Super-Polynomial Growth of the Generalized Persistence Diagram
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 with . 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 simplices, its persistence diagram contains at most points. This observation leads to the question: Given a -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 , where we compute the persistence diagram directly at the simplicial filtration level. If this were also the case for , 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 -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 invariantCopyright and License:
![[Uncaptioned image]](x1.png)
2012 ACM Subject Classification:
Mathematics of computing Algebraic topology ; Theory of computationAcknowledgements:
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 WangSeries and Publisher:

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 -parameter setting, topological features of datasets are indexed by the poset or a subposet of [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 () to the category of finite dimensional vector spaces over a field , 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 is the set of all intervals in (cf. Definitions 2 and 5). The cardinality of the domain is huge relative to the cardinality of even when ; 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 simplices, its persistence diagram contains at most points. This observation leads to the question: Given a -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 be an abstract simplicial complex, and let be the set of subcomplexes of ordered by inclusion. A monotone map such that there exists a with is called a (-parameter simplicial) filtration (of ). The number of simplices in the filtration is defined as the number of simplices in .
Definition 1 ([45]).
We call the filtration finite, if is finite, and in , every simplex is born at finitely many points of , i.e. there exist finitely many points s.t. for if and only if in for some . We call those points the birth indices of . We also say that is born at .
If is finite, then for each homology degree , the persistence module is finitely presentable (cf. Definition 3 and Remark 4). This guarantees that the -th GPD of any finite -parameter filtration is well-defined as an integer-valued function on a finite subset of intervals of (cf. Definition 5 and Remark 7), denoted by . By the size of we mean the cardinality of the support of , i.e. (cf. Definition 2). Since the notion of the GPD reduces to that of the persistence diagram when [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 such that for any homology degree , the size of the -th GPD of any finite simplicial filtration over is where stands for the number of simplicies in ?
Note that when , the answer to the question is yes, and can be taken to be , in which case we compute the persistence diagram directly at the simplicial filtration level [28]. If the answer is also yes when , 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 .
Our contributions
-
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 of finite -parameter simplicial filtrations where the sizes of their GPDs are not bounded by any polynomial in the number of simplices in .
-
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.
We find that computing the value of the GPD for a 2-parameter filtration containing simplices, for some , via the Möbius inversion of the GRI can result in the problem of summing 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 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 over (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 , making it natural to interpret 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, is a poset, regarded as the category whose objects are the elements of , and for any pair , there exists a unique morphism if and only if . All vector spaces in this paper are over a fixed field . Let denote the category of finite-dimensional vector spaces and linear maps over . A functor will be referred to as a persistence module over or simply a -module. A morphism between -modules is a natural transformation between the -modules. For any -modules and , their direct sum is defined pointwisely. A -module is trivial if for all , and we write . A nontrivial -module is indecomposable if the assumption for some -modules and implies that either or . By Krull-Remak-Schmidt-Azumaya’s theorem [6, 9], any -module is isomorphic to a direct sum of indecomposable -modules, and this decomposition is unique up to isomorphism and permutation of summands.
Definition 2.
An interval of is a subset such that:
-
(i)
is nonempty.
-
(ii)
If and , then .
-
(iii)
is connected, i.e. for any , there is a sequence of elements of with and comparable for .
By we denote the set of all intervals of .
For any in , the set is called a segment. The collection of all segments (resp. intervals) in will be denoted by (rep. ). It is not difficult to see that .
Given any , the interval module is the -module, with
(1) |
Every interval module is indecomposable [10, Proposition 2.2]. A -module is called interval-decomposable if it is isomorphic to a direct sum of interval modules. The barcode of an interval decomposable -module is defined as the multiset .
For , let (resp. ) denote the set of points such that (resp. ). Clearly, both and belong to .
Definition 3.
A -module is called finitely presentable if it is isomorphic to the cokernel of a morphism where and are finite multisets of elements of .
Remark 4.
It is well known that, for any finite -parameter simplicial filtration (Definition 1), the induced -module , for each , is finitely presentable. Namely, is isomorphic to the cokernel of a morphism where is a subset of the smallest finite -d grid in that contains all the birth indices of - and -simplices in . See, e.g. [45].
Generalized Rank invariant and Generalized Persistence Diagram.
Any -module admits both a limit and a colimit [48, Chapter V]: A limit of , denoted by , consists of a vector space together with a collection of linear maps such that
(2) |
A colimit of , denoted by , consists of a vector space together with a collection of linear maps such that
(3) |
Both and satisfy certain universal properties, making them unique up to isomorphism.
Let us assume that is connected. The connectedness of alongside the equalities given in Equations (2) and (3) imply that for any . This fact ensures that the canonical limit-to-colimit map given by for any is well-defined. The (generalized) rank of is defined to be222This construction was considered in the study of quiver representations [43]. , which is finite as for any . The rank of is a count of the “persistent features” in that span the entire indexing poset [40].
Now, we refine the rank of a -module, which is a single integer, into an integer-valued function. Options for the domain of the function include or the larger set .
Definition 5 ([22, 39]).
Let be a -module.
