Abstract 1 Introduction 2 Preliminaries 3 Geometric Dimension 4 Geometrically 2-Dimensional VASS 5 A Note on Geometrically 2-Dimensional 3-VASS 6 Geometrically 1-Dimensional and 0-Dimensional VASS 7 Concluding Remarks References

Reachability in Vector Addition System with States Parameterized by Geometric Dimension

Yangluo Zheng ORCID BASICS, Shanghai Jiao Tong University, China
Abstract

The geometric dimension of a vector addition system with states (VASS), emerged in Leroux and Schmitz (2019) and formalized by Fu, Yang, and Zheng (2024), quantifies the dimension of the vector space spanned by cycle effects in the system. This paper examines the VASS reachability problem through the lens of geometric dimension, revealing key differences from the traditional dimensional parameterization. Notably, we establish that the reachability problem for both geometrically 1-dimensional and 2-dimensional VASS is PSPACE-complete, achieved by extending the pumping technique initially proposed by Czerwiński et al. (2019).

Keywords and phrases:
Petri net, vector addition system, reachability, geometric dimension, pumping
Copyright and License:
[Uncaptioned image] © Yangluo Zheng; licensed under Creative Commons License CC-BY 4.0
2012 ACM Subject Classification:
Theory of computation Models of computation
; Theory of computation Logic and verification
Related Version:
Full Version: https://arxiv.org/abs/2412.14608
Acknowledgements:
The author would like to thank Wojciech Czerwiński, Łukasz Orlikowski and Qizhe Yang for a fruitful discussion which motivates Section 5. The author also thanks the members of BASICS for their interest. The efforts of anonymous reviewers are appreciated.
Funding:
The support from the National Science Foundation of China (62072299), Science and Technology Commission of Shanghai Municipality (24BC3200500) are acknowledged.
Editors:
Patricia Bouyer and Jaco van de Pol

1 Introduction

Vector addition systems with states (VASSes), equivalent to Petri nets, serve as a fundamental model for concurrency [10]. A VASS extends finite automata with integer counters that cannot be zero-tested but must be kept non-negative. Central to the algorithmic theory of VASS is the reachability problem: determining if a run exists from one configuration to another. Due to its generic nature, numerous practical problems can be modeled via the reachability problem [19]. After decades of study, the computational complexity of the VASS reachability problem was settled to be Ackermann-complete [15, 7, 14]. However, when fixing the dimension – the number of counters, a gap remains in complexity bounds. For d-dimensional VASS where d>2, reachability lies in 𝖥d [12], the dth level of the Grzegorczyk hierarchy of complexity classes [17] (for d=3 the upper bound has been improved to 2-𝖤𝖷𝖯𝖲𝖯𝖠𝖢𝖤 recently [8]), while 𝖥d-hardness is achieved with (2d+3)-dimensional VASS [5]. This gap is known to be closed only in low dimensions. PSPACE-completeness holds for 2-dimensional VASS under binary encoding [3, 6], and NL-completeness under unary encoding [9]. NP-completeness holds for 1-dimensional VASS under binary encoding [13], and again NL-completeness under unary encoding [9]. Dimension has traditionally served as the standard parameterization for reachability.

On the other hand, the structure of cycles was identified as a pivotal factor controlling the complexity of the VASS reachability problem [15]. The notion of geometric dimension, formalized in [12], measures the dimension of the cycle space – vector space spanned by all cycle effects. Insights from [15, 12] suggest that the 𝖥d upper bound of the famous KMLST algorithm applies to geometric dimension d, not only to dimension d. In this work we propose geometric dimension as an alternative parameterization for the VASS reachability problem. In theory the geometric dimension is closer to the nature of the reachability problem, as suggested by [15] and [12], and the cycles provides a rich structure for analysis. Recently a work on 3-dimensional VASS also made use of the geometric dimension [8]. Moreover, the structure of cycles played an important role in a study on continuous VASSes [1] where the authors extended the technique of linear path schemes to study the reachability problem. In practice, as the system parameters might not necessarily be independent of each other, fixing geometric dimension rather than dimension allows one to introduce certain types of interconnections in system parameters for free, which could possibly make the model more expressive. For example, a bounded counter can be simulated by a pair of complementary counters such that transitions increasing one of them must simultaneously decrease the other by the same amount. One easily verifies that these two counters contribute at most 1 to the geometric dimension.

Our contribution

In this paper, we study the reachability problem in VASSes with fixed geometric dimensions. As mentioned before, the 𝖥d upper bound in [12] directly applies to geometric dimension d3. Thus, the primary focus is on VASSes with geometric dimension 2. Our main contributions are the following theorems.

Theorem 1.1.

Reachability in VASS of geometric dimension 2 is PSPACE-complete under binary encoding.

Previous work [12] showing the semi-linearity of VASS reachability set in geometric dimension 2 utilized the technique of linear path schemes, which yielded merely an EXPSPACE upper bound (see [18] for an explicit statement). This is largely due to an exponential blow-up in the number of control states introduced by a dimension-reduction argument (see, e.g. [12, Lemma A.18]). In contrast, our proof relies on a pumping technique for 2-dimensional VASSes [6]. To apply this technique, we make use of the sign-reflecting projection proposed in [12], with some further properties developed in Subsection 4.1. Another tool called the support projection is introduced in Subsection 4.2. Combining these projection tools we establish a suitable coordinate system (4.6) within the 2-dimensinoal cycle space of the VASS. This enables us to apply the arguments in [6] to obtain the PSPACE upper bound. Together with the PSPACE-hardness inherited from 2-dimensinoal VASS [3, 11], we conclude PSPACE-completeness. We mention that the projection tools in this paper do not provide a straightforward reduction from d-dimensional VASS of geometric dimension 2 to 2-dimensinoal VASS. But we will show such a reduction exists for d=3 in Section 5.

Geometric dimensions lower than 2 are also studied in this paper:

Theorem 1.2.

Reachability in VASS of geometric dimension 1 is PSPACE-complete, and that of geometric dimension 0 is NP-complete under binary encoding.

Results in VASS of geometric dimension 1 and 0 are obtained by a re-examination of known results for VASS of dimension 1 and 2. These results show an interesting distinction in complexity of VASS reachability parameterized by dimension and by geometric dimension, as compared in Table 1.

Table 1: Complexity of VASS reachability parameterized by dimension and by geometric dimension.
dimension d geometric dimension d
d=0 NL-complete (folklore) NP-complete
d=1 NP-complete [13] PSPACE-complete
d=2 PSPACE-complete [3] PSPACE-complete
d=3 PSPACE-hard [3], in 2-EXPSPACE[8] PSPACE-hard [3], in TOWER=𝖥3 [12]
d4 no known distinctions

In addition to the above complexity results, we also give an efficient (polynomial time) algorithm computing the geometric dimension of a VASS in Subsection 3.1.

