply that ipπp=iqπq:LC for any p,qP. This fact ensures that the canonical limit-to-colimit map ψM:limMlimM given by ipπp for any pP is well-defined. The (generalized) rank of M is defined to be222This construction was considered in the study of quiver representations [43]. rank(M):=rank(ψM), which is finite as rank(M)=rank(ipπp)dim(M(p))< for any pP. The rank of M is a count of the “persistent features” in M that span the entire indexing poset P [40].

Now, we refine the rank of a P-module, which is a single integer, into an integer-valued function. Options for the domain of the function include Seg(P) or the larger set Int(P).

Definition 5 ([22, 39]).

Let M be a P-module.

  1. (i)

    The generalized rank invariant (GRI) is the map rkM:Int(P)0 given by Irank(M|I) where M|I is the restriction of M to I.

  2. (ii)

    The generalized persistence diagram (GPD) of 𝑴 is defined as the function dgmM:Int(P) that satisfies the equality333This equality generalizes the fundamental lemma of persistent homology [29].

    IInt(P),rkM(I)=JInt(P)JIdgmM(J), (4)

    where the right-hand side of the equation includes only finitely many nonzero summands.

We also remark that, in Definition 5, by replacing all instances of Int(P) by Seg(P), we obtain the notions of the rank invariant and its signed barcode [12, 13, 18].

Theorem 6 (Existence and Uniqueness of the GPD).

Let M be a P-module.

  1. (i)

    If P is finite, then the GPD of M exists.

  2. (ii)

    If P=d (d=1,2,), and M is finitely presentable, then the GPD of M exists. Furthermore, dgmM is finitely supported, i.e. there exist only finite many IInt(d) such that dgmM(I)0.

  3. (iii)

    In each of the previous two cases, the GPD is unique.

Proof.

Item i: If P is finite, then Int(P) is finite. Thus, the claim directly follows from the Möbius inversion formula [57]. Item ii: This statement is precisely that of [22, Theorem C(iii)]. Item iii: In the setting of Item i, the uniqueness is also a direct consequence of the Möbius inversion formula. In the setting of Item ii, the uniqueness is proved in [22, Proposition 3.2].  

 Remark 7 ([22, Theorem C (iii)]).

For any finitely presentable d-module M, assume that M is the cokernel of a morphism bB𝔽pbaA𝔽pa, where A and B are finite index sets. Let 𝒞:={pa:aA}{pb:bB}d. Consider the finite full subposet P:=i=1dπi(𝒞)d, where πi:d is the canonical projection to the i-th coordinate. Then, the GPD of M is directly obtained from the GPD of the restriction M|P, as follows.

We extend d to d{} by declaring that x for all xd. Let P:dP{} be the map sending each xd to the maximal point p=:xP in P{} such that px in d{}. For any Id, let IP denote the set of the points xP for xI. Then, the GPD of M, i.e. dgmM:Int(d), is equal to

I{dgmM|P(IP),if I=P1(J) for some JInt(P)0,otherwise.

This implies that there exists a bijection between the supports of dgm𝐌 and dgm𝐌|𝐏.

We also remark that if P is a finite poset, the condition given in Equation 4 holds if and only if

IInt(P),dgmM(I)=JInt(P)JIμ(J,I)rkM(J), (5)

where μ is the Möbius function of the poset (Int(P),); see [61, Section 3.7] for a general reference on Möbius inversion, and [40] for a discussion of Möbius inversion in this specific context.

We define the size of rkM, denoted by rkM, as the cardinality of its support. Likewise, the size of dgmM is defined as the cardinality of its support and is denoted by dgmM.

 Remark 8.

For any P-module M, the following holds.

  1. (i)

    (Monotonicity) rkM(I)rkM(J) for any pair IJ in Int(P) [39, Proposition 3.8].

  2. (ii)

    For any IInt(P), if rkM(I)=0, then dgmM(I)=0. Hence, we have dgmMrkM [40, Remark 8].

