Reachability in Vector Addition System with States Parameterized by Geometric Dimension
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, pumping2012 ACM Subject Classification:
Theory of computation Models of computation ; Theory of computation Logic and verificationAcknowledgements:
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 PolSeries and Publisher:
Leibniz International Proceedings in Informatics, Schloss Dagstuhl – Leibniz-Zentrum für Informatik
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 -dimensional VASS where , reachability lies in [12], the th level of the Grzegorczyk hierarchy of complexity classes [17] (for the upper bound has been improved to 2- recently [8]), while -hardness is achieved with -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 upper bound of the famous KMLST algorithm applies to geometric dimension , not only to dimension . 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 to the geometric dimension.
Our contribution
In this paper, we study the reachability problem in VASSes with fixed geometric dimensions. As mentioned before, the upper bound in [12] directly applies to geometric dimension . Thus, the primary focus is on VASSes with geometric dimension . 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 -dimensional VASS of geometric dimension to 2-dimensinoal VASS. But we will show such a reduction exists for 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.
| dimension | geometric dimension | |
| NL-complete (folklore) | NP-complete | |
| NP-complete [13] | PSPACE-complete | |
| PSPACE-complete [3] | PSPACE-complete | |
| PSPACE-hard [3], in 2-EXPSPACE[8] | PSPACE-hard [3], in [12] | |
| 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 be integers, we use to denote the set . And we abbreviate for . For a -dimensional vector , we write for its th component, and we use its maximum norm . The order is extended component-wise to vectors: we write if for all . Similarly we define the component-wise strict order for vectors. We write for their inner product. The support of a vector is . The support of a set of vectors is . A vector is positive if , it is semi-positive if and . For a string over an alphabet , we write for the substring of .
2.1 Vector Addition System with States
Let be an integer. A -dimensional vector addition system with states (-VASS) is a pair where is a finite set of states and 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 over transitions, we say that is a path from to if for all . It is a cycle if we further have . Such a path is usually presented in the following form:
| (1) |
where . The effect of is defined to be .
Size, traversal number and characteristic
The norm of a transition is defined by . For a -VASS we write . We shall mainly consider VASS under binary encoding, so the size of is given by .
We define the traversal number of to be the maximal number of distinct states that can be visited (traversed) by a path in , denoted by . We remark that 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 .
The characteristic of , denoted by , is defined to be . So upper bounds the norm of effect of any simple path/cycle in .
Semantics of VASSes
Let be a -VASS. A configuration of is a pair of a state and a vector , written as . We will often confuse a configuration with its vector. So we shall write, for example, for , and for . The semantics of is defined as follows. For each transition , the one-step transition relation relates all pairs of configurations of the form where and . Then for a word , the relation is the composition . So if and only if there are configurations such that
| (2) |
Also, when is the empty word, the relation is the identity relation over . Note that is non-empty only if is a path. When we also say that induces (or is) a run from to , and we write and for the source and target of . We emphasize that all configurations on this run lie in , and that they are uniquely determined by and . Finally, the reachability relation of is defined to be .
Reachability problem
The general reachability problem in VASS is formulated as follows:
Reachability in Vector Addition System with States Input: A VASS , two configurations of . Question: Does hold in ?
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:
-Reachability in Vector Addition System with States Input: A , two states . Question: Does hold in ?
Thus, in this paper we shall mainly care about runs starting from and ending at . Such a run is called a -run in the following.
Reverse of VASS
For a VASS we define its reverse as the VASS where . The reverse of a path (or a run) is defined naturally by reversing the order of transitions in , switching the source and target states of those transitions, and negating their effects. We note that in if and only if in .
3 Geometric Dimension
Definition 3.1.
Let be a -VASS. The cycle space of is the vector space spanned by the effects of all cycles in , that is: .
The dimension of the cycle space of is called the geometric dimension of , denoted by . We say is geometrically -dimensional if .
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 be a -VASS, then equals to the vector space spanned by the effects of all simple cycles in , that is, .
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 in polynomial time.