Organization

Section 2 fixes notations and definitions. Section 3 introduces the geometric dimension of a VASS and discusses some useful properties. Section 4 proves the PSPACE-completeness of geometrically 2-dimensional VASS. Section 5 gives a straightforward reduction from geometrically 2-dimensional 3-VASS to 2-VASS. Section 6 considers geometric dimensions lower than 2. Section 7 concludes the paper. Omitted proofs can be found in the full version.

2 Preliminaries

We use ,, to denote the set of natural numbers (non-negative integers), integers, and rational numbers respectively. Let mn be integers, we use [m,n] to denote the set {m,m+1,,n}. And we abbreviate [n] for [1,n]. For a d-dimensional vector 𝒗d, we write 𝒗(i) for its ith component, and we use its maximum norm 𝒗:=maxi[d]|𝒗(i)|. The order is extended component-wise to vectors: we write 𝒖𝒗 if 𝒖(i)𝒗(i) for all i[d]. Similarly we define the component-wise strict order < for vectors. We write 𝒖,𝒗=i[d]𝒖(i)𝒗(i) for their inner product. The support of a vector 𝒗 is supp(𝒗):={i[d],𝒗(i)0}. The support of a set S of vectors is supp(S):=𝒗Ssupp(𝒗). A vector 𝒗 is positive if 𝒗>𝟎, it is semi-positive if 𝒗𝟎 and 𝒗𝟎. For a string s=a1a2anΣ over an alphabet Σ, we write s[i..j] for the substring aiai+1aj of s.

2.1 Vector Addition System with States

Let d0 be an integer. A d-dimensional vector addition system with states (d-VASS) is a pair G=(Q,T) where Q is a finite set of states and TQ×d×Q is a finite set of transitions. Clearly a VASS can also be viewed as a directed graph with edges labelled by integer vectors. Given a word π=(p1,𝒂1,q1)(p2,𝒂2,q2)(pn,𝒂n,qn)T over transitions, we say that π is a path from p1 to qn if qi=pi+1 for all i=1,,n1. It is a cycle if we further have p1=qn. Such a path is usually presented in the following form:

π=p1t1q1t2q2t3tnqn (1)

where ti=(pi,𝒂i,qi). The effect of π is defined to be Δ(π):=i=1n𝒂i.

Size, traversal number and characteristic

The norm of a transition t=(p,𝒂,q) is defined by t:=𝒂. For a d-VASS G=(Q,T) we write T:=max{t:tT}. We shall mainly consider VASS under binary encoding, so the size of G is given by |G|:=|Q|+d|T|log(T+1)+1.

We define the traversal number of G to be the maximal number of distinct states that can be visited (traversed) by a path in G, denoted by ς(G). We remark that ς(G) is an upper bound of (i) the length of any simple path/cycle, and (ii) the number of connected components visited by any path. Note also the trivial fact ς(G)|Q|.

The characteristic of G, denoted by χ(G), is defined to be χ(G):=ς(G)T. So χ(G) upper bounds the norm of effect of any simple path/cycle in G.

Semantics of VASSes

Let G=(Q,T) be a d-VASS. A configuration c of G is a pair of a state pQ and a vector 𝒗d, written as c=p(𝒗). We will often confuse a configuration with its vector. So we shall write, for example, c for 𝒗, and c(i) for 𝒗(i). The semantics of G is defined as follows. For each transition t=(p,𝒂,q)T, the one-step transition relation 𝑡 relates all pairs of configurations of the form (p(𝒖),q(𝒗)) where 𝒖,𝒗d and 𝒗=𝒖+𝒂. Then for a word π=t1t2tnT, the relation 𝜋 is the composition 𝜋:=t1tn. So p(𝒖)𝜋q(𝒗) if and only if there are configurations p0(𝒖0),,pn(𝒖n)Q×d such that

p(𝒖)=p0(𝒖0)t1p1(𝒖1)t2tnpn(𝒖n)=q(𝒗). (2)

Also, when π=ϵ is the empty word, the relation ϵ is the identity relation over Q×d. Note that 𝜋 is non-empty only if π is a path. When p(𝒖)𝜋q(𝒗) we also say that π induces (or is) a run from p(𝒖) to q(𝒗), and we write src(π):=p(𝒖) and trg(π):=q(𝒗) for the source and target of π. We emphasize that all configurations on this run lie in d, and that they are uniquely determined by p(𝒖) and π. Finally, the reachability relation of G is defined to be :=πT𝜋.

Reachability problem

The general reachability problem in VASS is formulated as follows:

Reachability in Vector Addition System with States Input: A VASS G=(Q,T), two configurations p(𝒖),q(𝒗) of G. Question: Does p(𝒖)q(𝒗) hold in G?

It is a folklore that this problem can be reduced to the following one in polynomial time without affecting the dimension or the geometric dimension:

𝟎-Reachability in Vector Addition System with States Input: A G=(Q,T), two states p,qQ. Question: Does p(𝟎)q(𝟎) hold in G?

Thus, in this paper we shall mainly care about runs starting from 𝟎 and ending at 𝟎. Such a run is called a 𝟎-run in the following.

Reverse of VASS

For a VASS G=(Q,T) we define its reverse as the VASS Grev=(Q,Trev) where Trev:={(q,𝒂,p):(p,𝒂,q)T}. The reverse rev(π) of a path (or a run) π is defined naturally by reversing the order of transitions in π, switching the source and target states of those transitions, and negating their effects. We note that p(𝒖)𝜋q(𝒗) in G if and only if q(𝒗)rev(π)p(𝒖) in Grev.

3 Geometric Dimension

Definition 3.1.

Let G be a d-VASS. The cycle space of G is the vector space Cyc(G)d spanned by the effects of all cycles in G, that is: Cyc(G):=span{Δ(θ):θ is a cycle in G}.

The dimension of the cycle space of G is called the geometric dimension of G, denoted by gdim(G):=dim(Cyc(G)). We say G is geometrically k-dimensional if gdim(G)k.

It should be noticed that the cycle space of a VASS is indeed spanned by the effects of all simple cycles in it.

Lemma 3.2.

Let G be a d-VASS, then Cyc(G) equals to the vector space spanned by the effects of all simple cycles in G, that is, Cyc(G)=span{Δ(β):β is a simple cycle in G}.

Proof.

Just note that the effect of every cycle is a finite sum of effects of simple cycles.

A naive algorithm that computes the geometric dimension of a VASS by enumerating all simple cycles in it requires PSPACE. Indeed, we show here a more efficient algorithm which computes gdim(G) in polynomial time.