-
(i)
The generalized rank invariant (GRI) is the map given by where is the restriction of to .
-
(ii)
The generalized persistence diagram (GPD) of is defined as the function that satisfies the equality333This equality generalizes the fundamental lemma of persistent homology [29].
(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 by , we obtain the notions of the rank invariant and its signed barcode [12, 13, 18].
Theorem 6 (Existence and Uniqueness of the GPD).
Let be a -module.
-
(i)
If is finite, then the GPD of exists.
-
(ii)
If (), and is finitely presentable, then the GPD of exists. Furthermore, is finitely supported, i.e. there exist only finite many such that .
-
(iii)
In each of the previous two cases, the GPD is unique.
Proof.
Item i: If is finite, then 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 -module , assume that is the cokernel of a morphism where and are finite index sets. Let . Consider the finite full subposet , where is the canonical projection to the -th coordinate. Then, the GPD of is directly obtained from the GPD of the restriction , as follows.
We extend to by declaring that for all . Let be the map sending each to the maximal point in such that in . For any , let denote the set of the points for . Then, the GPD of , i.e. , is equal to
This implies that there exists a bijection between the supports of and .
We also remark that if is a finite poset, the condition given in Equation 4 holds if and only if
(5) |
where is the Möbius function of the poset ; 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 , denoted by , as the cardinality of its support. Likewise, the size of is defined as the cardinality of its support and is denoted by .
Remark 8.
In establishing results in later sections, we will utilize the following well-known concrete formulation for the limit of a -module (see, for instance, [39, Appendix E]):
Convention 9.
The limit of a -module is the pair described as:
where for each , the map is the canonical projection. Elements of are called sections of .
On 2-d grid lattices.
A join (a.k.a. least upper bound) of is an element such that (i) , for all , and (ii) for any , if for all , then . A meet (a.k.a. greatest lower bound) of is an element such that (i) for all , and (ii) for any , if for all , then . If a join and a meet of exist, then they are unique. Hence, whenever they exist, we refer to them as the join (denoted by ) and the meet (denoted by ), respectively. When consists of exactly two points and , we also use and instead of and , respectively. A lattice is a poset such that for any pair of elements, their meet and join exist. For any , let . By a finite -d grid lattice, we mean a poset isomorphic to the lattice for some .
Let and be any two points in a poset . We say that covers if and there is no such that . By , we denote the set of all points that cover .
Lemma 10 ([4, Theorem 5.3]).
Let be the Möbius function of the poset . Then, for all with ,
where denotes the cardinality of . Note that when and there is no nonempty such that , the sum above is empty, and thus . We also remark that represents the smallest interval in that contains all the intervals in .
A subposet (resp. ) is called a lower (resp. upper) fence of if is connected, and for any , the intersection (resp. ) is nonempty and connected [25, Definition 3.1].
Lemma 11 ([25, Proposition 3.2]).
Let and be a lower and an upper fence of a connected poset , respectively. Given any -module , we have
Let be any subset of . By and , we denote the collections of minimal and maximal elements of , respectively. A zigzag poset of points is where stands for either or .
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 with . There does not exist such that, for all finite filtrations over containing simplices, belongs to .
Let be an abstract simplicial complex and let . Let and be the group of -chains and that of -cycles of , respectively. Let be the -skeleton of .
To prove the statement, we construct a sequence of filtrations where contains simplices for some , but for any . By Remarks 4 and 7, it suffices to construct filtrations over the discrete posets .
Remark 14.
In [45], the size of a finite -parameter filtration of a simplicial complex is defined as the total number of birth indices across all . Even if we adopt this quantity as 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 .
Proof of Theorem 13 when .
We consider the cases of and separately.
Case 1 ().
Fix . Let be the simplicial complex on the vertex set that consists of the 1-simplices () and their faces. We define a filtration of over as follows. For , let (see Figure 1):
(6) |
Let . Then, we have:
(7) |
Let . Then, for every that covers , we have that
(8) |
In what follows, we use in place of . Now, we consider the following two intervals of (see Figure 1):
(9) |
By proving the following claims, we complete the proof for the case of .
Claim 15.
If is not a proper subset of , then .
Proof.
First, assume that there exists a point . Then, by the construction of , and thus by monotonicity of (Remark 8 Item i). Next, assume that . Since , it suffices to show . Again, since , by Lemma 11, it suffices to show that . By Equation (8), the diagram is given by
From this, it is not difficult to see that : For , let be the canonical projection. For any and for any , let . Then, Equations (2) and (8) imply the following pair of equalities for each :
and thus for . From this, we deduce that for all and . Therefore, for all and in turn . Since was arbitrary, we have .
Consider the following intervals of (see Figure 2):
(10) |
Claim 16.
Let such that . Then, .
Proof.
Since , there exists such that . Fix such . Since , by Lemma 11, we have the isomorphism . Observe that for every , . Hence, by Convention 9 and the definition of , we have that
Clearly, this tuple maps to via the limit-to-colimit map of over , followed by the isomorphism . Since is nonzero and (cf. Equation 7), we have that , as desired.