3.1 Computing Geometric Dimension
We present a stronger algorithm that given a VASS as input, computes a basis for . Observe that every cycle lies within some maximal strongly connected component (SCC) of . Once we have an algorithm that computes a basis for the cycle spaces of every SCC of , a basis for 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 in case is strongly connected.
Fix a strongly connected -VASS . We introduce an operation called cycle shrinking. Let be a simple cycle in that is not a self-loop and has the form
| (3) |
First we define a “shift function” as follows. If for some , we set ; otherwise we set . Note that . Let be the set of states that occurs on . Now we define a new VASS that “shrinks” into a single states as follows.
-
.
-
Let be defined as if and otherwise. The transitions are given by .
It should be clear that as is not a self-loop, and that can be constructed in polynomial time given and . Note that , so the size of is bounded by . Observe that is a graph homomorphism from onto . Thus is strongly connected as long as is. Besides, we can show that preserves the cycle space of .
Proposition 3.3.
.
Now the algorithm for computing a basis of where is strongly connected should be clear. As listed in Algorithm 1, we repeatedly shrink a cycle in until there remains only one state. Then its cycle space is the span of effects of self-loops in it. A basis of can be computed using Gaussian elimination. Since a cycle shrinking reduces the number of states by at least one, after at most iterations we must stop with a single state remained. Note that the size of VASS is always bounded by in each iteration. Thus the algorithm runs in polynomial time.
3.2 Geometry of Reachability Sets and Runs
Given a VASS and a configuration , we write for all configurations that is reachable from : . The next lemma shows that the “dimension” of any reachable set is bounded by , in the sense that it is contained in a finite union of affine copies of . Here the sum of a vector and a set is defined as .
Lemma 3.4.
Let be a -VASS, be a configuration of . Then
| (4) |
In other words, for any configuration with , we have for some and , where .
Note that one may need exponentially many (roughly ) affine copies of to cover . The next lemma shows that any fixed run from is confined in, however, at most affine copies of .
Lemma 3.5.
Let be a -VASS. For any run in with source , there is a function such that for every configuration occurring on , we have . Moreover, for every .
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 -run in a geometrically 2-dimensional -VASS , there is a -run in with the same source and target states as and .
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 after reducing to the -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 regions in split by the axes. Formally, given a vector , the orthant defined by is the set . The non-negative orthant is a major concern in this paper.
Let be a subset of indices. For a vector , we define its projection onto indices in as a function given by . We tacitly identify the function as a vector in . For a set of vectors , we define . It should be clear that the projection of a vector space onto indices in is again a vector space in , and the projection of an orthant onto is an orthant in defined by .
Definition 4.3 ([12, Definition A.7]).
Let be a vector space and be an orthant in . A set of indices is called a sign-reflecting projection for with respect to if for any , implies .
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 be a vector space and be an orthant in . Let be a sign-reflecting projection for w.r.t. . Then every vector is uniquely determined by . In other words, for any , implies .
We mainly care about sign-reflecting projections for a plane, i.e. a -dimensional subspace of . In this case a good sign-reflecting projection is given by the following lemma.
Lemma 4.5 ([12, Theorem A.9]).
For , let be a plane (i.e. a -dimensional subspace), and be an orthant in such that contains two linearly independent vectors. Then there is a sign-reflecting projection for w.r.t. such that .
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 be a plane. Let be a sign-reflecting projection for w.r.t. . Suppose for linearly independent vectors with norm . Then there exists two non-zero vectors such that and and that .
We call vectors given by this lemma the canonical horizontal / vertical vector derived from for with respect to . We remark that this notion can be generalized to orthants other than . As any vector in is uniquely represented as a linear combination of and , we can obtain a bound for components of vectors in in terms of their projections.
Lemma 4.7.
Let be a plane. Let be a sign-reflecting projection for w.r.t. . Suppose for linearly independent vectors with norm . For every and every , we have
| (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 to have full support, i.e. . 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 be a geometrically 2-dimensional -VASS. Let and . For vectors and , we define their composition naturally by if and if . Since is always clear from the context, we will simply write for this composition.