3.1 Computing Geometric Dimension

We present a stronger algorithm that given a VASS G as input, computes a basis for Cyc(G). Observe that every cycle lies within some maximal strongly connected component (SCC) of G. Once we have an algorithm that computes a basis for the cycle spaces of every SCC of G, a basis for Cyc(G) is just a maximal linearly independent subset of the union of these bases, which can be computed by Gaussian elimination in polynomial time. So the problem reduces to computing a basis for Cyc(G) in case G is strongly connected.

Fix a strongly connected d-VASS G=(Q,T). We introduce an operation called cycle shrinking. Let θ be a simple cycle in G that is not a self-loop and has the form

θ=p0t1p1t2tnpn=p0. (3)

First we define a “shift function” s:Qd as follows. If q=pk for some k[n], we set s(q):=Δ(θ[1..k])=Δ(t1)++Δ(tk); otherwise we set s(q):=𝟎. Note that s(p0)=s(pn)=Δ(θ). Let P={p1,,pn} be the set of states that occurs on θ. Now we define a new VASS G/θ=(Qθ,Tθ) that “shrinks” θ into a single states as follows.

  • Qθ:=(QP){θ}.

  • Let h:QQθ be defined as h(q)=θ if qP and h(q)=q otherwise. The transitions are given by Tθ:={(h(p),s(p)+𝒂s(q),h(q)):(p,𝒂,q)T}.

It should be clear that |Qθ|<|Q| as θ is not a self-loop, and that G/θ can be constructed in polynomial time given G and θ. Note that Tθ(2|Q|+1)T, so the size of G/θ is bounded by |G/θ||G|+d|T|log(2|Q|+1). Observe that h is a graph homomorphism from G onto G/θ. Thus G/θ is strongly connected as long as G is. Besides, we can show that G/θ preserves the cycle space of G.

Proposition 3.3.

Cyc(G/θ)=Cyc(G).

Now the algorithm for computing a basis of Cyc(G) where G is strongly connected should be clear. As listed in Algorithm 1, we repeatedly shrink a cycle in G until there remains only one state. Then its cycle space is the span of effects of self-loops in it. A basis of Cyc(G) can be computed using Gaussian elimination. Since a cycle shrinking reduces the number of states by at least one, after at most |Q| iterations we must stop with a single state remained. Note that the size of VASS is always bounded by |G|+d|Q||T|log(2|Q|+1)|G|2 in each iteration. Thus the algorithm runs in polynomial time.

Algorithm 1 CycleSpaceBasis.

3.2 Geometry of Reachability Sets and Runs

Given a VASS G=(Q,T) and a configuration p(𝒖)Q×d, we write ReachG(p(𝒖)) for all configurations that is reachable from p(𝒖): ReachG(p(𝒖)):={q(𝒗)Q×d:p(𝒖)q(𝒗)}. The next lemma shows that the “dimension” of any reachable set is bounded by gdim(G), in the sense that it is contained in a finite union of affine copies of Cyc(G). Here the sum of a vector 𝒗d and a set Sd is defined as 𝒗+S:={𝒗+𝒔:𝒔S}.

Lemma 3.4.

Let G=(Q,T) be a d-VASS, p(𝐮)Q×d be a configuration of G. Then

ReachG(p(𝒖))Q×𝒛d𝒛χ(G)𝒖+Cyc(G)+𝒛. (4)

In other words, for any configuration q(𝐯)Q×d with p(𝐮)q(𝐯), we have 𝐯=𝐮+𝐜+𝐳 for some 𝐜Cyc(G) and 𝐳d, where 𝐳χ(G).

Note that one may need exponentially many (roughly O(χ(G)d)) affine copies of Cyc(G) to cover ReachG(p(𝒖)). The next lemma shows that any fixed run from p(𝒖) is confined in, however, at most |Q| affine copies of Cyc(G).

Lemma 3.5.

Let G=(Q,T) be a d-VASS. For any run π in G with source p(𝐮)Q×d, there is a function fπ:Qd such that for every configuration q(𝐯) occurring on π, we have 𝐯𝐮+Cyc(G)+fπ(q). Moreover, fπ(q)χ(G) for every qQ.

These two lemmas follow easily from the fact that we can view a run as a simple path interleaved with cycles. Their proofs can be found in the full version of this paper.

4 Geometrically 2-Dimensional VASS

In this section we focus exclusively on geometrically 2-dimensional VASSes. We prove that reachability in geometrically 2-dimensional VASSes is PSPACE-complete. The lower bound is a simple corollary of [3, Lemma 20], so most effort will be devoted to the upper bound. Our proof is based on the pumping technique proposed in [6] for 2-VASSes, where they showed that every run in a 2-VASS is either thin – confined in some belt-shaped regions, or thick – enjoying good pumping properties that can be exploited to shrink long runs. We extend this technique and prove a similar thin-thick classification for runs in geometrically 2-dimensional VASSes. This will enable us to obtain the following exponential length bound for reachability witnesses.

Theorem 4.1.

For any 𝟎-run τ in a geometrically 2-dimensional d-VASS G, there is a 𝟎-run ρ in G with the same source and target states as τ and |ρ|χ(G)O(ς(G)d4).

From the above theorem the PSPACE-completeness follows immediately.

Theorem 4.2.

Reachability in geometrically 2-dimensional VASS is PSPACE-complete.

Proof.

The lower bound is inherited from the PSPACE-hardness of reachability in 2-VASS [3, Lemma 20]. For the upper bound, an algorithm only need to search a run of length up to χ(G)O(ς(G)d4) after reducing to the 𝟎-reachability problem, for which PSPACE is enough.

In order to establish the thin-thick classification of runs in a geometrically 2-dimensinoal VASS, we need to create a suitable coordinate system within its cycle space. This is achieved using the projection tools developed in Subsection 4.1 and Subsection 4.2. Depending on whether these tools can be applied, we classify geometrically 2-dimensinoal VASSes into degenerate ones (where projection tools are not applicable) and proper ones (where projection tools are applicable). Degenerate VASSes are easier to handle as they only admit thin runs, see Subsection 4.3. For proper VASSes in Subsection 4.4 we adapt the argument of [6] within the coordinate system created by the projection tools and establish the thin-thick classification. Finally we recall in Subsection 4.5 that both thin runs and thick runs can be shrunk to exponential length, thus Theorem 4.1 follows.

4.1 Sign Reflecting Projection

An orthant is one of the 2d regions in d split by the d axes. Formally, given a vector t{+1,1}d, the orthant Zt defined by t is the set Zt:={𝒖d:𝒖(i)t(i)0 for all i[d]}. The non-negative orthant 0d=Z(+1,+1,,+1) is a major concern in this paper.