  3. (iii)

    If M is interval decomposable and IInt(P), then dgmM(I) equals the multiplicity of I in barc(M) [25, Theorem 2.10].

In establishing results in later sections, we will utilize the following well-known concrete formulation for the limit of a P-module M (see, for instance, [39, Appendix E]):

Convention 9.

The limit of a P-module M is the pair (L,(πp)pP) described as:

L:={(p)pPpPM(p):pqP,M(pq)(p)=q}

where for each pP, the map πp:LM(p) is the canonical projection. Elements of L are called sections of M.

On 2-d grid lattices.

A join (a.k.a. least upper bound) of SP is an element q0P such that (i) sq0, for all sS, and (ii) for any qP, if sq for all sS, then q0q. A meet (a.k.a. greatest lower bound) of SP is an element r0P such that (i) r0s for all sS, and (ii) for any rP, if rs for all sS, then rr0. If a join and a meet of S exist, then they are unique. Hence, whenever they exist, we refer to them as the join (denoted by S) and the meet (denoted by S), respectively. When S consists of exactly two points s1 and s2, we also use s1s2 and s1s2 instead of S and S, respectively. A lattice is a poset such that for any pair of elements, their meet and join exist. For any n0, let [n]:={0<1<<n}. By a finite d-d grid lattice, we mean a poset isomorphic to the lattice [n1]×[n2]××[nd] for some n1,n2,,nd0.

Let p and q be any two points in a poset P. We say that q covers p if p<q and there is no rP such that p<r<q. By Cov(p), we denote the set of all points qP that cover p.

Lemma 10 ([4, Theorem 5.3]).

Let μ be the Möbius function of the poset (Int([n]2),). Then, for all J,IInt([n]2) with JI,

μ(J,I)={1,if I=J,J=SSCov(I)(1)|S|,otherwise,

where |S| denotes the cardinality of S. Note that when IJ and there is no nonempty SCov(I) such that J=S, the sum above is empty, and thus μ(J,I)=0. We also remark that S represents the smallest interval in [n]2 that contains all the intervals in S.

A subposet LP (resp. UP) is called a lower (resp. upper) fence of P if L is connected, and for any qP, the intersection Lq (resp. Uq) is nonempty and connected [25, Definition 3.1].

Lemma 11 ([25, Proposition 3.2]).

Let L and U be a lower and an upper fence of a connected poset P, respectively. Given any P-module M, we have

limMlimM|LandlimMlimM|U.

Let I be any subset of P. By min(I) and max(I), we denote the collections of minimal and maximal elements of I, respectively. A zigzag poset of n points is 12n1n where stands for either or .

Definition 12 ([25, Definition 3.5]).

For IInt([n]2) with min(I)={p0,p1,,pk}, and max(I)={q0,q1,,ql}, we define the following two zigzag posets

minZZ(I):= {p0<(p0p1)>p1<(p1p2)><(pk1pk)>pk}
= min(I){pipi+1:i=0,,k1},
maxZZ(I):= {q0>(q0q1)<q1>(q1q2)<>(ql1ql)>ql}
= max(I){qiqi+1:i=0,,l1},

which are lower and upper fences of I, respectively [25, Section 3.2].

3 Super-Polynomial Growth of the GPD

The goal of this section is to establish the following theorem.

Theorem 13 (Super-polynomial Growth of the GPD).

Let d,m0 with d2. There does not exist k0 such that, for all finite filtrations over d containing N simplices, dgmm() belongs to O(Nk).

Let K be an abstract simplicial complex and let m0. Let Cm(K;𝔽) and Zm(K;𝔽) be the group of m-chains and that of m-cycles of K, respectively. Let Km be the m-skeleton of K.

To prove the statement, we construct a sequence (n) of filtrations where n contains O(nt) simplices for some t0, but dgmm(n)O(nk) for any k0. By Remarks 4 and 7, it suffices to construct filtrations n over the discrete posets [n]d.

