19,004 research outputs found
Spin-orbit scattering in d-wave superconductors
When non-magnetic impurities are introduced in a d-wave superconductor, both
thermodynamic and spectral properties are strongly affected if the impurity
potential is close to the strong resonance limit. In addition to the scalar
impurity potential, the charge carriers are also spin-orbit coupled to the
impurities. Here it is shown that (i) close to the unitarity limit for the
impurity scattering, the spin-orbit contribution is of the same order of
magnitude than the scalar scattering and cannot be neglected, (ii) the
spin-orbit scattering is pair-breaking and (iii) induces a small id_xy
component to the off-diagonal part of the self-energy.Comment: 9 pages, 3 postscript figures, euromacr.tex-europhys.sty, submitted
to Europhysics Letter
Possible f-wave superconductivity in SrRuO?
Until recently it has been believed that the superconductivity in
SrRuO is described by p-wave pairing. However, both the recent specific
heat and the magnetic penetration depth measurements on the purest single
crystals of SrRuO appear to be explained more consistently in terms of
f-wave superconductivity. In order to further this hypothesis, we study
theoretically the thermodynamics and thermal conductivity of f-wave
superconductors in a planar magnetic field. We find the simple expressions for
these quantities when and , which should be
readily accessible experimentally.Comment: 6 pages, 2 figure
Resonant impurity scattering in the s-gap state of the Fe-based superconductors
We study the impurity scattering on the s-wave superconductor, with
realistic parameters for the Fe-pnictide superconductors. Using
-matrix method, generalized for the two bands, we found that
impurity scattering of the unitary limit forms off-centered bound states inside
of the superconducting gap, which modifies, surprisingly, the density of states
(DOS) of a fully opened gap to a V-shaped one as in the case of a d-wave
superconductor. This behavior provides coherent explanations to the several
conflicting experimental issues of the Fe-pnictide superconductors: the
V-shaped DOS but with an isotropic gap observed in the photoemission and
tunneling experiments; the power law behavior of the nuclear spin-lattice
relaxation rate ( ; ), down to very
low temperatures.Comment: 5 pages, 3 figures, Revisions of Figures and their captions;
references update
A Package for the Automated Classification of Periodic Variable Stars
We present a machine learning package for the classification of periodic
variable stars. Our package is intended to be general: it can classify any
single band optical light curve comprising at least a few tens of observations
covering durations from weeks to years, with arbitrary time sampling. We use
light curves of periodic variable stars taken from OGLE and EROS-2 to train the
model. To make our classifier relatively survey-independent, it is trained on
16 features extracted from the light curves (e.g. period, skewness, Fourier
amplitude ratio). The model classifies light curves into one of seven
superclasses - Delta Scuti, RR Lyrae, Cepheid, Type II Cepheid, eclipsing
binary, long-period variable, non-variable - as well as subclasses of these,
such as ab, c, d, and e types for RR Lyraes. When trained to give only
superclasses, our model achieves 0.98 for both recall and precision as measured
on an independent validation dataset (on a scale of 0 to 1). When trained to
give subclasses, it achieves 0.81 for both recall and precision. In order to
assess classification performance of the subclass model, we applied it to the
MACHO, LINEAR, and ASAS periodic variables, which gave recall/precision of
0.92/0.98, 0.89/0.96, and 0.84/0.88, respectively. We also applied the subclass
model to Hipparcos periodic variable stars of many other variability types that
do not exist in our training set, in order to examine how much those types
degrade the classification performance of our target classes. In addition, we
investigate how the performance varies with the number of data points and
duration of observations. We find that recall and precision do not vary
significantly if the number of data points is larger than 80 and the duration
is more than a few weeks. The classifier software of the subclass model is
available from the GitHub repository (https://goo.gl/xmFO6Q).Comment: 16 pages, 11 figures, accepted for publication in A&
ACREAGE RESPONSES TO EXPECTED REVENUES AND PRICE RISK FOR MINOR OILSEEDS AND PROGRAM CROPS IN THE NORTHERN PLAINS
Wheat, barely, flaxseed, and oilseed sunflower acreage respond to different economic variables. Wheat and barely acreage must be divided among program-complying, program-planted, and nonprogram-planted acreage because these categories respond to different variables and respond to own expected-revenue and price-risk variables in opposite ways. Flaxseed, sunflower, and nonprogram-planted acreage of wheat and barley have highly significant, positive responses to their own expected revenue and negative responses to their own-price risk. Flaxseed and sunflower acreage have been more responsive to their lagged values than to expected revenues for wheat.Crop Production/Industries,
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