14,121 research outputs found
Toward an architecture for quantum programming
It is becoming increasingly clear that, if a useful device for quantum
computation will ever be built, it will be embodied by a classical computing
machine with control over a truly quantum subsystem, this apparatus performing
a mixture of classical and quantum computation.
This paper investigates a possible approach to the problem of programming
such machines: a template high level quantum language is presented which
complements a generic general purpose classical language with a set of quantum
primitives. The underlying scheme involves a run-time environment which
calculates the byte-code for the quantum operations and pipes it to a quantum
device controller or to a simulator.
This language can compactly express existing quantum algorithms and reduce
them to sequences of elementary operations; it also easily lends itself to
automatic, hardware independent, circuit simplification. A publicly available
preliminary implementation of the proposed ideas has been realized using the
C++ language.Comment: 23 pages, 5 figures, A4paper. Final version accepted by EJPD ("swap"
replaced by "invert" for Qops). Preliminary implementation available at:
http://sra.itc.it/people/serafini/quantum-computing/qlang.htm
Cost Preserving Bisimulations for Probabilistic Automata
Probabilistic automata constitute a versatile and elegant model for
concurrent probabilistic systems. They are equipped with a compositional theory
supporting abstraction, enabled by weak probabilistic bisimulation serving as
the reference notion for summarising the effect of abstraction. This paper
considers probabilistic automata augmented with costs. It extends the notions
of weak transitions in probabilistic automata in such a way that the costs
incurred along a weak transition are captured. This gives rise to
cost-preserving and cost-bounding variations of weak probabilistic
bisimilarity, for which we establish compositionality properties with respect
to parallel composition. Furthermore, polynomial-time decision algorithms are
proposed, that can be effectively used to compute reward-bounding abstractions
of Markov decision processes in a compositional manner
On the Collaboration of an Automatic Path-Planner and a Human User for Path-Finding in Virtual Industrial Scenes
This paper describes a global interactive framework enabling an automatic path-planner and a user to collaborate for finding a path in cluttered virtual environments. First, a collaborative architecture including the user and the planner is described. Then, for real time purpose, a motion planner divided into different steps is presented. First, a preliminary workspace discretization is done without time limitations at the beginning of the simulation. Then, using these pre-computed data, a second algorithm finds a collision free path in real time. Once the path is found, an haptic artificial guidance on the path is provided to the user. The user can then influence the planner by not following the path and automatically order a new path research. The performances are measured on tests based on assembly simulation in CAD scenes
A fuzzy multiobjective algorithm for multiproduct batch plant: Application to protein production
This paper addresses the problem of the optimal design of batch plants with imprecise demands and proposes an alternative treatment of the imprecision by using fuzzy concepts. For this purpose, we extended a multiobjective genetic algorithm (MOGA) developed in previousworks, taking into account simultaneously maximization of the net present value (NPV) and two other performance criteria, i.e. the production delay/advance and a flexibility criterion. The former is computed by comparing the fuzzy computed production time to a given fuzzy production time horizon and the latter is based on the additional fuzzy demand that the plant is able to produce. The methodology provides a set of scenarios that are helpful to the decision’s maker and constitutes a very promising framework for taken imprecision into account in new product development stage
Approximate Bayesian Computation by Subset Simulation
A new Approximate Bayesian Computation (ABC) algorithm for Bayesian updating
of model parameters is proposed in this paper, which combines the ABC
principles with the technique of Subset Simulation for efficient rare-event
simulation, first developed in S.K. Au and J.L. Beck [1]. It has been named
ABC- SubSim. The idea is to choose the nested decreasing sequence of regions in
Subset Simulation as the regions that correspond to increasingly closer
approximations of the actual data vector in observation space. The efficiency
of the algorithm is demonstrated in two examples that illustrate some of the
challenges faced in real-world applications of ABC. We show that the proposed
algorithm outperforms other recent sequential ABC algorithms in terms of
computational efficiency while achieving the same, or better, measure of ac-
curacy in the posterior distribution. We also show that ABC-SubSim readily
provides an estimate of the evidence (marginal likelihood) for posterior model
class assessment, as a by-product
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Structure identification in relational data
This paper presents several investigations into the prospects for identifying meaningful structures in empirical data, namely, structures permitting effective organization of the data to meet requirements of future queries. We propose a general framework whereby the notion of identifiability is given a precise formal definition similar to that of learnability. Using this framework, we then explore if a tractable procedure exists for deciding whether a given relation is decomposable into a constraint network or a CNF theory with desirable topology and, if the answer is positive, identifying the desired decomposition. Finally, we address the problem of expressing a given relation as a Horn theory and, if this is impossible, finding the best k-Horn approximation to the given relation. We show that both problems can be solved in time polynomial in the length of the data
Japanese/English Cross-Language Information Retrieval: Exploration of Query Translation and Transliteration
Cross-language information retrieval (CLIR), where queries and documents are
in different languages, has of late become one of the major topics within the
information retrieval community. This paper proposes a Japanese/English CLIR
system, where we combine a query translation and retrieval modules. We
currently target the retrieval of technical documents, and therefore the
performance of our system is highly dependent on the quality of the translation
of technical terms. However, the technical term translation is still
problematic in that technical terms are often compound words, and thus new
terms are progressively created by combining existing base words. In addition,
Japanese often represents loanwords based on its special phonogram.
Consequently, existing dictionaries find it difficult to achieve sufficient
coverage. To counter the first problem, we produce a Japanese/English
dictionary for base words, and translate compound words on a word-by-word
basis. We also use a probabilistic method to resolve translation ambiguity. For
the second problem, we use a transliteration method, which corresponds words
unlisted in the base word dictionary to their phonetic equivalents in the
target language. We evaluate our system using a test collection for CLIR, and
show that both the compound word translation and transliteration methods
improve the system performance
A generic imperative language for polynomial time
The ramification method in Implicit Computational Complexity has been
associated with functional programming, but adapting it to generic imperative
programming is highly desirable, given the wider algorithmic applicability of
imperative programming. We introduce a new approach to ramification which,
among other benefits, adapts readily to fully general imperative programming.
The novelty is in ramifying finite second-order objects, namely finite
structures, rather than ramifying elements of free algebras. In so doing we
bridge between Implicit Complexity's type theoretic characterizations of
feasibility, and the data-flow approach of Static Analysis.Comment: 18 pages, submitted to a conferenc
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