Let I[d] be a subset of indices. For a vector 𝒖d, we define its projection onto indices in I as a function 𝒖|II given by (𝒖|I)(i)=𝒖(i) for all iI. We tacitly identify the function 𝒖|II as a vector in |I|. For a set of vectors Vd, we define V|I:={𝒗|I:𝒗V}. It should be clear that the projection of a vector space onto indices in I is again a vector space in |I|, and the projection of an orthant Zt onto I is an orthant in |I| defined by t|I.

Definition 4.3 ([12, Definition A.7]).

Let Pd be a vector space and Z be an orthant in d. A set of indices I[d] is called a sign-reflecting projection for P with respect to Z if for any 𝐯P, 𝐯|IZ|I implies 𝐯Z.

Sign-reflecting projection helps us project the vectors in a vector space to some of its components so that the pre-image of a certain orthant still belongs to one orthant. Moreover, we have that such a projection is one-to-one.

Lemma 4.4 ([12, Lemma A.8]).

Let Pd be a vector space and Z be an orthant in d. Let I[d] be a sign-reflecting projection for P w.r.t. Z. Then every vector 𝐯P is uniquely determined by 𝐯|I. In other words, for any 𝐯,𝐯P, 𝐯|I=𝐯|I implies 𝐯=𝐯.

We mainly care about sign-reflecting projections for a plane, i.e. a 2-dimensional subspace of d. In this case a good sign-reflecting projection is given by the following lemma.

Lemma 4.5 ([12, Theorem A.9]).

For d2, let Pd be a plane (i.e. a 2-dimensional subspace), and Z be an orthant in d such that PZ contains two linearly independent vectors. Then there is a sign-reflecting projection I for P w.r.t. Z such that |I|=2.

Intuitively 4.5 projects a plane onto an axis plane. The preimages of those two axes will play an important role in our work, as stated in the following lemma.

Lemma 4.6.

Let Pd be a plane. Let I={i1,i2}[d] be a sign-reflecting projection for P w.r.t. 0d. Suppose P=span{𝐯1,𝐯2} for linearly independent vectors 𝐯1,𝐯2d with norm N:=max{𝐯1,𝐯2}. Then there exists two non-zero vectors 𝐮1,𝐮2Pd such that 𝐮1(i2)=𝐮2(i1)=0 and 𝐮1(i1)=𝐮2(i2)>0 and that 𝐮1,𝐮22N2.

We call vectors 𝒖1,𝒖2 given by this lemma the canonical horizontal / vertical vector derived from 𝒗1,𝒗2 for P with respect to 0d. We remark that this notion can be generalized to orthants other than 0d. As any vector in P is uniquely represented as a linear combination of 𝒖1 and 𝒖2, we can obtain a bound for components of vectors in P in terms of their projections.

Lemma 4.7.

Let Pd be a plane. Let I={i1,i2}[d] be a sign-reflecting projection for P w.r.t. 0d. Suppose P=span{𝐯1,𝐯2} for linearly independent vectors 𝐯1,𝐯2d with norm N:=max{𝐯1,𝐯2}. For every 𝐰Pd and every isupp(P), we have

min{𝒘(i1),𝒘(i2)}2N2𝒘(i)2N2(𝒘(i1)+𝒘(i2)). (5)

4.2 Support Projection

4.7 gives bounds on the components in the support of the plane. So we would like the cycle space of a VASS G to have full support, i.e. supp(Cyc(G))=[d]. In this section we develop a technique called support projection to transform an arbitrary geometrically 2-dimensional VASS to one with such good property, without increasing its traversal number and the characteristic.

Let G=(Q,T) be a geometrically 2-dimensional d-VASS. Let S=supp(Cyc(G)) and S¯=[d]S. For vectors 𝒗S and 𝒗¯S¯, we define their composition 𝒗S𝒗¯d naturally by (𝒗S𝒗¯)(i)=𝒗(i) if iS and (𝒗S𝒗¯)(i)=𝒗¯(i) if iS¯. Since S is always clear from the context, we will simply write 𝒗𝒗¯ for this composition.

The support projection of G is the |S|-dimensional VASS GS=(QS,TS) where

QS :={(q,𝒗)Q×S¯:𝒗2χ(G)}, (6)
TS :={((p,𝒖),𝒂|S,(q,𝒗))QS×S×QS:(p,𝒂,q)T,𝒖+𝒂|S¯=𝒗}. (7)

A state of the form (q,𝒗) in GS is denoted q𝒗 for conciseness.

There is a huge expansion in the size of GS, as |QS|=|Q|(2χ(G))|S¯|. On the other hand, we can show that support projection does not increase traversal number and characteristic, and the projected VASS has full support as we expected.

Proposition 4.8.

ς(GS)ς(G), χ(GS)χ(G), and supp(Cyc(GS))=S.

Proof.

Let’s denote by ς(π) the number of distinct states in the path π. Consider any path πS in GS of the form πS=p0𝒗0t1Sp1𝒗𝟏t2StnSpn𝒗n where tiSTS. We define a corresponding path π in G as π:=p0t1p1t2tnpn where ti=(pi1,𝒂i,pi) and 𝒂i:=Δ(tiS)(𝒗i𝒗i1). Verify that ti is indeed a transition in T by the definition of TS. We claim that for any i,j[0,n], pi=pj implies 𝒗i=𝒗j, then it follows that ς(πS)=ς(π). Indeed, suppose pi=pj, then the sub path in π from pi to pj is a cycle with effect Δ(ti+1ti+2tj)Cyc(G). So 𝒗j=𝒗i+Δ(ti+1ti+2tj)|S¯=𝒗i, which proves the claim. As the choice of πS is arbitrary, for any path in GS, there exists a path in G visits the same number of distinct states. This proves ς(G)ς(GS).

Since it is clear that TST, we immediately have χ(GS)=ς(GS)TSς(G)T=χ(G).

Finally, we show supp(Cyc(GS))=S. Observe that it suffices to prove Cyc(G)|SCyc(GS). By 3.2, Cyc(G) is spanned by effects of all simple cycles in G. So consider any cycle θ in G of the form θ:=p0t1p1t2tnpn=p0 where t1,,tnT. We define vectors 𝒗0,,𝒗nS¯ by

𝒗0:=χ(G)𝟏,𝒗i+1:=𝒗i+Δ(ti+1)|S¯. (8)

Since θ is simple, we have nς(G). It follows that 𝟎𝒗i2χ(G)𝟏 for all i[0,n]. So pi𝒗i is a state in GS. Also note that 𝒗n=𝒗0+Δ(θ)|S¯=𝒗0. We can define a corresponding cycle θS:=p0𝒗0t1Sp1𝒗𝟏t2StnSpn𝒗n, where ti=(pi1𝒗i1,Δ(ti)|S,pi𝒗i). Verify that each ti is a transition in TS by definition. So θS is a cycle in GS. In particular, we have Δ(θ)|S=Δ(θS)Cyc(GS). As the choice of θ is arbitrary, we conclude that

Cyc(G)|S=(span{Δ(θ):θ is a simple cycle in G})|SCyc(GS), (9)

which is the desired result.

