Neutrino Electromagnetic Form Factor and Oscillation Effects on Neutrino Interaction With Dense Matter

The mean free path of neutrino - free electron gas interaction has been calculated by taking into account the neutrino electromagnetic form factors and the possibility of neutrino oscillation. It is shown that the form factor effect becomes significant for a neutrino magnetic moment \mu_\nu > 10^{-10} mu_B and for a neutrino radius R > 10^{-6} MeV^{-1}. The mean free path is found to be sensitive to the nu_e-nu_mu and nu_e-nu_e^R transition probabilities.Comment: 4 pages, 3 eps figures, accepted for publication in Phys. Rev.

Neutron Fraction and Neutrino Mean Free Path Predictions in Relativistic Mean Field Models

The equation of state (EOS) of dense matter and neutrino mean free path (NMFP) in a neutron star have been studied by using relativistic mean field models motivated by effective field theory (ERMF). It is found that the models predict too large proton fractions, although one of the models (G2) predicts an acceptable EOS. This is caused by the isovector terms. Except G2, the other two models predict anomalous NMFP. In order to minimize the anomaly, besides an acceptable EOS, a large M* is favorable. A model with large M* retains the regularity in the NMFP even for a small neutron fraction.Comment: 4 pages, 5 figures, accepted for publication in Phys. Rev.

Deterministic dense coding and entanglement entropy

We present an analytical study of the standard two-party deterministic dense-coding protocol, under which communication of perfectly distinguishable messages takes place via a qudit from a pair of non-maximally entangled qudits in pure state |S>. Our results include the following: (i) We prove that it is possible for a state |S> with lower entanglement entropy to support the sending of a greater number of perfectly distinguishable messages than one with higher entanglement entropy, confirming a result suggested via numerical analysis in Mozes et al. [Phys. Rev. A 71 012311 (2005)]. (ii) By explicit construction of families of local unitary operators, we verify, for dimensions d = 3 and d=4, a conjecture of Mozes et al. about the minimum entanglement entropy that supports the sending of d + j messages, j = 2, ..., d-1; moreover, we show that the j=2 and j= d-1 cases of the conjecture are valid in all dimensions. (iii) Given that |S> allows the sending of K messages and has the square roof of c as its largest Schmidt coefficient, we show that the inequality c <= d/K, established by Wu et al. [ Phys. Rev. A 73, 042311 (2006)], must actually take the form c < d/K if K = d+1, while our constructions of local unitaries show that equality can be realized if K = d+2 or K = 2d-1.Comment: 19 pages, 2 figures. Published versio

Neutrino Electromagnetic Form Factors Effect on the Neutrino Cross Section in Dense Matter

The sensitivity of the differential cross section of the interaction between neutrino-electron with dense matter to the possibly nonzero neutrino electromagnetic properties has been investigated. Here, the relativistic mean field model inspired by effective field theory has been used to describe non strange dense matter, both with and without the neutrino trapping. We have found that the cross section becomes more sensitive to the constituent distribution of the matter, once electromagnetic properties of the neutrino are taken into account. The effects of electromagnetic properties of neutrino on the cross section become more significant for the neutrino magnetic moment mu_nu > 10^{-10} mu_B and for the neutrino charge radius R > 10^{-5} MeV^{-1}.Comment: 24 pages, 10 figures, submitted to Physical Review

Social Sensing of Floods in the UK

"Social sensing" is a form of crowd-sourcing that involves systematic analysis of digital communications to detect real-world events. Here we consider the use of social sensing for observing natural hazards. In particular, we present a case study that uses data from a popular social media platform (Twitter) to detect and locate flood events in the UK. In order to improve data quality we apply a number of filters (timezone, simple text filters and a naive Bayes `relevance' filter) to the data. We then use place names in the user profile and message text to infer the location of the tweets. These two steps remove most of the irrelevant tweets and yield orders of magnitude more located tweets than we have by relying on geo-tagged data. We demonstrate that high resolution social sensing of floods is feasible and we can produce high-quality historical and real-time maps of floods using Twitter.Comment: 24 pages, 6 figure