102,644 research outputs found
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
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