Using the support projection we can change our focus on VASSes with full support. We will prove the following lemma in the remaining of this section.

Lemma 4.9.

For any 𝟎-run τ in a geometrically 2-dimensional d-VASS G with the additional property that supp(Cyc(G))=[d], there is a 𝟎-run ρ in G with the same source and target states as τ and |ρ|χ(G)O(ς(G)d4).

Once 4.9 is established, Theorem 4.1 follows by plugging in the support projection of G. The rest is devoted to 4.9, so we can always assume that the VASS G has full support, i.e., supp(Cyc(G))=[d].

4.3 Degenerate VASS and Thin Runs

Depending on whether the cycle space of a VASS can be sign-reflectively projected onto an axes-plane with respect to the non-negative orthant 0d, we classify geometrically 2-dimensional VASSes into the following two classes.

Definition 4.10.

A geometrically 2-dimensional VASS G is proper if Cyc(G)0d contains two linearly independent vectors; it is degenerate otherwise.

In this subsection we focus on degenerate VASSes. We show that every run from 𝟎 in a degenerate VASS is thin in the sense of the following definitions. An illustration of thin runs can be found in 1(a).

Definition 4.11.

Let 𝐯d and W. The beam 𝐯,W is defined by

𝒗,W:={𝒖d:α0,𝒖α𝒗W}. (10)

The beam 𝐯,W is said to be an A-beam where A if 𝐯A and WA.

Definition 4.12.

Let G be a d-VASS. A run π in G is said to be A-thin if for every configuration p(𝐮) occurring in π, the vector 𝐮 belongs to some A-beam.

Indeed, we can relax the definition of beams by letting the direction 𝒗 range over all integer vectors in d. Let 𝒗d and W. The generalized beam 𝒗,W is defined by

𝒗,W:={𝒖d:α,𝒖α𝒗W}. (11)
Lemma 4.13.

For any 𝐯d and W, there exist 𝐯+d and 𝐯d such that 𝐯,W𝐯+,W𝐯,W and that 𝐯+,𝐯𝐯.

With 4.13, 4.12 is equivalent to stating that each configuration is located in some generalized A-beam. This makes it easier to argue if a run is thin, as demonstrated in the following lemma. We remark that the following result does not depend on whether the VASS has full support.

Lemma 4.14.

Let G be a geometrically 2-dimensional VASS that is degenerate. Then every 𝟎-run in G is χ(G)O(d)-thin.

Proof sketch.

A degenerate VASS G falls into one of the following 3 cases: (i) gdim(G)<2; (ii) gdim(G)=2 and Cyc(G)0d={𝟎}, or (iii) gdim(G)=2 and Cyc(G)0d=0𝒖 for some 𝒖d{𝟎}. We consider only the first case here. For the other cases we refer the readers to the full version of this paper.

Suppose gdim(G)<2, then Cyc(G)=span{𝒄} where 𝒄 is the effect of a (possibly empty) simple cycle in G. So 𝒄χ(G). By 3.4 every configuration q(𝒗) reachable from p(𝟎) satisfy 𝒗=α𝒄+𝒛 for some α and 𝒛χ(G). This shows that 𝒗𝒄,χ(G). As the choice of q(𝒗) is arbitrary, we deduce that every 𝟎-run in G is confined in the generalized beam 𝒄,χ(G), thus is χ(G)-thin.

4.4 Proper VASS and the Thin-Thick Classification

In this subsection we fix a geometrically 2-dimensional d-VASS G=(Q,T) that is proper, and assume that supp(Cyc(G))=[d]. So by 4.5, there exists i1i2[d] such that I:={i1,i2} is a sign-reflecting projection of Cyc(G) with respect to 0d. Moreover, let 𝒖1,𝒖2d be the canonical horizontal and vertical vectors given by 4.6. We have 𝒖1(i2)=0 and 𝒖2(i1)=0. Observe that we can assume 𝒖1,𝒖22χ(G)2, as they can be derived from effects of simple cycles in G.

4.4.1 Thick Runs

We will show that every 𝟎-run in G can be classified into thin runs and thick runs. Here we give the definition of thick runs.

Sequential cones

Recall that the cone generated by vectors 𝒗1,,𝒗kd is the set Cone{𝒗1,,𝒗k}:={j=1kaj𝒗j:a1,,ak0}. The definition of cones is enhanced in [6] where every prefix sum is also required to be non-negative:

Definition 4.15 (sequential cones).

Let 𝐯1,,𝐯𝐤d be a sequence of vectors, the sequential cone generated by these vectors is the following set:

SeqCone(𝒗1,,𝒗𝒌):={j=1kaj𝒗j:a1,,ak0,i.j=1iaj𝒗j𝟎}. (12)

In dimension 2 it was shown that a sequential cone is nothing but a cone generated by 2 vectors [6]. We generalize this result to sequential cones generated by vectors from the cycle space of a proper geometrically 2-dimensional VASS.

Lemma 4.16.

Let 𝐯1,,𝐯kd be vectors in Cyc(G). Then SeqCone(𝐯1,,𝐯k)=Cone{𝐱,𝐲} for some non-negative vectors 𝐱,𝐲 where each of them is either 𝐯j for some j[k], or is the canonical horizontal / vertical vector 𝐮1 or 𝐮2.

Indeed, this lemma reduces to [6, Lemma 2] easily by projecting the sequential cone onto coordinates in I.

Sequentially enabled cycles and thick runs
(a) Thin runs.
(b) Thick runs.
Figure 1: Illustration of thin runs and thick runs.

A path π is enabled at configuration c if there exists a configuration c such that c𝜋c is a legal run. Let S[d], we say π is S-enabled at c=p(𝒖) if there exists a vector 𝒛d with supp(𝒛)[d]S such that π is enabled at p(𝒖+𝒛). In other words, π is S-enabled if it is enabled when ignoring the coordinates outside S.

Definition 4.17.

Let A, and let π1,π2,π3,π4 be four cycles in G, we say these cycles are A-sequentially enabled in a run ρ in G if their lengths are at most A, and ρ can be factored into five parts ρ=ρ1ρ2ρ3ρ4ρ5 such that

  • Δ(π1)|I is semi-positive, and π1 is enabled at trg(ρ1). Moreover, both coordinates in I are bounded by A along ρ1.

  • If Δ(π1)|I is positive, then π2 is -enabled at trg(ρ2). Otherwise, π2 is S-enabled at trg(ρ2) for S=[d]supp(Δ(π1)), and, if Δ(π1)(ib)=0, then the ib-th coordinate is bounded by A along ρ2 where b=1,2.

