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Algebra is a well-established part of mathematics, dealing with sets with operations satisfying certain properties, like groups, rings, vector spaces, etc. Its results are essential throughout mathematics and other sciences. Universal algebra is a part of algebra in which algebraic structures are studied at a high level of abstraction and in which general notions like homomorphism, subalgebra, congruence are studied in themselves, see e.g. [Coh81, MT92, Wec92]. A further step up the abstraction ladder is taken when one studies algebra with the notions and tools from category theory. This approach leads to a particularly concise notion of what is an algebra (for a functor or for a monad), see for example [Man74]. The conceptual world that we are about to enter owes much to this categorical view, but it also takes inspiration from universal algebra, see e.g. [Rut00].
In general terms, a program in some programming language manipulates data. During the development of computer science over the past few decades it became clear that an abstract description of these data is desirable, for example to ensure that one's program does not depend on the particular representation of the data on which it operates. Also, such abstractness facilitates correctness proofs. This desire led to the use of algebraic methods in computer science, in a branch called algebraic specification or abstract data type theory. The objects of study are data types in themselves, using notions and techniques which are familiar from algebra.
One of the main reasons for the success of bisimilarity is the strength of the associated proof method. We discuss here the method on processes, more precisely, on Labelled Transition Systems (LTSs). However the reader should bear in mind that the bisimulation concept has applications in many areas beyond concurrency [San12]. According to the proof method, to establish that two processes are bisimilar it suffices to find a relation on processes that contains the given pair and that is a bisimulation. Being a bisimulation means that related processes can match each other's transitions so that the derivatives are again related.
In general, when two processes are bisimilar there may be many relations containing the pair, including the bisimilarity relation, defined as the union of all bisimulations. However, the amount of work needed to prove that a relation is a bisimulation depends on its size, since there are transition diagrams to check for each pair. It is therefore important to use relations as small as possible.
In this chapter we show that the bisimulation proof method can be enhanced, by employing relations called ‘bisimulations up to’. These relations need not be bisimulations; they are just contained in a bisimulation. The proof that a relation is a ‘bisimulation up to’ follows diagram-chasing arguments similar to those in bisimulation proofs. The reason why ‘bisimulations up to’ are interesting is that they can be substantially smaller than any enclosing bisimulation; hence they may entail much less work in proofs.
In this chapter,we look at the origins of bisimulation.We showthat bisimulation has been discovered not only in computer science, but also – and roughly at the same time – in other fields: philosophical logic (more precisely, modal logic), and set theory. In each field, we discuss the main steps that led to the discovery, and introduce the people who made these steps possible.
In computer science, philosophical logic, and set theory, bisimulation has been derived through refinements of notions of morphism between algebraic structures. Roughly, morphisms are maps (i.e. functions) that are ‘structurepreserving’. The notion is therefore fundamental in all mathematical theories in which the objects of study have some kind of structure, or algebra. The most basic forms of morphism are the homomorphisms. These essentially give us a way of embedding a structure (the source) into another one (the target), so that all the relations in the source are present in the target. The converse, however, need not be true; for this, stronger notions of morphism are needed. One such notion is isomorphism, which is, however, extremely strong – isomorphic structures must be essentially the same, i.e. ‘algebraically identical’. It is a quest for notions in between homomorphism and isomorphism that led to the discovery of bisimulation.
The kind of structures studied in computer science, philosophical logic, and set theory were forms of rooted directed graphs.
A model for reactive computation, for example that of labelled transition systems [Kel76], or a process algebra (such asACP [BW90], CCS [Mil89], CSP [Hoa85]) can be used to describe both implementations of processes and specifications of their expected behaviours. Process algebras and labelled transition systems therefore naturally support the so-called single-language approach to process theory, that is, the approach in which a single language is used to describe both actual processes and their specifications. An important ingredient of the theory of these languages and their associated semantic models is therefore a notion of behavioural equivalence or behavioural approximation between processes. One process description, say SYS, may describe an implementation, and another, say SPEC, may describe a specification of the expected behaviour. To say that SYS and SPEC are equivalent is taken to indicate that these two processes describe essentially the same behaviour, albeit possibly at different levels of abstraction or refinement. To say that, in some formal sense, SYS is an approximation of SPEC means roughly that every aspect of the behaviour of this process is allowed by the specification SPEC, and thus that nothing unexpected can happen in the behaviour of SYS. This approach to program verification is also sometimes called implementation verification or equivalence checking.
