3,323 research outputs found
On the State Complexity of Partial Derivative Automata For Regular Expressions with Intersection
Extended regular expressions (with complement and intersection) are used in many applications due to their succinctness. In particular, regular expressions extended with intersection only (also called semi-extended) can already be exponentially smaller than standard regular expressions or equivalent nondeterministic finite automata (NFA). For practical purposes it is important to study the average behaviour of conversions between these models. In this paper, we focus on the conversion of regular expressions with intersection to nondeterministic finite automata, using partial derivatives and the notion of support. First, we give a tight upper bound of 2O(n) for the worst-case number of states of the resulting partial derivative automaton, where n is the size of the expression. Using the framework of analytic combinatorics, we then establish an upper bound of (1.056 + o(1))n for its asymptotic average-state complexity, which is significantly smaller than the one for the worst case. (c) IFIP International Federation for Information Processing 2016
Regular Expressions and Transducers over Alphabet-invariant and User-defined Labels
We are interested in regular expressions and transducers that represent word
relations in an alphabet-invariant way---for example, the set of all word pairs
u,v where v is a prefix of u independently of what the alphabet is. Current
software systems of formal language objects do not have a mechanism to define
such objects. We define transducers in which transition labels involve what we
call set specifications, some of which are alphabet invariant. In fact, we give
a more broad definition of automata-type objects, called labelled graphs, where
each transition label can be any string, as long as that string represents a
subset of a certain monoid. Then, the behaviour of the labelled graph is a
subset of that monoid. We do the same for regular expressions. We obtain
extensions of a few classic algorithmic constructions on ordinary regular
expressions and transducers at the broad level of labelled graphs and in such a
way that the computational efficiency of the extended constructions is not
sacrificed. For regular expressions with set specs we obtain the corresponding
partial derivative automata. For transducers with set specs we obtain further
algorithms that can be applied to questions about independent regular
languages, in particular the witness version of the independent property
satisfaction question
Quasichemical Models of Multicomponent Nonlinear Diffusion
Diffusion preserves the positivity of concentrations, therefore,
multicomponent diffusion should be nonlinear if there exist non-diagonal terms.
The vast variety of nonlinear multicomponent diffusion equations should be
ordered and special tools are needed to provide the systematic construction of
the nonlinear diffusion equations for multicomponent mixtures with significant
interaction between components. We develop an approach to nonlinear
multicomponent diffusion based on the idea of the reaction mechanism borrowed
from chemical kinetics.
Chemical kinetics gave rise to very seminal tools for the modeling of
processes. This is the stoichiometric algebra supplemented by the simple
kinetic law. The results of this invention are now applied in many areas of
science, from particle physics to sociology. In our work we extend the area of
applications onto nonlinear multicomponent diffusion.
We demonstrate, how the mechanism based approach to multicomponent diffusion
can be included into the general thermodynamic framework, and prove the
corresponding dissipation inequalities. To satisfy thermodynamic restrictions,
the kinetic law of an elementary process cannot have an arbitrary form. For the
general kinetic law (the generalized Mass Action Law), additional conditions
are proved. The cell--jump formalism gives an intuitively clear representation
of the elementary transport processes and, at the same time, produces kinetic
finite elements, a tool for numerical simulation.Comment: 81 pages, Bibliography 118 references, a review paper (v4: the final
published version
Optimization of Regular Path Queries in Graph Databases
Regular path queries offer a powerful navigational mechanism in graph databases. Recently, there has been renewed interest in such queries in the context of the Semantic Web. The extension of SPARQL in version 1.1 with property paths offers a type of regular path query for RDF graph databases. While eminently useful, such queries are difficult to optimize and evaluate efficiently, however. We design and implement a cost-based optimizer we call Waveguide for SPARQL queries with property paths. Waveguide builds a query planwhich we call a waveplan (WP)which guides the query evaluation. There are numerous choices in the con- struction of a plan, and a number of optimization methods, so the space of plans for a query can be quite large. Execution costs of plans for the same query can vary by orders of magnitude with the best plan often offering excellent performance. A WPs costs can be estimated, which opens the way to cost-based optimization. We demonstrate that Waveguide properly subsumes existing techniques and that the new plans it adds are relevant. We analyze the effective plan space which is enabled by Waveguide and design an efficient enumerator for it. We implement a pro- totype of a Waveguide cost-based optimizer on top of an open-source relational RDF store. Finally, we perform a comprehensive performance study of the state of the art for evaluation of SPARQL property paths and demonstrate the significant performance gains that Waveguide offers
Beyond the Spectral Theorem: Spectrally Decomposing Arbitrary Functions of Nondiagonalizable Operators
Nonlinearities in finite dimensions can be linearized by projecting them into
infinite dimensions. Unfortunately, often the linear operator techniques that
one would then use simply fail since the operators cannot be diagonalized. This
curse is well known. It also occurs for finite-dimensional linear operators. We
circumvent it by developing a meromorphic functional calculus that can
decompose arbitrary functions of nondiagonalizable linear operators in terms of
their eigenvalues and projection operators. It extends the spectral theorem of
normal operators to a much wider class, including circumstances in which poles
and zeros of the function coincide with the operator spectrum. By allowing the
direct manipulation of individual eigenspaces of nonnormal and
nondiagonalizable operators, the new theory avoids spurious divergences. As
such, it yields novel insights and closed-form expressions across several areas
of physics in which nondiagonalizable dynamics are relevant, including
memoryful stochastic processes, open non unitary quantum systems, and
far-from-equilibrium thermodynamics.
The technical contributions include the first full treatment of arbitrary
powers of an operator. In particular, we show that the Drazin inverse,
previously only defined axiomatically, can be derived as the negative-one power
of singular operators within the meromorphic functional calculus and we give a
general method to construct it. We provide new formulae for constructing
projection operators and delineate the relations between projection operators,
eigenvectors, and generalized eigenvectors.
By way of illustrating its application, we explore several, rather distinct
examples.Comment: 29 pages, 4 figures, expanded historical citations;
http://csc.ucdavis.edu/~cmg/compmech/pubs/bst.ht
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