The support projection of is the -dimensional VASS where
| (6) | ||||
| (7) |
A state of the form in is denoted for conciseness.
There is a huge expansion in the size of , as . 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.
, , and .
Proof.
Let’s denote by the number of distinct states in the path . Consider any path in of the form where . We define a corresponding path in as where and . Verify that is indeed a transition in by the definition of . We claim that for any , implies , then it follows that . Indeed, suppose , then the sub path in from to is a cycle with effect . So , which proves the claim. As the choice of is arbitrary, for any path in , there exists a path in visits the same number of distinct states. This proves .
Since it is clear that , we immediately have .
Finally, we show . Observe that it suffices to prove . By 3.2, is spanned by effects of all simple cycles in . So consider any cycle in of the form where . We define vectors by
| (8) |
Since is simple, we have . It follows that for all . So is a state in . Also note that . We can define a corresponding cycle , where . Verify that each is a transition in by definition. So is a cycle in . In particular, we have . As the choice of is arbitrary, we conclude that
| (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 -run in a geometrically 2-dimensional -VASS with the additional property that , there is a -run in with the same source and target states as and .
Once 4.9 is established, Theorem 4.1 follows by plugging in the support projection of . The rest is devoted to 4.9, so we can always assume that the VASS has full support, i.e., .
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 , we classify geometrically 2-dimensional VASSes into the following two classes.
Definition 4.10.
A geometrically 2-dimensional VASS is proper if contains two linearly independent vectors; it is degenerate otherwise.
In this subsection we focus on degenerate VASSes. We show that every run from 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 and . The beam is defined by
| (10) |
The beam is said to be an -beam where if and .
Definition 4.12.
Let be a -VASS. A run in is said to be -thin if for every configuration occurring in , the vector belongs to some -beam.
Indeed, we can relax the definition of beams by letting the direction range over all integer vectors in . Let and . The generalized beam is defined by
| (11) |
Lemma 4.13.
For any and , there exist and such that and that .
With 4.13, 4.12 is equivalent to stating that each configuration is located in some generalized -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 be a geometrically 2-dimensional VASS that is degenerate. Then every -run in is -thin.
Proof sketch.
A degenerate VASS falls into one of the following 3 cases: (i) ; (ii) and , or (iii) and for some . We consider only the first case here. For the other cases we refer the readers to the full version of this paper.
Suppose , then where is the effect of a (possibly empty) simple cycle in . So . By 3.4 every configuration reachable from satisfy for some and . This shows that . As the choice of is arbitrary, we deduce that every -run in is confined in the generalized beam , thus is -thin.
4.4 Proper VASS and the Thin-Thick Classification
In this subsection we fix a geometrically -dimensional -VASS that is proper, and assume that . So by 4.5, there exists such that is a sign-reflecting projection of with respect to . Moreover, let be the canonical horizontal and vertical vectors given by 4.6. We have and . Observe that we can assume , as they can be derived from effects of simple cycles in .
4.4.1 Thick Runs
We will show that every -run in 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 is the set . 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 be a sequence of vectors, the sequential cone generated by these vectors is the following set:
| (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 be vectors in . Then for some non-negative vectors where each of them is either for some , or is the canonical horizontal / vertical vector or .
Indeed, this lemma reduces to [6, Lemma 2] easily by projecting the sequential cone onto coordinates in .
Sequentially enabled cycles and thick runs
A path is enabled at configuration if there exists a configuration such that is a legal run. Let , we say is -enabled at if there exists a vector with such that is enabled at . In other words, is -enabled if it is enabled when ignoring the coordinates outside .
Definition 4.17.
Let , and let be four cycles in , we say these cycles are -sequentially enabled in a run in if their lengths are at most , and can be factored into five parts such that
-
is semi-positive, and is enabled at . Moreover, both coordinates in are bounded by along .
-
If is positive, then is -enabled at . Otherwise, is -enabled at for , and, if , then the -th coordinate is bounded by along where .
-
contains some positive vector. (We remark that this is possible only if has full support.)
-
are -enabled at respectively.