  • SeqCone(Δ(π1),Δ(π2)) contains some positive vector. (We remark that this is possible only if G has full support.)

  • π3,π4 are -enabled at trg(ρ3),trg(ρ4) respectively.

Definition 4.18.

Let A. A 𝟎-run τ in G is A-thick if τ factors into τ=ρρ such that

  • some cycles π1,π2,π3,π4 in G are A-sequentially enabled in ρ,

  • some cycles π1,π2,π3,π4 in Grev are A-sequentially enabled in rev(ρ),

  • SeqCone(Δ(π1),Δ(π2),Δ(π3),Δ(π4))SeqCone(Δ(π1),Δ(π2),Δ(π3),Δ(π4)) is not trivial (i.e. it contains two linearly independent vectors).

An illustration of thick runs is given in 1(b).

4.4.2 Thin-Thick Classification

In spirit of [6], the following classification lemma is of great significance.

Lemma 4.19.

Let G be a proper geometrically 2-dimensional d-VASS with supp(Cyc(G))=[d], then there exists a number Aχ(G)O(ς(G)) such that every 𝟎-run in G is A-thick if it is not A-thin.

An important technical lemma in [6] is the “non-negative cycle lemma” [6, Lemma 3], which states that a run in 2-VASS from 𝟎 visiting a high configuration must contain a configuration enabling a semi-positive cycle. Here we need a similar lemma for geometrically 2-dimensional VASS.

Lemma 4.20.

There exists a polynomial P such that every run ρ in G from 𝟎 to 𝐯 with 𝐯P(χ(G))ς(G) contains a configuration enabling a cycle θ of length at most P(χ(G)) such that Δ(θ)|I is semi-positive.

We also need some simple geometric facts.

Lemma 4.21.

Let 𝐮,𝐯d. Let Xspan{𝐮,𝐯} be a convex set such that X0𝐮= and X0𝐯=. Then either XCone{𝐮,𝐯}= or XCone{𝐮,𝐯}.

Given a 2-vector 𝒗2, we define its right rotation 𝒗R:=(𝒗(2),𝒗(1)). For another vector 𝒖2, we write 𝒗𝒖 if 𝒖,𝒗R>0, and write 𝒗¯𝒖 if 𝒖,𝒗R0. We generalize this notation to the 2-dimensional subspace Cyc(G): given two vectors 𝒖,𝒗Cyc(G), we write 𝒗𝒖 if 𝒗|I𝒖|I, and 𝒗¯𝒖 if 𝒗|I¯𝒖|I.

Proposition 4.22.

Let 𝐮,𝐯Cyc(G) be such that 𝐮𝐯. Then for any 𝐰Cyc(G), 𝐰Cone{𝐮,𝐯} if and only if 𝐮¯𝐰¯𝐯.

The threshold 𝑨

Let P be the polynomial in 4.20. We define p to be the polynomial

p(x)=4x4(2x3(P(x)+(x+1)2+5)+2x)+x. (13)

Define A:=p(χ(G))ς(G)χ(G)O(ς(G)). Note that in particular we have

Ap(χ(G))ς(G)4χ(G)4(B+χ(G))+χ(G) (14)

where B:=2χ(G)3(P(χ(G))ς(G)+(χ(G)+1)2+5)+χ(G).

If a 𝟎-run is not A-thin, then we can find a configuration that lies out of all A-beams. The property that G has full support helps to further show that each component of this configuration is high.

Lemma 4.23.

Let ρ be a 𝟎-run in G that is not A-thin. Then ρ contains a configuration s(𝐰) where 𝐰 lies outside all A-beams, and such that 𝐰(i)B for all i[d].

Main Lemma
Lemma 4.24.

Let τ be a 𝟎-run in G that is not A-thin. Let s(𝐰) be the configuration on τ given by 4.23. Then τ can be factored into two parts τ=ρρ where trg(ρ)=s(𝐰)=src(ρ) such that

  • There are 4 cycles π1,π2,π3,π4 in G that are B-sequentially enabled in ρ, such that the set SeqCone(Δ(π1),Δ(π2),Δ(π3),Δ(π4)) contains a vector 𝒙 with 𝒙𝒘χ(G).

  • There are 4 cycles π1,π2,π3,π4 in Grev that are B-sequentially enabled in rev(ρ), such that SeqCone(Δ(π1),Δ(π2),Δ(π3),Δ(π4)) contains a vector 𝒙 with 𝒙𝒘χ(G).

We show that 4.19 follows immediately from 4.24.

Proof of 4.19.

If the run τ is not A-thin, then 4.24 applies. Regarding the definition of thick runs, we are only left to show SeqCone(Δ(π1),Δ(π2),Δ(π3),Δ(π4))SeqCone(Δ(π1),Δ(π2),Δ(π3),Δ(π4)) contains two linearly independent vectors. Define U:={𝒖Cyc(G):𝒖𝒘2χ(G)}. By 4.16, SeqCone(Δ(π1),Δ(π2),Δ(π3),Δ(π4)) is equal to some Cone{𝒗1,𝒗2} where 𝒗1,𝒗2Bχ(G)A. As 𝒘 lies out of all A-beams, we must have U0𝒗1= and U0𝒗2=. On the other hand, 4.24 guarantees that SeqCone(Δ(π1),Δ(π2),Δ(π3),Δ(π4))U. So by 4.21, we have USeqCone(Δ(π1),Δ(π2),Δ(π3),Δ(π4)). A similar argument shows also that USeqCone(Δ(π1),Δ(π2),Δ(π3),Δ(π4)). Finally, one easily verifies that U contains two linearly independent vectors.

Proof sketch of 4.24.

By symmetry we only need to prove the first item. Since ρ reaches the configuration s(𝒘) which is high enough, 4.20 shows that ρ contains a configuration c1 enabling a semi-positive cycle π1. For the second cycle, if π1 is positive, then we simply let π2:=π1. Otherwise, Δ(π1) is parallel to one of the canonical vectors 𝒖1 or 𝒖2. Say it is the latter case, so Δ(π1)(i1)=0. We need to find a cycle π2 with Δ(π2)(i1)>0. First observe that 4.20 allows us to assume c1P(χ(G))ς(G)+χ(G). As 𝒘(i1)B>ci(i1)+χ(G), the run from c1 to s(𝒘) must contain a cycle with positive effect in i1-th coordinate. We would like to choose this cycle to be π2, but its length may be unbounded. So we remove from it all sub-cycles whose effect is in parallel with Δ(π1). This makes π2 merely ([d]supp(Δ(π1)))-enabled, but that’s enough. Finally, we exhibit cycles π3,π4 so that the sequential cone contains some vector 𝒙 in the neighbor of 𝒘. We would like 𝒙 to be exactly 𝒘, but this may be impossible as 𝒘 might not even belong to Cyc(G). So we write 𝒘=𝒄+𝒛 for 𝒄Cyc(G) and 𝒛χ(G). The goal is now to contain 𝒙=𝒄 in the sequential cone. Consider all simple cycles enabled at some configuration on the run ρ after the source of π2. List them in the order they are enabled, and extract a subsequence π3,π4, such that Δ(π2)Δ(π3)Δ(π4). So the effects of them sweep the cycle space clockwise. Then we are able to argue, as in [6], that there must be some πi,πi+1 in this sequence such that Δ(πi)𝒄Δ(πi+1). We are done by choosing them as π3 and π4.