 Remark 14.

In [45], the size of a finite d-parameter filtration of a simplicial complex K is defined as the total number of birth indices across all σK. Even if we adopt this quantity as N in the above theorem, the statement remains true.

We also remark that some techniques used in the following proof are similar to those employed in the proof of [22, Theorem B]. We first prove the statement for the case of d=2.

Proof of Theorem 13 when 𝒅=𝟐.

We consider the cases of m=0 and m1 separately.

Case 1 (𝒎=𝟎).

Fix n0. Let K:=Kn be the simplicial complex on the vertex set K0={z0,z1,,zn} that consists of the 1-simplices {zi,zj} (0i<jn) and their faces. We define a filtration :=n of K over [n]2 as follows. For (i,j)[n]2, let (see Figure 1):

(i,j):={,if i+j<nK0{{zi}},if i+j=nK0,if i+j>n and (i,j)(n,n)K,if (i,j)=(n,n). (6)

Let M:=H0(;𝔽):[n]2𝐯𝐞𝐜𝔽. Then, we have:

Figure 1: For n=3, the filtration over [n]2 defined in Equation (6), along with the intervals U and D of [n]2, as described in Equation (9).
M(i,j){0,if i+j<n𝔽n,if i+j=n𝔽n+1,if i+j>n and (i,j)(n,n)𝔽,if (i,j)=(n,n). (7)

Let i[n]. Then, for every (x,y)[n]2 that covers (i,ni), we have that

M((i,ni)(x,y)) = ιin: 𝔽n 𝔽n+1
(v1,,vn) (v1,,vi,0,vi+1,,vn). (8)

In what follows, we use ιi in place of ιin. Now, we consider the following two intervals of [n]2 (see Figure 1):

U:={(i,j)[n]2:ni+j}andD:={(i,j)[n]2:ni+jn+1}. (9)

By proving the following claims, we complete the proof for the case of m=0.

Claim 15.

If JInt([n]2) is not a proper subset of U, then rkM(J)=0.

Proof.

First, assume that there exists a point pJU. Then, by the construction of M, dim(M(p))=0 and thus rkM(J)=0 by monotonicity of rkM (Remark 8 Item i). Next, assume that J=U. Since rkM(U)=rank(limM|UlimM|U), it suffices to show limM|U=0. Again, since D=minZZ(U) , by Lemma 11, it suffices to show that limM|D=0. By Equation (8), the diagram M|D is given by

𝔽nι0𝔽n+1ι1𝔽nι1𝔽n+1ι2𝔽nι2𝔽n+1ι3𝔽nι3ιn𝔽n.

From this, it is not difficult to see that limM|D=0: For pD, let πp:limM|DM(p) be the canonical projection. For any i=0,,n and for any vlimM|D, let π(i,ni)(v)=:(v1i,v2i,,vni)𝔽n=M(i,ni). Then, Equations (2) and (8) imply the following pair of equalities for each i=1,,n:

π(i,ni+1)(v)=ιi1π(i1,ni+1)(v)=(v1i1,,vi1i1,0,vii1,vi+1i1,,vni1),π(i,ni+1)(v)=ιiπ(i,ni)(v)=(v1i,,vi1i,vii,0,vi+1i1,,vni),

and thus vii=vii1=0 for i=1,n. From this, we deduce that vji=0 for all i=0,1,,n and j=1,2,,n. Therefore, π(i,ni)(v)=0 for all i=0,1,,n and in turn v=0. Since vlimM|D was arbitrary, we have limM|D=0.

Consider the following intervals of [n]2 (see Figure 2):

Ui:=U{(i,ni)}for each i[n]. (10)
Figure 2: For n=3, the intervals U0,U1,U2,U3 of [n]2 that are defined in Equation (10).
Claim 16.

Let JInt([n]2) such that i=0nUiJU. Then, rkM(J)=1.

