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 Sr2_2RuO4_4?

Until recently it has been believed that the superconductivity in Sr$_2$RuO$_4$ is described by p-wave pairing. However, both the recent specific heat and the magnetic penetration depth measurements on the purest single crystals of Sr$_2$RuO$_4$ 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 $H \ll H_{c2}$ and $T \ll T_{c}$, which should be readily accessible experimentally.Comment: 6 pages, 2 figure

Resonant impurity scattering in the ±\pms-gap state of the Fe-based superconductors

We study the impurity scattering on the $\pm$s-wave superconductor, with realistic parameters for the Fe-pnictide superconductors. Using $\mathcal{T}$-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 ($1/T_1 \approx T^{\alpha}$ ; $\alpha \approx 3$), 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,