Designers using implementation verification to validate their (models of) reactive systems need only learn one language to describe both their systems and their specifications, and can benefit from the intrinsic compositionality of their descriptions, at least when they are using a process algebra for denoting the labelled transition systems in their models and an equivalence (or preorder) that is preserved by the operations in the algebra.
The Turán number of a graph H, ex(n, H), is the maximum number of edges in any graph on n vertices which does not contain H as a subgraph. Let Pl denote a path on l vertices, and let k ⋅ Pl denote k vertex-disjoint copies of Pl. We determine ex(n, k ⋅ P3) for n appropriately large, answering in the positive a conjecture of Gorgol. Further, we determine ex(n, k ⋅ Pl) for arbitrary l, and n appropriately large relative to k and l. We provide some background on the famous Erdős–Sós conjecture, and conditional on its truth we determine ex(n, H) when H is an equibipartite forest, for appropriately large n.
In this paper, we study certain pairings which are defined as follows: if A and B are finite subsets of an arbitrary group, a Wakeford–Fan–Losonczy pairing from B onto A is a bijection φ : B → A such that bφ(b) ∉ A, for every b ∈ B. The number of such pairings is denoted by μ(B, A).
We investigate the quantity μ(B, A) for A and B, two finite subsets of an arbitrary group satisfying 1 ∉ B, |A| = |B|, and the fact that the order of every element of B is ≥ |B| + 1. Extending earlier results, we show that in this case, μ(B, A) is never equal to 0. Furthermore we prove an explicit lower bound on μ(B, A) in terms of |B| and the cardinality of the group generated by B, which is valid unless A and B have a special form explicitly described. In the case A = B, our bound holds unless B is a translate of a progression.
We present a simple graph integral equivalent to a multiple of the circuit partition polynomial. Let G be a directed graph, and let k be a positive integer. Associate with each vertex v of G an independent, uniformly random k-dimensional complex vector xv of unit length. We define q(G;k) to be the expected value of the product, over all edges (u, v), of the inner product 〈xu, xv〉. We show that q(G;k) is proportional to G's cycle partition polynomial, and therefore that computing q(G;k) is #P-complete for any k > 1. We also study the natural variants that arise when the xv are real or drawn from the Gaussian distribution.
In this work we give a study of generalizations of Stirling permutations, a restricted class of permutations of multisets introduced by Gessel and Stanley [15]. First we give several bijections between such generalized Stirling permutations and various families of increasing trees extending the known correspondences of [20, 21]. Then we consider several permutation statistics of interest for generalized Stirling permutations as the number of left-to-right minima, the number of left-to-right maxima, the number of blocks of specified sizes, the distance between occurrences of elements, and the number of inversions. For all these quantities we give a distributional study, where the established connections to increasing trees turn out to be very useful. To obtain the exact and limiting distribution results we use several techniques ranging from generating functions, connections to urn models, martingales and Stein's method.
The repetition threshold introduced by Dejean and Brandenburg is the smallest real number α such that there exists an infinite word over a k-letter alphabet that avoids β-powers for all β>α. We extend this notion to colored graphs and obtain the value of the repetition thresholds of trees and “large enough” subdivisions of graphs for every alphabet size.
The (−β)-integers are natural generalisations of theβ-integers, and thus of the integers, for negative real bases. Whenβ is the analogue of a Parry number, we describe the structure of theset of (−β)-integers by a fixed point of an anti-morphism.
We study cooperating distributed systems (CD-systems) of stateless deterministicrestarting automata with window size 1 that are equipped with an external pushdown store.In this way we obtain an automata-theoretical characterization for the class of wordlanguages that are linearizations of context-free trace languages.
We obtain a first non-trivial estimate for the sum of dilates problem in the case of groups of prime order, by showing that if t is an integer different from 0, 1 or −1 and if ⊂ ℤ/pℤ is not too large (with respect to p), then | + t ⋅ | is significantly larger than 2|| (unless |t| = 3). In the important case |t| = 2, we obtain for instance | + t ⋅ | ≥ 2.08 ||−2.
Plünnecke's inequality is a standard tool for obtaining estimates on the cardinality of sumsets and has many applications in additive combinatorics. We present a new proof. The main novelty is that the proof is completed with no reference to Menger's theorem or Cartesian products of graphs. We also investigate the sharpness of the inequality and show that it can be sharp for arbitrarily long, but not for infinite commutative graphs. A key step in our investigation is the construction of arbitrarily long regular commutative graphs. Lastly we prove a necessary condition for the inequality to be attained.