Definition 4.18.
Let . A -run in is -thick if factors into such that
-
some cycles in are -sequentially enabled in ,
-
some cycles in are -sequentially enabled in ,
-
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 be a proper geometrically -dimensional -VASS with , then there exists a number such that every -run in is -thick if it is not -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 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 such that every run in from to with contains a configuration enabling a cycle of length at most such that is semi-positive.
We also need some simple geometric facts.
Lemma 4.21.
Let . Let be a convex set such that and . Then either or .
Given a 2-vector , we define its right rotation . For another vector , we write if , and write if . We generalize this notation to the 2-dimensional subspace : given two vectors , we write if , and if .
Proposition 4.22.
Let be such that . Then for any , if and only if .
The threshold
Let be the polynomial in 4.20. We define to be the polynomial
| (13) |
Define . Note that in particular we have
| (14) |
where .
If a -run is not -thin, then we can find a configuration that lies out of all -beams. The property that has full support helps to further show that each component of this configuration is high.
Lemma 4.23.
Let be a -run in that is not -thin. Then contains a configuration where lies outside all -beams, and such that for all .
Main Lemma
Lemma 4.24.
Let be a -run in that is not -thin. Let be the configuration on given by 4.23. Then can be factored into two parts where such that
-
There are 4 cycles in that are -sequentially enabled in , such that the set contains a vector with .
-
There are 4 cycles in that are -sequentially enabled in , such that contains a vector with .
Proof of 4.19.
If the run is not -thin, then 4.24 applies. Regarding the definition of thick runs, we are only left to show contains two linearly independent vectors. Define . By 4.16, is equal to some where . As lies out of all -beams, we must have and . On the other hand, 4.24 guarantees that . So by 4.21, we have . A similar argument shows also that . Finally, one easily verifies that contains two linearly independent vectors.
Proof sketch of 4.24.
By symmetry we only need to prove the first item. Since reaches the configuration which is high enough, 4.20 shows that contains a configuration enabling a semi-positive cycle . For the second cycle, if is positive, then we simply let . Otherwise, is parallel to one of the canonical vectors or . Say it is the latter case, so . We need to find a cycle with . First observe that 4.20 allows us to assume . As , the run from to must contain a cycle with positive effect in -th coordinate. We would like to choose this cycle to be , but its length may be unbounded. So we remove from it all sub-cycles whose effect is in parallel with . This makes merely -enabled, but that’s enough. Finally, we exhibit cycles so that the sequential cone contains some vector in the neighbor of . We would like to be exactly , but this may be impossible as might not even belong to . So we write for and . The goal is now to contain in the sequential cone. Consider all simple cycles enabled at some configuration on the run after the source of . List them in the order they are enabled, and extract a subsequence such that . So the effects of them sweep the cycle space clockwise. Then we are able to argue, as in [6], that there must be some in this sequence such that . We are done by choosing them as and .
4.5 Exponential Bounds of Reachability Witnesses
4.19, together with 4.14, shows that every run in a geometrically 2-dimensional VASS is either -thin or -thick for . For both cases we are able to exhibit a reachability witness of length exponential in . 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 -run that is -thin in a -VASS where , there exists a -run with the same source and target states as such that .
Proof sketch.
Recall that -thin runs are confined in -beams of finitely many possibilities. These beams become eventually disjoint in the region far away from the origin. If an -thin -run without repeated configuration is long enough, it must contain a configuration whose vector is far from origin. In this case we can find a sub-run around that stays within a unique -beam. As is a -run, first goes “up” and then “down” in this beam. From this observation we will extract from two cycles of opposite effects by Pigeonhole Principle. Deleting these cycles shortens the length of .
For thick runs, recall that they only occur in proper VASSes.
Lemma 4.26.
Let be a proper geometrically 2-dimensional -VASS with . For any -run in that is -thick for some , there is a -run with the same source and target states as such that .
Proof sketch.
Consider a thick run . By definition, it can be decomposed into such that each of and contains four pumping cycles. For each path and , 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 and 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.