Proof.

Since JU, there exists i[n] such that JUi. Fix such i. Since max(J)={(n,n)}, by Lemma 11, we have the isomorphism limM|J()M(n,n). Observe that for every pJUi, {zi}p. Hence, by Convention 9 and the definition of M, we have that

([zi])pJlimM|JpJH0(p;𝔽).

Clearly, this tuple ([zi])pJ maps to [zi]H0((n,n);𝔽)=M(n,n) via the limit-to-colimit map of M over J, followed by the isomorphism (). Since [zi]M(n,n) is nonzero and dimM(n,n)=1 (cf. Equation 7), we have that rkM(J)=1, as desired.  

Claim 17.

dgmM(Ui)=1 for every i[n].

Proof.

We have:

1 =rkM(Ui) by Claim 16
=IInt([n]2)IUidgmM(I) by Equation (4)
=dgmM(Ui) by Claim 15 and Remark 8 Item ii.

For each nonempty S[n], we define US:=iSUi, which is an interval of [n]2.

Claim 18.

For each nonempty S[n], we have that dgmM(US)=(1)|S|+1.

Proof.

Let I:=US. When |S|=1, there exists i[n] such that I=Ui. We already proved that dgmM(Ui)=(1)1+1=1. If |S|>1, then

dgmM(I) =JInt(P)JIμ(J,I)rkM(J) by Equation 5
=JInt(P)UJIμ(J,I)rkM(J) by Claim 15
=JInt(P)UJI(1)|JI|rkM(J) by Lemma 10
=SS(1)|S| by Claim 16, letting S=JI
=(11)|S|(1)|S|=(1)|S|+1 by the binomial theorem

as desired. The number of nonempty subsets S[n] is 2n+11 and each S corresponds to the interval US such that dgmM(US)0. Hence, dgm0()=dgmM2n+11. In particular, there is no k0 such that 2n+11O(Nk) for N:=(n2+n)/2, the number of simplices in the filtration , completing the proof.

Case 2 (𝒎𝟏).

Let K:=Kn,m be the smallest simplicial complex on the vertex set {x0,,xn,y0,,ym}, containing all m-simplices τ,τij, and (m+1)-simplices σij that are the underlying sets of the following oriented simplices (see Figure 3a):

τ+ :=[y0,,ym]
τij+ :=[xi,y0,,yj1,yj+1,,ym], for 0in, 0jm,
σij+ :=[xi1,xi,y0,,yj1,yj+1,,ym], for 1in, 0jm.

For 0kn, let Lk be the m-dimensional subcomplex of K, whose m-simplices are exactly τ and {τkj:0jm} (see Figure 3a).

We define the filtration :=n,m:[n]2ΔK (=ΔKn,m) as (see Figure 3b):

(i,j):={,if i+j<nk[n]{i}Lk,if i+j=nk[n]Lk,if i+j>n and (i,j)(n,n)K,if (i,j)=(n,n). (11)

Note that, for each 0in, the m-chain ci=τ+j=0m(1)jτij+ in Cm(K;𝔽) satisfies ci=0, i.e. ci is an m-cycle. Moreover, Hm(Li;𝔽), which is isomorphic to Zm(Li;𝔽), is the 1-dimensional vector space generated by the homology class [ci].

Figure 3: Illustration of the constructions described in Case 2.

Let N:=Hm(;𝔽):[n]2𝐯𝐞𝐜𝔽. We claim that N is isomorphic to M, given in Equation 7. Indeed,

N(i,j){0,if i+j<n[c0],,[ci1],[ci+1],,[cn]𝔽n,if i+j=n[c0],,[cn]𝔽n+1,if i+j>n and (i,j)(n,n)𝔽,if (i,j)=(n,n)

and for each pair pq in [n]2, N(pq)M(pq). Therefore, there is no k0 such that dgmm()=dgmN=dgmM=2n+11O(Nk) for N, the number of simplices in the filtration , which belongs to O(nm+2).

