6,199 research outputs found
The mass distribution of Galactic double neutron stars
The conventional wisdom, dating back to 2012, is that the mass distribution
of Galactic double neutron stars is well-fit by a Gaussian distribution with a
mean of and a width of . With the recent discovery
of new Galactic double neutron stars and GW170817, the first neutron star
merger event to be observed with gravitational waves, it is timely to revisit
this model. In order to constrain the mass distribution of double neutron
stars, we perform Bayesian inference using a sample of 17 Galactic double
neutron stars effectively doubling the sample used in previous studies. We
expand the space of models so that the recycled neutron star need not be drawn
from the same distribution as the non-recycled companion. Moreover, we consider
different functional forms including uniform, single-Gaussian, and two-Gaussian
distributions. While there is insufficient data to draw firm conclusions, we
find positive support (a Bayes factor of 9) for the hypothesis that recycled
and non-recycled neutron stars have distinct mass distributions. The most
probable model---preferred with a Bayes factor of 29 over the conventional
model---is one in which the recycled neutron star mass is distributed according
to a two-Gaussian distribution and the non-recycled neutron star mass is
distributed uniformly. We show that precise component mass measurements of
double neutron stars are required in order to determine with high
confidence (a Bayes factor of 150) if recycled and non-recycled neutron stars
come from a common distribution. Approximately are needed in order to
establish the detailed shape of the distributions.Comment: Minor update of PSR J1913+1102 masses, 13 pages, 7 figures, 5 table
The Lifecycles of Apps in a Social Ecosystem
Apps are emerging as an important form of on-line content, and they combine
aspects of Web usage in interesting ways --- they exhibit a rich temporal
structure of user adoption and long-term engagement, and they exist in a
broader social ecosystem that helps drive these patterns of adoption and
engagement. It has been difficult, however, to study apps in their natural
setting since this requires a simultaneous analysis of a large set of popular
apps and the underlying social network they inhabit.
In this work we address this challenge through an analysis of the collection
of apps on Facebook Login, developing a novel framework for analyzing both
temporal and social properties. At the temporal level, we develop a retention
model that represents a user's tendency to return to an app using a very small
parameter set. At the social level, we organize the space of apps along two
fundamental axes --- popularity and sociality --- and we show how a user's
probability of adopting an app depends both on properties of the local network
structure and on the match between the user's attributes, his or her friends'
attributes, and the dominant attributes within the app's user population. We
also develop models that show the importance of different feature sets with
strong performance in predicting app success.Comment: 11 pages, 10 figures, 3 tables, International World Wide Web
Conferenc
Imaging and manipulating electrons in a 1D quantum dot with Coulomb blockade microscopy
Motivated by the recent experiments by the Westervelt group using a mobile
tip to probe the electronic state of quantum dots formed on a segmented
nanowire, we study the shifts in Coulomb blockade peak positions as a function
of the spatial variation of the tip potential, which can be termed "Coulomb
blockade microscopy". We show that if the tip can be brought sufficiently close
to the nanowire, one can distinguish a high density electronic liquid state
from a Wigner crystal state by microscopy with a weak tip potential. In the
opposite limit of a strongly negative tip potential, the potential depletes the
electronic density under it and divides the quantum wire into two partitions.
There the tip can push individual electrons from one partition to the other,
and the Coulomb blockade micrograph can clearly track such transitions. We show
that this phenomenon can be used to qualitatively estimate the relative
importance of the electron interaction compared to one particle potential and
kinetic energies. Finally, we propose that a weak tip Coulomb blockade
micrograph focusing on the transition between electron number N=0 and N=1
states may be used to experimentally map the one-particle potential landscape
produced by impurities and inhomogeneities.Comment: 4 pages 7 figure
Quantitative Ultrasound and B-mode Image Texture Features Correlate with Collagen and Myelin Content in Human Ulnar Nerve Fascicles
We investigate the usefulness of quantitative ultrasound (QUS) and B-mode
texture features for characterization of ulnar nerve fascicles. Ultrasound data
were acquired from cadaveric specimens using a nominal 30 MHz probe. Next, the
nerves were extracted to prepare histology sections. 85 fascicles were matched
between the B-mode images and the histology sections. For each fascicle image,
we selected an intra-fascicular region of interest. We used histology sections
to determine features related to the concentration of collagen and myelin, and
ultrasound data to calculate backscatter coefficient (-24.89 dB 8.31),
attenuation coefficient (0.92 db/cm-MHz 0.04), Nakagami parameter (1.01
0.18) and entropy (6.92 0.83), as well as B-mode texture features
obtained via the gray level co-occurrence matrix algorithm. Significant
Spearman's rank correlations between the combined collagen and myelin
concentrations were obtained for the backscatter coefficient (R=-0.68), entropy
(R=-0.51), and for several texture features. Our study demonstrates that QUS
may potentially provide information on structural components of nerve
fascicles
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