42,894 research outputs found
Evolutionary Dynamics in a Simple Model of Self-Assembly
We investigate the evolutionary dynamics of an idealised model for the robust
self-assembly of two-dimensional structures called polyominoes. The model
includes rules that encode interactions between sets of square tiles that drive
the self-assembly process. The relationship between the model's rule set and
its resulting self-assembled structure can be viewed as a genotype-phenotype
map and incorporated into a genetic algorithm. The rule sets evolve under
selection for specified target structures. The corresponding, complex fitness
landscape generates rich evolutionary dynamics as a function of parameters such
as the population size, search space size, mutation rate, and method of
recombination. Furthermore, these systems are simple enough that in some cases
the associated model genome space can be completely characterised, shedding
light on how the evolutionary dynamics depends on the detailed structure of the
fitness landscape. Finally, we apply the model to study the emergence of the
preference for dihedral over cyclic symmetry observed for homomeric protein
tetramers
The dome: An unexpectedly simple failure of determinism
Newton's equations of motion tell us that a mass at rest at the apex of a dome with the shape specified here can spontaneously move. It has been suggested that this indeterminism should be discounted since it draws on an incomplete rendering of Newtonian physics, or it is "unphysical," or it employs illicit idealizations. I analyze and reject each of these reasons. Copyright 2008 by the Philosophy of Science Association. All rights reserved
Generalized Flow and Determinism in Measurement-based Quantum Computation
We extend the notion of quantum information flow defined by Danos and Kashefi
for the one-way model and present a necessary and sufficient condition for the
deterministic computation in this model. The generalized flow also applied in
the extended model with measurements in the X-Y, X-Z and Y-Z planes. We apply
both measurement calculus and the stabiliser formalism to derive our main
theorem which for the first time gives a full characterization of the
deterministic computation in the one-way model. We present several examples to
show how our result improves over the traditional notion of flow, such as
geometries (entanglement graph with input and output) with no flow but having
generalized flow and we discuss how they lead to an optimal implementation of
the unitaries. More importantly one can also obtain a better quantum
computation depth with the generalized flow rather than with flow. We believe
our characterization result is particularly essential for the study of the
algorithms and complexity in the one-way model.Comment: 16 pages, 10 figure
A probabilistic extension of UML statecharts: specification and verification
This paper is the extended technical report that corresponds to a published paper [14]. This paper introduces means to specify system randomness within UML statecharts, and to verify probabilistic temporal properties over such enhanced statecharts which we call probabilistic UML statecharts. To achieve this, we develop a general recipe to extend a statechart semantics with discrete probability distributions, resulting in Markov decision processes as semantic models. We apply this recipe to the requirements-level UML semantics of [8]. Properties of interest for probabilistic statecharts are expressed in PCTL, a probabilistic variant of CTL for processes that exhibit both non-determinism and probabilities. Verification is performed using the model checker Prism. A model checking example shows the feasibility of the suggested approach
Deterministic Automata for Unordered Trees
Automata for unordered unranked trees are relevant for defining schemas and
queries for data trees in Json or Xml format. While the existing notions are
well-investigated concerning expressiveness, they all lack a proper notion of
determinism, which makes it difficult to distinguish subclasses of automata for
which problems such as inclusion, equivalence, and minimization can be solved
efficiently. In this paper, we propose and investigate different notions of
"horizontal determinism", starting from automata for unranked trees in which
the horizontal evaluation is performed by finite state automata. We show that a
restriction to confluent horizontal evaluation leads to polynomial-time
emptiness and universality, but still suffers from coNP-completeness of the
emptiness of binary intersections. Finally, efficient algorithms can be
obtained by imposing an order of horizontal evaluation globally for all
automata in the class. Depending on the choice of the order, we obtain
different classes of automata, each of which has the same expressiveness as
CMso.Comment: In Proceedings GandALF 2014, arXiv:1408.556
Generalized Flow and Determinism in Measurement-based Quantum Computation
We extend the notion of quantum information flow defined by Danos and Kashefi
for the one-way model and present a necessary and sufficient condition for the
deterministic computation in this model. The generalized flow also applied in
the extended model with measurements in the X-Y, X-Z and Y-Z planes. We apply
both measurement calculus and the stabiliser formalism to derive our main
theorem which for the first time gives a full characterization of the
deterministic computation in the one-way model. We present several examples to
show how our result improves over the traditional notion of flow, such as
geometries (entanglement graph with input and output) with no flow but having
generalized flow and we discuss how they lead to an optimal implementation of
the unitaries. More importantly one can also obtain a better quantum
computation depth with the generalized flow rather than with flow. We believe
our characterization result is particularly essential for the study of the
algorithms and complexity in the one-way model.Comment: 16 pages, 10 figure
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