4.5 Exponential Bounds of Reachability Witnesses

4.19, together with 4.14, shows that every run in a geometrically 2-dimensional VASS G is either A-thin or A-thick for A=χ(G)O(dς(G)). For both cases we are able to exhibit a reachability witness of length exponential in A. The proofs are similar to that in [6]. So here we only state the results with basic sketches of the proof.

Lemma 4.25.

For any 𝟎-run τ that is A-thin in a d-VASS G where A2χ(G), there exists a 𝟎-run ρ with the same source and target states as τ such that |ρ|AO(d2).

Proof sketch.

Recall that A-thin runs are confined in A-beams of finitely many possibilities. These beams become eventually disjoint in the region far away from the origin. If an A-thin 𝟎-run τ without repeated configuration is long enough, it must contain a configuration c whose vector is far from origin. In this case we can find a sub-run π around c that stays within a unique A-beam. As τ is a 𝟎-run, π first goes “up” and then “down” in this beam. From this observation we will extract from π two cycles of opposite effects by Pigeonhole Principle. Deleting these cycles shortens the length of τ.

For thick runs, recall that they only occur in proper VASSes.

Lemma 4.26.

Let G be a proper geometrically 2-dimensional d-VASS with supp(Cyc(G))=[d]. For any 𝟎-run τ in G that is A-thick for some Aχ(G), there is a 𝟎-run ρ with the same source and target states as τ such that |ρ|AO(d3).

Proof sketch.

Consider a thick run τ. By definition, it can be decomposed into τ=ππ such that each of π and rev(π) contains four pumping cycles. For each path π and π, we remove any cycle whose effect can be realized by those pumping cycles to shorten their lengths. After that, we add some additional iterations to the pumping cycles to make the target configurations of π and π meet in a common point. This is possible as we required that the sequential cones generated by the pumping cycles have a non-trivial intersection. The bound on the number of iterations of cycles can be obtained using standard tools in integer programming, e.g. [4] and [16].

With these bounds we can finish the proof of our major goal 4.9.

Proof of 4.9.

By 4.14 and 4.19, any 𝟎-run τ in G is either A-thin or A-thick for some A=χ(G)O(dς(G)). We can apply 4.25 or 4.26 to transform τ into a run ρ with the same source and target so that |ρ|AO(d3)χ(G)O(d4ς(G)).

5 A Note on Geometrically 2-Dimensional 3-VASS

The projection techniques used in Section 4 did not provide a straightforward reduction from geometrically 2-dimensional d-VASS to 2-VASS. In this section we will show that such a reduction is indeed possible for d=3. We shall also mention some issues one will face when trying to generalize this reduction for d>3.

In this section we care about the unary-encoding size of VASSes. Let G=(Q,T) be a d-VASS, its unary-encoding size is defined as |G|1:=|Q|+d|T|T+1. The reduction is stated as the following lemma, from which one immediately gets the PSPACE upper bound for reachability in geometrically 2-dimensinoal 3-VASS even under binary encoding.

Lemma 5.1.

Given a geometrically 2-dimensinoal 3-VASS G with 2 states p,q, one can compute in time polynomial in |G|1 a 2-VASS G¯ with 2 states p¯,q¯ satisfying |G¯|1|G|1O(1), such that the following statements are equivalent:

  • there exists a run from p(𝟎) to q(𝟎) of length in G;

  • there exists a run from p¯(𝟎) to q¯(𝟎) of length 3 in G¯.

Corollary 5.2.

Reachability in geometrically 2-dimensinoal 3-VASS is in PSPACE.

Proof.

By [2, Theorem 3.2], in a 2-VASS G¯, length of the shortest reachability witness is bounded by |G¯|1O(1). Together with 5.1 this shows that length of the shortest reachability witness in a geometrically 2-dimensinoal 3-VASS G is also bounded by |G|1O(1), which is exponential in the binary-encoding size |G|. Polynomial space is enough for enumerating every run of length at most |G|1O(1).

The following is devoted to 5.1. Fix a geometrically 2-dimensinoal 3-VASS G=(Q,T) with 2 states p,q. We can assume that gdim(G)=2, by adding isolated loops to G when necessary. Then there exists a normal vector 𝒏3 such that Cyc(G)={𝒄3:𝒏,𝒄=0}. As Cyc(G) is spanned by effects of two simple cycles, whose norms are bounded by χ(G)<|G|1O(1), applying Cramer’s rule we can assume 𝒏|G|1O(1). Let h, we define the set Ch:={𝒖3:𝒏,𝒖=h} as an affine copy of Cyc(G). The following proposition shows that any run from p(𝟎) moves within a limited number of Ch’s.

Proposition 5.3.

There exists a number B|G|1O(1) such that for any configuration s(𝐰) reachable from p(𝟎), 𝐰Ch for some h with |h|B.

Proof.

By 3.4 we have 𝒘=𝒄+𝒛 for some 𝒄Cyc(G) and 𝒛χ(G). So 𝒘Ch for h=𝒏,𝒘. Note that |h|=|𝒏,𝒘|=|𝒏,𝒄+𝒏,𝒛|=|𝒏,𝒛|. We can pick B:=3χ(G)𝒏|G|1O(1).

Proof of 5.1.

Let B be the number given in 5.3. We consider 2 cases according to the signs of components in 𝒏.

Case 1. 𝒏𝟎 (or symmetrically 𝒏𝟎).

By 5.3, every configuration s(𝒘) reachable from p(𝟎) satisfies |𝒏,𝒘|B. We claim that 𝒘|supp(𝒏)B. Otherwise, as 𝒏 is an integer vector, 𝒏(i)1 for all isupp(𝒏), then 𝒘|supp(𝒏)>B implies |𝒏,𝒘|>B. Then we can encode all possible values of the coordinates in supp(𝒏) using the states of the VASS and thus reduce its dimension. As 𝒏𝟎, supp(𝒏) contains at least one coordinate, so the resulting VASS is at most 2-dimensional. And the size is blown up by a factor of at most (B+1)2|G|1O(1). Note that to validate the factor 3 in the amplification of lengths of runs as in the statements of 5.1, we also need to add two dummy transitions after each transition in the original VASS.