We consider the problem of selecting sequentially a unimodal subsequence from a sequence of independent identically distributed random variables, and we find that a person doing optimal sequential selection does so within a factor of the square root of two as well as a prophet who knows all of the random observations in advance of any selections. Our analysis applies in fact to selections of subsequences that have d+1 monotone blocks, and, by including the case d=0, our analysis also covers monotone subsequences.
We prove that some fairly basic questions on automata reading infinite words depend on the models of the axiomatic system ZFC. It is known that there are only three possibilities for the cardinality of the complement of an ω-language \hbox{$L(\mathcal{A})$}L(𝒜) accepted by a Büchi 1-counter automaton \hbox{$\mathcal{A}$}𝒜. We prove the following surprising result: there exists a 1-counter Büchi automaton \hbox{$\mathcal{A}$}𝒜 such that the cardinality of the complement \hbox{$L(\mathcal{A})^-$}L(𝒜) − of the ω-language \hbox{$L(\mathcal{A})$}L(𝒜) is not determined by ZFC: (1) There is a model V1 of ZFC in which \hbox{$L(\mathcal{A})^-$}L(𝒜) − is countable. (2) There is a model V2 of ZFC in which \hbox{$L(\mathcal{A})^-$}L(𝒜) − has cardinal 2ℵ0. (3) There is a model V3 of ZFC in which \hbox{$L(\mathcal{A})^-$}L(𝒜) − has cardinal ℵ1 with ℵ0< ℵ1< 2ℵ0.
We prove a very similar result for the complement of an infinitary rational relation accepted by a 2-tape Büchi automaton ℬ. As a corollary, this proves that the continuum hypothesis may be not satisfied for complements of 1-counter ω-languages and for complements of infinitary rational relations accepted by 2-tape Büchi automata. We infer from the proof of the above results that basic decision problems about 1-counter ω-languages or infinitary rational relations are actually located at the third level of the analytical hierarchy. In particular, the problem to determine whether the complement of a 1-counter ω-language (respectively, infinitary rational relation) is countable is in Σ13\(Π12 ∪ Σ12). This is rather surprising if compared to the fact that it is decidable whether an infinitary rational relation is countable (respectively, uncountable).
We show that there are graphs with n vertices containing no K5,5 which have about n7/4 edges, thus proving that ex(n, K5,5) ≥ (1 + o(1))n7/4. This bound gives an asymptotic improvement to the known lower bounds on ex(n, Kt, s) for t = 5 when 5 ≤ s ≤ 12, and t = 6 when 6 ≤ s ≤ 8.
The bandwidth minimization problem is of significance in network communication and related areas. Let G be a graph of n vertices. The two-dimensional bandwidth B2(G) of G is the minimum value of the maximum distance between adjacent vertices when G is embedded into an n × n grid in the plane. As a discrete optimization problem, determining B2(G) is NP-hard in general. However, exact results for this parameter can be derived for some special classes of graphs. This paper studies the “square-root rule” of the two-dimensional bandwidth, which is useful in evaluating B2(G) for some typical graphs.
In the paper we study abelian versions of the critical factorization theorem. We investigate both similarities and differences between the abelian powers and the usual powers. The results we obtained show that the constraints for abelian powers implying periodicity should be quite strong, but still natural analogies exist.
The depth-first search (DFS) technique is a method of scanning a finite, undirected graph. Since the publication of the papers of Hopcroft and Tarjan [4, 6], DFS has been widely recognized as a powerful technique for solving various graph problems. However, the algorithm has been known since the nineteenth century as a technique for threading mazes. See, for example, Lucas' report of Trémaux's work [5]. Another algorithm, which was suggested later by Tarry [7], is just as good for threading mazes, and in fact, DFS is a special case of it. But the additional structure of DFS is what makes the technique so useful.
Trémaux's Algorithm
Assume one is given a finite, connected graph G(V,E), which we will also refer to as the maze. Starting in one of the vertices, one wants to “walk” along the edges, from vertex to vertex, visit all vertices, and halt. We seek an algorithm that will guarantee that the whole graph will be scanned without wandering too long in the maze, and that the procedure will allow one to recognize when the task is done. However, before one starts walking in the maze, one does not know anything about its structure, and therefore, no preplanning is possible. So, decisions about where to go next must be made one by one as one goes along.
We will use “markers,” which will be placed in the maze to help one to recognize that one has returned to a place visited earlier and to make later decisions on where to go next.