Low Scale Left-Right Symmetry and Warm Dark Matter

We study the scenario of dark matter in the minimal left-right symmetric theory at the TeV scale. The only viable candidate is found to be the lightest right-handed neutrino with a mass of keV. To satisfy the dark matter relic abundance, the relic yield is diluted by late decays of the two heavier neutrinos. We point out that the QCD phase transition temperature coincidences with the typical freeze-out temperature governed by right-handed interactions, which helps to alleviate the problem of overproduction. A careful numerical study reveals a narrow window for the mass of the right-handed gauge boson, within the reach of the LHC.Comment: Article in proceedings of the CETUP* 2012 workshop in Lead, South Dakota; 10 pages, 5 figures, v2: references adde

Tensor Norms and the Classical Communication Complexity of Nonlocal Quantum Measurement

We initiate the study of quantifying nonlocalness of a bipartite measurement by the minimum amount of classical communication required to simulate the measurement. We derive general upper bounds, which are expressed in terms of certain tensor norms of the measurement operator. As applications, we show that (a) If the amount of communication is constant, quantum and classical communication protocols with unlimited amount of shared entanglement or shared randomness compute the same set of functions; (b) A local hidden variable model needs only a constant amount of communication to create, within an arbitrarily small statistical distance, a distribution resulted from local measurements of an entangled quantum state, as long as the number of measurement outcomes is constant.Comment: A preliminary version of this paper appears as part of an article in Proceedings of the the 37th ACM Symposium on Theory of Computing (STOC 2005), 460--467, 200

The Organization and Control of an Evolving Interdependent Population

Starting with Darwin, biologists have asked how populations evolve from a low fitness state that is evolutionarily stable to a high fitness state that is not. Specifically of interest is the emergence of cooperation and multicellularity where the fitness of individuals often appears in conflict with that of the population. Theories of social evolution and evolutionary game theory have produced a number of fruitful results employing two-state two-body frameworks. In this study we depart from this tradition and instead consider a multi-player, multi-state evolutionary game, in which the fitness of an agent is determined by its relationship to an arbitrary number of other agents. We show that populations organize themselves in one of four distinct phases of interdependence depending on one parameter, selection strength. Some of these phases involve the formation of specialized large-scale structures. We then describe how the evolution of independence can be manipulated through various external perturbations.Comment: To download simulation code cf. article in Proceedings of the Royal Society, Interfac

Maximum Segment Sum, Monadically (distilled tutorial, with solutions)

The maximum segment sum problem is to compute, given a list of integers, the largest of the sums of the contiguous segments of that list. This problem specification maps directly onto a cubic-time algorithm; however, there is a very elegant linear-time solution too. The problem is a classic exercise in the mathematics of program construction, illustrating important principles such as calculational development, pointfree reasoning, algebraic structure, and datatype-genericity. Here, we take a sideways look at the datatype-generic version of the problem in terms of monadic functional programming, instead of the traditional relational approach; the presentation is tutorial in style, and leavened with exercises for the reader.Comment: Revision of the article in Proceedings DSL 2011, EPTCS 66, arXiv:1109.0323, to provide solutions to the exercise

Using Ontologies to Query Probabilistic Numerical Data: Extended Version

We consider ontology-based query answering in a setting where some of the data are numerical and of a probabilistic nature, such as data obtained from uncertain sensor readings. The uncertainty for such numerical values can be more precisely represented by continuous probability distributions than by discrete probabilities for numerical facts concerning exact values. For this reason, we extend existing approaches using discrete probability distributions over facts by continuous probability distributions over numerical values. We determine the exact (data and combined) complexity of query answering in extensions of the well-known description logics EL and ALC with numerical comparison operators in this probabilistic setting.This is an extended version of the article in: Proceedings of the 11th International Symposium on Frontiers of Combining Systems. This version has been revised based on the comments of the reviewers