Case 2. 𝒏 contains both positive and negative components.

By negating 𝒏 we can assume there is only one negative component in 𝒏. Assume w.l.o.g. 𝒏(3)<0 and 𝒏(1),𝒏(2)0. Let 𝒏=:(a,b,c) for some a,b,c, then we have Ch={(x,y,z)3:ax+by=cz+h}. We construct a 2-VASS G¯ that projects G onto the first 2 coordinates. Let G¯=(Q¯,T¯) be defined as follows. The state set Q¯ contains {sh:sQ,h,|h|B}{sh¯:sQ,h,|h|B}. Intuitively a configuration sh(x,y) in G¯ represents the configuration s(x,y,z) in G such that (x,y,z)Ch, and the barred version marks an “unchecked” state, where z=(ax+byh)/c could be negative. So for each transition t=(r,𝒂,s) of G, we add the transitions th=(rh,𝒂|{1,2},sh¯) to G¯ for all |h|,|h|B and h=h+𝒏,𝒂. Indeed, if r(𝒖)𝑡s(𝒗) in G and 𝒖Ch, 𝒗Ch, then h=𝒏,𝒗=𝒏,𝒖+Δ(t)=h+𝒏,Δ(t). This justifies the correctness of the transitions we added to G¯.

Next, we add to G¯ transitions that checks, at each state sh¯, if the configuration sh¯(x,y) represents a legal configuration s(x,y,z) in G, where (x,y,z)Ch, so cz=ax+byh. As c>0, this is equivalent to checking if ax+byh0. Recall that a,b0, one can verify that for (x,y)𝟎, we have ax+byh0 if and only if (x,y)𝒎 for some 𝒎h, where h is the set of minimal solutions given by

h:={{(0,0)}if h0;{(0,h/b)}if a=0,b>0, and h>0;{(h/a,0)}if a>0,b=0, and h>0;{(x,(hax)/b):x=0,1,,h/a}if a>0,b>0, and h>0. (15)

Now for each number h with |h|B, we add the path sh¯𝒎𝒎sh to G¯ for each 𝒎h, where is an arbitrary but unique state added to G¯. One can easily verify that sh¯(x,y)sh(x,y) if and only if z=(ax+byh)/c0. Therefore, p(𝟎)𝜋q(𝟎) in G for a path π of length if and only if p0(𝟎)π¯q0(𝟎) in G¯ for a path π¯ of length 3. Also note that |h|B|G|1O(1), so we have |G¯|1|G|1O(1). This completes the proof.

Finally, we mention some issues when trying to generalize for higher dimensions.

  1. 1.

    If the dimension d is not fixed as a parameter, one can easily construct an acyclic (geometrically 0-dimensinoal) VASS so that each point in the Hamming cube {0,1}d is reachable from 𝟎. Then the reduced VASS must handle an exponential number of affine copies of Cyc(G), which suggests an exponential blow-up in size.

  2. 2.

    For d=3 the reduced 2-VASS only need to check inequalities of the form 𝒂,𝒙b for 𝒂𝟎. For higher dimensions we no longer have the assumption 𝒂𝟎. And we have no idea how to make a VASS check inequalities such as xy3.

6 Geometrically 1-Dimensional and 0-Dimensional VASS

We have shown that the reachability problem in geometrically 2-dimensional VASS is PSPACE-complete, which is same as the complexity of reachability in 2-VASS. The situation becomes different for lower geometric dimensions. In this section we study the reachability problems for geometrically 1-dimensional and 0-dimensional VASSes. Indeed, these results turn out to be just rephrase of existing results for 2-VASS and 1-VASS.

Theorem 6.1.

Reachability in geometrically 1-dimensional VASS is PSPACE-complete.

Proof.

The upper bound is implied by Theorem 4.2. For the lower bound, we refer the readers to the reduction from bounded one-counter automata to 2-VASS [3, Lemma 20]. We remark that as the reduced VASS uses 2 counters to simulate a bounded counter, every transition have effect of the form (z,z) for some z. Thus, the cycle space of the reduced VASS is contained in span{(1,1)}. So this reduction indeed establishes the PSPACE-hardness of reachability in geometrically 1-dimensional VASS.

Theorem 6.2.

Reachability in geometrically 0-dimensional VASS is NP-complete.

Proof.

We first show the upper bound. Let G=(Q,T) be a geometrically 0-dimensional VASS. Then any cycle in G has effect 𝟎. So for any run τ in G we can safely remove all cycles from τ and obtain a run τ¯ whose length is bounded by |Q|. Now a nondeterministic algorithm can decide reachability in G by simply guessing a run of length at most |Q|.

For the lower bound, we recall the folklore reduction from Subset-Sum to the reachability problem in 1-VASS. Given an instance S={a1,,an},s of Subset-Sum, where S and the goal is to find a subset of S whose sum is s, we construct a 1-VASS G=(Q,T) as follows. The states are Q:={q0,,qn}. For each i=1,,n we add two transitions qi1aiqi and qi10qi. One can easily observe that there exists a subset of S with sum s if and only if q0(0)qn(s) in G. Note that there are no cycles in G, thus G is indeed geometrically 0-dimensional.

7 Concluding Remarks

In this paper, we have studied the reachability problem in vector addition systems with states (VASS) parameterized by geometric dimension. We introduced an efficient algorithm for computing the geometric dimension of a VASS and demonstrated some simple geometrical properties of reachable sets and runs. The primary focus is on VASS with low geometric dimensions, particularly those that are geometrically 2-dimensional. By generalizing existing pumping techniques for 2-VASS, we have shown that the reachability problem in geometrically 2-dimensional VASS is PSPACE-complete. The techniques of sign-reflecting projection and support projection also provide insights into how results for d-VASS can be adapted to geometrically d-dimensional VASS.

The results for geometrically 1- and 0-dimensional VASS are both interesting and technically straightforward. By re-examining existing results, we have shown that reachability in geometrically 1-dimensional VASS is PSPACE-complete, while in geometrically 0-dimensional VASS it is NP-complete. It is worth noting that reachability is known to be NP-complete in 1-VASS and NL-complete in 0-VASS. Our findings highlight a distinction in expressiveness and computational power between geometrically d-dimensional VASS and d-VASS. We suggest that comparing these two models could be a possible direction for future research.

In this paper our main focus is on binary encoded VASSes of low geometric dimensions. The situation would become different if unary encoding is considered. It is known that in fixed-dimensional settings the problem is NL-complete for dimensions 0, 1, and 2 [2]. However, if only the geometric dimension is fixed, we note that logarithmic space is not enough to store a single configuration containing d counters (recall that the size of G=(Q,T) under unary encoding is |G|1:=|Q|+d|T|T+1). The complexity of reachability in low geometric dimensions under unary encoding is left for future work.

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