In order to prove Theorem 13 for the case where d>2, we utilize a result from [12, Section 3.2] and techniques present in [22, Section 3]. See the full version [38] for details.

 Remark 19.

Notably, the supports of the GPDs we have considered contain many overlapping intervals with opposite-signed values. This makes it difficult to interpret the information the GPDs convey, unlike persistence diagrams for one-parameter persistence modules.

4 Super-Polynomial Growth of the GPDs Induced by Finite Metric Spaces

In this section, we show that the sizes of the 1-st GPDs of the sublevel-Rips, sublevel-Čech, degree-Rips, and degree-Čech bifiltrations are not bounded by any polynomial in the number of points in the input metric space (Theorems 24 and 25). We prove these results by constructing specific point sets in 3 that induce persistence modules isomorphic, or structurally similar to, those appearing in the proof of Theorem 13. Also, we make use of Rota’s Galois connection.

A Galois connection between two posets P and Q is a pair of monotone maps g1:PQ:g2 satisfying g1(p)q iff pg2(q) for any pP and qQ. Let f:PQ be any function. For any h:P, the pushforward of h along f is the function fh:Q given by fh(q)=pf1(q)h(p). For any :Q, the pullback of along f is the function f:P defined by f(p)=(f)(p). For any poset P, let P denote the Möbius inversion operator over P. To say that the GPD of a P-module M exists is equivalent to stating that Int(P)rkM is well-defined and equals dgmM.

Lemma 20 ([33, Theorem 3.1]).

Let P be a finite poset, Q be any poset, and g1:PQ:g2 be a Galois connection. Then, Qg2=g1P.

Lemma 20 is crucial for establishing the following lemma, whose second item is essential for the proofs of both Theorem 24 and Theorem 25. See the full version [38] for the proof.

Lemma 21.

Let P be a finite poset, M be a P-module, and IP be an interval of P. Then,

  1. (i)

    for every JInt(I), we have dgmM|I(J)=JInt(P)JΠ(JI)dgmM(J), where Π(JI) denotes the coarsest partition of JI into disjoint intervals of I.

  2. (ii)

    Furthermore, if P and I are finite 2-d grid, then dgmMdgmM|I.

 Remark 22.

Lemma 21 Item ii does not generally hold in higher dimensions, i.e. for d3, there exist d-d grids P and I with IP and a P-module M such that dgmM<dgmM|I.

4.1 Sublevel-Rips and Sublevel-Čech Bifiltrations

For r0, the Vietoris-Rips complex of a metric space (X,𝖽X) at scale r is defined as

Rips((X,𝖽X))r ={finite σX:maxx,yσ𝖽X(x,y)r}.

Now assume that Xd, where d is equipped with a metric 𝖽, and 𝖽X=𝖽|X×X. The Čech complex of (X,𝖽X) in (d,𝖽) at scale r is

Cˇech((X,𝖽X))r ={finite σX:xσBr(x)},

where Br(x)={yd:𝖽(x,y)r}.

Lemma 23 ([32, Lemma VII]).

Let (d,ρ) be the Euclidean space with the supremum metric ρ. For any finite Xd and any r0, we have Cˇech((X,ρ|X×X))r=Rips((X,ρ|X×X))2r.

Let γ:X be a function. For any a and any r0 (see e.g. [18]),

  1. (i)

    the sublevel-Rips complex at scale r and threshold a is Rips((X,𝖽,γ))a,r:=
    Rips(γ1((,a]))r. The sublevel-Rips bifiltration of (X,𝖽,γ) is the simplicial filtration Rips((X,𝖽,γ)):={Rips((X,𝖽,γ))a,r}a,r0 over ×0.

  2. (ii)

    the sublevel-Čech complex at scale r and threshold a is Cˇech((X,𝖽,γ))a,r:=
    Cˇech(γ1((,a]))r. The sublevel-Čech bifiltration of (X,𝖽,γ) is the simplicial filtration Cˇech((X,𝖽,γ)):={Cˇech((X,𝖽,γ))a,r}a,r0 over ×0.