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 -VASS to 2-VASS. In this section we will show that such a reduction is indeed possible for . We shall also mention some issues one will face when trying to generalize this reduction for .
In this section we care about the unary-encoding size of VASSes. Let be a -VASS, its unary-encoding size is defined as . 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 -dimensinoal 3-VASS with 2 states , one can compute in time polynomial in a 2-VASS with 2 states satisfying , such that the following statements are equivalent:
-
there exists a run from to of length in ;
-
there exists a run from to of length in .
Corollary 5.2.
Reachability in geometrically -dimensinoal 3-VASS is in PSPACE.
Proof.
By [2, Theorem 3.2], in a 2-VASS , length of the shortest reachability witness is bounded by . Together with 5.1 this shows that length of the shortest reachability witness in a geometrically -dimensinoal 3-VASS is also bounded by , which is exponential in the binary-encoding size . Polynomial space is enough for enumerating every run of length at most .
The following is devoted to 5.1. Fix a geometrically -dimensinoal 3-VASS with 2 states . We can assume that , by adding isolated loops to when necessary. Then there exists a normal vector such that . As is spanned by effects of two simple cycles, whose norms are bounded by , applying Cramer’s rule we can assume . Let , we define the set as an affine copy of . The following proposition shows that any run from moves within a limited number of ’s.
Proposition 5.3.
There exists a number such that for any configuration reachable from , for some with .
Proof.
By 3.4 we have for some and . So for . Note that . We can pick .
Proof of 5.1.
Let be the number given in 5.3. We consider 2 cases according to the signs of components in .
Case 1. (or symmetrically ).
By 5.3, every configuration reachable from satisfies . We claim that . Otherwise, as is an integer vector, for all , then implies . Then we can encode all possible values of the coordinates in using the states of the VASS and thus reduce its dimension. As , 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 . 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. contains both positive and negative components.
By negating we can assume there is only one negative component in . Assume w.l.o.g. and . Let for some , then we have . We construct a 2-VASS that projects onto the first 2 coordinates. Let be defined as follows. The state set contains . Intuitively a configuration in represents the configuration in such that , and the barred version marks an “unchecked” state, where could be negative. So for each transition of , we add the transitions to for all and . Indeed, if in and , , then . This justifies the correctness of the transitions we added to .
Next, we add to transitions that checks, at each state , if the configuration represents a legal configuration in , where , so . As , this is equivalent to checking if . Recall that , one can verify that for , we have if and only if , where is the set of minimal solutions given by
| (15) |
Now for each number with , we add the path to for each , where is an arbitrary but unique state added to . One can easily verify that if and only if . Therefore, in for a path of length if and only if in for a path of length . Also note that , so we have . This completes the proof.
Finally, we mention some issues when trying to generalize for higher dimensions.
-
1.
If the dimension is not fixed as a parameter, one can easily construct an acyclic (geometrically 0-dimensinoal) VASS so that each point in the Hamming cube is reachable from . Then the reduced VASS must handle an exponential number of affine copies of , which suggests an exponential blow-up in size.
-
2.
For the reduced 2-VASS only need to check inequalities of the form for . For higher dimensions we no longer have the assumption . And we have no idea how to make a VASS check inequalities such as .
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 for some . Thus, the cycle space of the reduced VASS is contained in . 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 be a geometrically -dimensional VASS. Then any cycle in has effect . So for any run in we can safely remove all cycles from and obtain a run whose length is bounded by . Now a nondeterministic algorithm can decide reachability in by simply guessing a run of length at most .
For the lower bound, we recall the folklore reduction from Subset-Sum to the reachability problem in 1-VASS. Given an instance of Subset-Sum, where and the goal is to find a subset of whose sum is , we construct a 1-VASS as follows. The states are . For each we add two transitions and . One can easily observe that there exists a subset of with sum if and only if in . Note that there are no cycles in , thus 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 -VASS can be adapted to geometrically -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 -dimensional VASS and -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 counters (recall that the size of under unary encoding is ). The complexity of reachability in low geometric dimensions under unary encoding is left for future work.
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