186,363 research outputs found
Zero-error channel capacity and simulation assisted by non-local correlations
Shannon's theory of zero-error communication is re-examined in the broader
setting of using one classical channel to simulate another exactly, and in the
presence of various resources that are all classes of non-signalling
correlations: Shared randomness, shared entanglement and arbitrary
non-signalling correlations. Specifically, when the channel being simulated is
noiseless, this reduces to the zero-error capacity of the channel, assisted by
the various classes of non-signalling correlations. When the resource channel
is noiseless, it results in the "reverse" problem of simulating a noisy channel
exactly by a noiseless one, assisted by correlations. In both cases, 'one-shot'
separations between the power of the different assisting correlations are
exhibited. The most striking result of this kind is that entanglement can
assist in zero-error communication, in stark contrast to the standard setting
of communicaton with asymptotically vanishing error in which entanglement does
not help at all. In the asymptotic case, shared randomness is shown to be just
as powerful as arbitrary non-signalling correlations for noisy channel
simulation, which is not true for the asymptotic zero-error capacities. For
assistance by arbitrary non-signalling correlations, linear programming
formulas for capacity and simulation are derived, the former being equal (for
channels with non-zero unassisted capacity) to the feedback-assisted zero-error
capacity originally derived by Shannon to upper bound the unassisted zero-error
capacity. Finally, a kind of reversibility between non-signalling-assisted
capacity and simulation is observed, mirroring the famous "reverse Shannon
theorem".Comment: 18 pages, 1 figure. Small changes to text in v2. Removed an
unnecessarily strong requirement in the premise of Theorem 1
Towards a navigational logic for graphical structures
One of the main advantages of the Logic of Nested Conditions, defined by Habel and Pennemann, for reasoning about graphs, is its generality: this logic can be used in the framework of many classes of graphs and graphical structures. It is enough that the category of these structures satisfies certain basic conditions.
In a previous paper [14], we extended this logic to be able to deal with graph properties including paths, but this extension was only defined for the category of untyped directed graphs. In addition it seemed difficult to talk about paths abstractly, that is, independently of the given category of graphical structures. In this paper we approach this problem. In particular, given an arbitrary category of graphical structures, we assume that for every object of this category there is an associated edge relation that can be used to define a path relation. Moreover, we consider that edges have some kind of labels and paths can be specified by associating them to a set of label sequences. Then, after the presentation of that general framework, we show how it can be applied to several classes of graphs. Moreover, we present a set of sound inference rules for reasoning in the logic.Peer ReviewedPostprint (author's final draft
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