Let

ΓX:=im(γ)andTX:=im(𝖽)0. (12)

By Remarks 4 and 7, for each m0, the size of the GPD of M:=Hm(Rips((X,𝖽,γ)),𝔽):×0𝐯𝐞𝐜𝔽 equals dgmM|ΓX×TX.

Theorem 24 (Super-polynomial GPD of Sublevel-Rips and Sublevel-Čech filtrations).

There does not exist k0 such that for every metric space (X,𝖽) and every function γ:X, dgm1((X,𝖽,γ)) belongs to O(|X|k), where (X,𝖽,γ){Rips((X,𝖽,γ)),Cˇech((X,𝖽,γ))}.

Given any set Ad and r, let rA:={rad:aA}. When d2, let π:d2 be the projection (x1,,xd)(x1,x2).

Proof Sketch.
Figure 4: For n=3, the set Xn that is defined in the proof of Theorem 24.

By Lemma 23, it suffices to show the statement when (X,𝖽,γ)=Rips((X,𝖽,γ)). Let n1. We construct an Xn3, which consists of 4n(n+2) points and inherits the metric 𝖽n from the supremum metric on 3. Our goal is to show that dgm1(Rips((Xn,𝖽n,γn))) does not belong to O(nk) for any k, which then does not belong to O(|Xn|k) for any k. Let ϵn:=1/n2. Let Xn=(i=0nYi)(i=0n1Zi) (see Figure 4), where, for i[n], Yi is the subset of the plane z=2in in 3 whose projected image πYi onto 2 is described below, and Zi is the subset of the plane z=(2i+1)n in 3 whose projected image πZi onto 2 is described below. Let A:={(1,0),(0,1),(1,0),(0,1)}, bj:=njϵn for j[n], πYi:=0jnjibjA, and πZi:=b0A. Note that |Xn|=|i=0nYi|+|i=0n1Zi|=4n(n+1)+4n=4n(n+2). Let γn:Xn be

γn(w)={j,if wi=0nYi and π(w)bjA for some 0jn,n,if wi=0n1Zi

so that ΓXn=im(γn)={0<1<<n}. In the full version [38], we show that for n:=Rips((Xn,𝖽n,γn)) on ΓXn×TXn (Figure 5), dgm1(n) does not belong to O(|Xn|k) for any k. In particular, we identify an interval of ΓXn×TXn on which the restriction of Mn:=H1(n;𝔽) is isomorphic to M from Equation (7), and then apply Lemma 21 Item ii.

Figure 5: Partial illustration of the filtration 3 on ΓX3×T3. The body of 3(3,3) is homotopy equivalent to the cylinder S1×[0,1]. The 1-cycles in 3(2,3ϵ3), 3(2,32ϵ3), and 3(3,32ϵ3) become homologous in 3(3,3).

4.2 Degree-Rips and Degree-Čech Bifiltrations

Let (X,𝖽) be a metric space. For d and r0,

  1. (i)

    the Degree-Rips complex at scale r and degree d [45], denoted DRips((X,𝖽))d,r, is the maximal subcomplex of Rips((X,𝖽))r whose vertices have degree at least d1 in the 1-skeleton of Rips((X,𝖽))r. The Degree-Rips bifiltration of (X,𝖽) is the simplicial filtration DRips((X,𝖽)):={DRips((X,𝖽))d,r}dop,r0 over op×0.

  2. (ii)

    The Degree-Čech complex at scale r and degree d [30], denoted DCˇech((X,𝖽))d,r, is the maximal subcomplex of Cˇech((X,𝖽))r whose vertices have degree at least d1 in the 1-skeleton of Cˇech((X,𝖽))r. The Degree-Čech bifiltration of (X,𝖽) is the simplicial filtration DCˇech((X,𝖽)):={DCˇech((X,𝖽))d,r}dop,r0 over op×0.

