The Shannon capacity of a graph G is the maximum asymptotic rate at which messages can be sent with zero probability of error through a noisy channel with confusability graph G. This extensively studied graph parameter disregards the fact that on atomic scales, nature behaves in line with quantum mechanics. Entanglement, arguably the most counterintuitive feature of the theory, turns out to be ...

The well-studied Vámos matroid has provided a wealth of interesting theoretical results in matroid theory. We use the Vámos matroid to construct a new network, which we call the Vámos network. We then exploit the Vámos network to answer in the negative the open question as to whether Shannon-type information inequalities are in general sufficient for computing network coding capacities. To acco...

Fading broadcast channels have been studied extensively over the past 30 years and the Shannon capacity of these channels is well established. This paper examines the Shannon capacity of two-user fading broadcast channel using superposition coding and assuming perfect channel information at both the receiver and transmitter with the additional constraint of maintaining minimum data rates for bo...

We study the relation between the stable throughput regions and the capacity regions for a Gaussian multiple-access channel. Our main focus is to study how the extent of side information about source arrival statistics and/or instantaneous queue states at each transmitter influence the achievable stable throughput region. Two notions of MAC capacity are studied. The first notion is the conventi...

We consider axiomatically the problem of estimating the strength of a conditional dependence relationship PY |X from a random variables X to a random variable Y . This has applications in determining the strength of a known causal relationship, where the strength depends only on the conditional distribution of the effect given the cause (and not on the driving distribution of the cause). Shanno...

We consider axiomatically the problem of estimating the strength of a conditional dependence relationship PY |X from a random variables X to a random variable Y . This has applications in determining the strength of a known causal relationship, where the strength depends only on the conditional distribution of the effect given the cause (and not on the driving distribution of the cause). Shanno...

We provide a novel definition of quantitative information flow, called transmissible information, that is suitable for reasoning about informational-theoretically secure (or non-cryptographic) systems, as well as about cryptographic systems with their polynomially bounded adversaries, error probabilities, etc. Transmissible information captures deliberate communication between two processes, an...