Claim 17.
for every .
Proof.
We have:
by Claim 16 | ||||
by Equation (4) | ||||
by Claim 15 and Remark 8 Item ii. |
For each nonempty , we define , which is an interval of .
Claim 18.
For each nonempty , we have that .
Proof.
Let . When , there exists such that . We already proved that . If , then
by Equation 5 | ||||
by Claim 15 | ||||
by Lemma 10 | ||||
by Claim 16, letting | ||||
by the binomial theorem |
as desired. The number of nonempty subsets is and each corresponds to the interval such that . Hence, In particular, there is no such that for , the number of simplices in the filtration , completing the proof.
Case 2 ().
Let be the smallest simplicial complex on the vertex set , containing all -simplices , and -simplices that are the underlying sets of the following oriented simplices (see Figure 3a):
For , let be the -dimensional subcomplex of , whose -simplices are exactly and (see Figure 3a).
We define the filtration () as (see Figure 3b):
(11) |
Note that, for each , the -chain in satisfies , i.e. is an -cycle. Moreover, , which is isomorphic to , is the 1-dimensional vector space generated by the homology class .
Let . We claim that is isomorphic to , given in Equation 7. Indeed,
and for each pair in , . Therefore, there is no such that for , the number of simplices in the filtration , which belongs to .
In order to prove Theorem 13 for the case where , 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 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 and is a pair of monotone maps satisfying iff for any and . Let be any function. For any , the pushforward of along is the function given by For any , the pullback of along is the function defined by . For any poset , let denote the Möbius inversion operator over . To say that the GPD of a -module exists is equivalent to stating that is well-defined and equals .
Lemma 20 ([33, Theorem 3.1]).
Let be a finite poset, be any poset, and be a Galois connection. Then,
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 be a finite poset, be a -module, and be an interval of . Then,
-
(i)
for every , we have where denotes the coarsest partition of into disjoint intervals of .
-
(ii)
Furthermore, if and are finite 2-d grid, then
Remark 22.
4.1 Sublevel-Rips and Sublevel-Čech Bifiltrations
For , the Vietoris-Rips complex of a metric space at scale is defined as
Now assume that , where is equipped with a metric , and . The Čech complex of in at scale is
where .
Lemma 23 ([32, Lemma VII]).
Let be the Euclidean space with the supremum metric . For any finite and any , we have .
Let be a function. For any and any (see e.g. [18]),
-
(i)
the sublevel-Rips complex at scale and threshold is
. The sublevel-Rips bifiltration of is the simplicial filtration over . -
(ii)
the sublevel-Čech complex at scale and threshold is
. The sublevel-Čech bifiltration of is the simplicial filtration over .
Theorem 24 (Super-polynomial GPD of Sublevel-Rips and Sublevel-Čech filtrations).
There does not exist such that for every metric space and every function , belongs to , where .
Given any set and , let . When , let be the projection .
Proof Sketch.
By Lemma 23, it suffices to show the statement when . Let . We construct an , which consists of points and inherits the metric from the supremum metric on . Our goal is to show that does not belong to for any , which then does not belong to for any . Let . Let (see Figure 4), where, for , is the subset of the plane in whose projected image onto is described below, and is the subset of the plane in whose projected image onto is described below. Let , for , , and . Note that . Let be
so that . In the full version [38], we show that for on (Figure 5), does not belong to for any . In particular, we identify an interval of on which the restriction of is isomorphic to from Equation (7), and then apply Lemma 21 Item ii.
4.2 Degree-Rips and Degree-Čech Bifiltrations
Let be a metric space. For and ,
-
(i)
the Degree-Rips complex at scale and degree [45], denoted , is the maximal subcomplex of whose vertices have degree at least in the 1-skeleton of . The Degree-Rips bifiltration of is the simplicial filtration over .
-
(ii)
The Degree-Čech complex at scale and degree [30], denoted , is the maximal subcomplex of whose vertices have degree at least in the 1-skeleton of . The Degree-Čech bifiltration of is the simplicial filtration over .
Theorem 25 (Super-polynomial GPD of Degree-Rips and Degree-Čech filtrations).
There does not exist such that for every finite metric space , belongs to , where .
Proof Sketch.
By Lemma 23, it suffices to show the statement when .
Let . We construct an , which consists of points and inherits the metric from the supremum metric on . Our goal is to show that does not belong to for any , which then does not belong to for any . Let . Let (see Figure 6), where, for , is the subset of the plane in whose projected image onto is described below. Let , , and . For , let .
Let
In the full version [38], we show that for the filtration , does not belong to for any . For this, we identify an interval of on which the restriction of is similar to from Equation 7. Then, we prove claims analogous to Claim 15 through 18, and apply Lemma 21 Item ii.
It is known that, for , adding integers has time complexity [37]. Hence, as a direct corollary of Theorems 13, 25, and 24, we obtain:
Corollary 26.
Let , , and . For an arbitrary -module , computing via the Möbius inversion of the GRI of requires at least in time. In particular, can arise as the homology of a simplicial filtration over , with the number of simplices being polynomial in .
Proof.
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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