We consider the finite subposets

JX:={|X|1<|X|2<<1}opandTX:=im(𝖽)0.

By Remarks 4 and 7, for each m0, the size of the GPD of M:=Hm(DRips((X,𝖽)),𝔽):op×0𝐯𝐞𝐜𝔽 equals dgmM|JX×TX.

Theorem 25 (Super-polynomial GPD of Degree-Rips and Degree-Čech filtrations).

There does not exist k0 such that for every finite metric space (X,𝖽), dgm1((X,𝖽)) belongs to O(|X|k), where (X,𝖽){DRips((X,𝖽)),DCˇech((X,𝖽))}.

Proof Sketch.

By Lemma 23, it suffices to show the statement when (X,𝖽)=DRips((X,𝖽)).

Let n1. We construct an Xn3, which consists of 4(n+1)2 points and inherits the metric 𝖽n from the supremum metric on 3. Our goal is to show that dgm1(DRips((Xn,𝖽n))) does not belong to O(nk) for any k, which then does not belong to O(|Xn|k) for any k. Let ϵn:=1/n2. Let Xn:=i=0nYi (see Figure 6), where, for i[n], Yi is the subset of the plane z=(n+ϵn)i in 3 whose projected image πYi onto 2 is described below. Let A:={(1,0),(0,1),(1,0),(0,1)}, B:={(1,ϵn),(ϵn,1),(1,ϵn),(ϵn,1)}, and a:=nnϵn. For j[n+1], let bj:=a+jϵn=n+(jn)ϵn.

Figure 6: For n=3, the set Xn that is defined in the proof of Theorem 25.

Let

πYi:=aA(0jnji(a+bi)A)(a+bi+1)B.

In the full version [38], we show that for the filtration n:=DRips((Xn,𝖽n)), dgm1(n) does not belong to O(|Xn|k) for any k. For this, we identify an interval of ΓXn×TXn on which the restriction of Mn:=H1(n;𝔽) is similar to M from Equation 7. Then, we prove claims analogous to Claim 15 through 18, and apply Lemma 21 Item ii.

It is known that, for m0, adding m integers has time complexity O(m) [37]. Hence, as a direct corollary of Theorems 13, 25, and 24, we obtain:

Corollary 26.

Let n,d0, d2, and IInt([n]d). For an arbitrary [n]d-module M, computing dgmM(I) via the Möbius inversion of the GRI of M requires at least Θ(2n) in time. In particular, M can arise as the homology of a simplicial filtration over [n]d, with the number of simplices being polynomial in n.

Proof.

Let M be the persistence module defined in the proof of Theorem 13 for d=2 and m=0. Let I:=U[n], as described immediately above Claim 18 in that proof. By Lemma 10, we have dgmM(I)=S[n](1)|S|=(1)n+2. This sum contains 2n+11 nonzero summands, requiring Θ(2n) time for computation.

5 Conclusion

We showed that the size of the GPD can be super-polynomial in the number of simplices in a given multi-parameter filtration, and such sizes can arise even from well-known constructions. Furthermore, we noted that the GRI can be “locally densely supported” (see Claim 18), which suggests that using the Möbius inversion of the GRI to compute the GPD can be intractable. These findings highlight the need to compute the GPD (or any invariant approximating it) directly, without relying on the GRI.

From a different perspective, developing an output-sensitive algorithm for computing the GPD might be a more practical approach, potentially extending or adapting ideas from [52]. Moreover, combining optimization techniques to address challenges in computing the GPD appears to be a promising research direction. In line with this, [20] proposes a method for “sparsifying” the GPD via gradient descent.

It also remains an interesting question whether special types of multi-parameter filtrations not explored in this work can also give rise to GPDs of super-polynomial size. Examples include multicover and barycentric (subdivision) bifiltrations [60].

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