504 research outputs found
Real-Reward Testing for Probabilistic Processes (Extended Abstract)
We introduce a notion of real-valued reward testing for probabilistic
processes by extending the traditional nonnegative-reward testing with negative
rewards. In this richer testing framework, the may and must preorders turn out
to be inverses. We show that for convergent processes with finitely many states
and transitions, but not in the presence of divergence, the real-reward
must-testing preorder coincides with the nonnegative-reward must-testing
preorder. To prove this coincidence we characterise the usual resolution-based
testing in terms of the weak transitions of processes, without having to
involve policies, adversaries, schedulers, resolutions, or similar structures
that are external to the process under investigation. This requires
establishing the continuity of our function for calculating testing outcomes.Comment: In Proceedings QAPL 2011, arXiv:1107.074
On Hidden States in Quantum Random Walks
It was recently pointed out that identifiability of quantum random walks and
hidden Markov processes underlie the same principles. This analogy immediately
raises questions on the existence of hidden states also in quantum random walks
and their relationship with earlier debates on hidden states in quantum
mechanics. The overarching insight was that not only hidden Markov processes,
but also quantum random walks are finitary processes. Since finitary processes
enjoy nice asymptotic properties, this also encourages to further investigate
the asymptotic properties of quantum random walks. Here, answers to all these
questions are given. Quantum random walks, hidden Markov processes and finitary
processes are put into a unifying model context. In this context, quantum
random walks are seen to not only enjoy nice ergodic properties in general, but
also intuitive quantum-style asymptotic properties. It is also pointed out how
hidden states arising from our framework relate to hidden states in earlier,
prominent treatments on topics such as the EPR paradoxon or Bell's
inequalities.Comment: 26 page
Modelling Probabilistic Wireless Networks
We propose a process calculus to model high level wireless systems, where the
topology of a network is described by a digraph. The calculus enjoys features
which are proper of wireless networks, namely broadcast communication and
probabilistic behaviour. We first focus on the problem of composing wireless
networks, then we present a compositional theory based on a probabilistic
generalisation of the well known may-testing and must-testing pre- orders.
Also, we define an extensional semantics for our calculus, which will be used
to define both simulation and deadlock simulation preorders for wireless
networks. We prove that our simulation preorder is sound with respect to the
may-testing preorder; similarly, the deadlock simulation pre- order is sound
with respect to the must-testing preorder, for a large class of networks. We
also provide a counterexample showing that completeness of the simulation
preorder, with respect to the may testing one, does not hold. We conclude the
paper with an application of our theory to probabilistic routing protocols
Metric Semantics and Full Abstractness for Action Refinement and Probabilistic Choice
This paper provides a case-study in the field of metric semantics for probabilistic programming. Both an operational and a denotational semantics are presented for an abstract process language L_pr, which features action refinement and probabilistic choice. The two models are constructed in the setting of complete ultrametric spaces, here based on probability measures of compact support over sequences of actions. It is shown that the standard toolkit for metric semantics works well in the probabilistic context of L_pr, e.g. in establishing the correctness of the denotational semantics with respect to the operational one. In addition, it is shown how the method of proving full abstraction --as proposed recently by the authors for a nondeterministic language with action refinement-- can be adapted to deal with the probabilistic language L_pr as well
Characterising Probabilistic Processes Logically
In this paper we work on (bi)simulation semantics of processes that exhibit
both nondeterministic and probabilistic behaviour. We propose a probabilistic
extension of the modal mu-calculus and show how to derive characteristic
formulae for various simulation-like preorders over finite-state processes
without divergence. In addition, we show that even without the fixpoint
operators this probabilistic mu-calculus can be used to characterise these
behavioural relations in the sense that two states are equivalent if and only
if they satisfy the same set of formulae.Comment: 18 page
Computation in Finitary Stochastic and Quantum Processes
We introduce stochastic and quantum finite-state transducers as
computation-theoretic models of classical stochastic and quantum finitary
processes. Formal process languages, representing the distribution over a
process's behaviors, are recognized and generated by suitable specializations.
We characterize and compare deterministic and nondeterministic versions,
summarizing their relative computational power in a hierarchy of finitary
process languages. Quantum finite-state transducers and generators are a first
step toward a computation-theoretic analysis of individual, repeatedly measured
quantum dynamical systems. They are explored via several physical systems,
including an iterated beam splitter, an atom in a magnetic field, and atoms in
an ion trap--a special case of which implements the Deutsch quantum algorithm.
We show that these systems' behaviors, and so their information processing
capacity, depends sensitively on the measurement protocol.Comment: 25 pages, 16 figures, 1 table; http://cse.ucdavis.edu/~cmg; numerous
corrections and update
- ā¦