3,217 research outputs found
A Modeling Framework for Schedulability Analysis of Distributed Avionics Systems
This paper presents a modeling framework for schedulability analysis of
distributed integrated modular avionics (DIMA) systems that consist of
spatially distributed ARINC-653 modules connected by a unified AFDX network. We
model a DIMA system as a set of stopwatch automata (SWA) in UPPAAL to analyze
its schedulability by classical model checking (MC) and statistical model
checking (SMC). The framework has been designed to enable three types of
analysis: global SMC, global MC, and compositional MC. This allows an effective
methodology including (1) quick schedulability falsification using global SMC
analysis, (2) direct schedulability proofs using global MC analysis in simple
cases, and (3) strict schedulability proofs using compositional MC analysis for
larger state space. The framework is applied to the analysis of a concrete DIMA
system.Comment: In Proceedings MARS/VPT 2018, arXiv:1803.0866
Generic Incomparability of Infinite-Dimensional Entangled States
In support of a recent conjecture by Nielsen (1999), we prove that the
phenomena of 'incomparable entanglement'--whereby, neither member of a pair of
pure entangled states can be transformed into the other via local operations
and classical communication (LOCC)--is a generic feature when the states at
issue live in an infinite-dimensional Hilbert space.Comment: 3 pages, final published version, minor adjustment
A Compositional Approach for Schedulability Analysis of Distributed Avionics Systems
This work presents a compositional approach for schedulability analysis of
Distributed Integrated Modular Avionics (DIMA) systems that consist of
spatially distributed ARINC-653 modules connected by a unified AFDX network. We
model a DIMA system as a set of stopwatch automata in UPPAAL to verify its
schedulability by model checking. However, direct model checking is infeasible
due to the large state space. Therefore, we introduce the compositional
analysis that checks each partition including its communication environment
individually. Based on a notion of message interfaces, a number of message
sender automata are built to model the environment for a partition. We define a
timed selection simulation relation, which supports the construction of
composite message interfaces. By using assume-guarantee reasoning, we ensure
that each task meets the deadline and that communication constraints are also
fulfilled globally. The approach is applied to the analysis of a concrete DIMA
system.Comment: In Proceedings MeTRiD 2018, arXiv:1806.09330. arXiv admin note: text
overlap with arXiv:1803.1105
Learning Markov Decision Processes for Model Checking
Constructing an accurate system model for formal model verification can be
both resource demanding and time-consuming. To alleviate this shortcoming,
algorithms have been proposed for automatically learning system models based on
observed system behaviors. In this paper we extend the algorithm on learning
probabilistic automata to reactive systems, where the observed system behavior
is in the form of alternating sequences of inputs and outputs. We propose an
algorithm for automatically learning a deterministic labeled Markov decision
process model from the observed behavior of a reactive system. The proposed
learning algorithm is adapted from algorithms for learning deterministic
probabilistic finite automata, and extended to include both probabilistic and
nondeterministic transitions. The algorithm is empirically analyzed and
evaluated by learning system models of slot machines. The evaluation is
performed by analyzing the probabilistic linear temporal logic properties of
the system as well as by analyzing the schedulers, in particular the optimal
schedulers, induced by the learned models.Comment: In Proceedings QFM 2012, arXiv:1212.345
Control of inhomogeneous atomic ensembles of hyperfine qudits
We study the ability to control d-dimensional quantum systems (qudits)
encoded in the hyperfine spin of alkali-metal atoms through the application of
radio- and microwave-frequency magnetic fields in the presence of
inhomogeneities in amplitude and detuning. Such a capability is essential to
the design of robust pulses that mitigate the effects of experimental
uncertainty and also for application to tomographic addressing of particular
members of an extended ensemble. We study the problem of preparing an arbitrary
state in the Hilbert space from an initial fiducial state. We prove that
inhomogeneous control of qudit ensembles is possible based on a semi-analytic
protocol that synthesizes the target through a sequence of alternating rf and
microwave-driven SU(2) rotations in overlapping irreducible subspaces. Several
examples of robust control are studied, and the semi-analytic protocol is
compared to a brute force, full numerical search. For small inhomogeneities, <
1%, both approaches achieve average fidelities greater than 0.99, but the brute
force approach performs superiorly, reaching high fidelities in shorter times
and capable of handling inhomogeneities well beyond experimental uncertainty.
The full numerical search is also applied to tomographic addressing whereby two
different nonclassical states of the spin are produced in two halves of the
ensemble
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