Profiles of thermal line emission from advection dominated accretion flows

Recently, Narayan & Raymond (1999) proposed that the thermal emission lines from the hot plasma in advection dominated accretion flows (ADAFs) are potentially observable with the next generation of X-ray observatories, with which the physical properties of some X-ray sources can be probed. In ADAFs, the temperature of the ion is so high that the thermal broadening of the line is important. We calculate the profiles of thermal line emission from ADAFs, in which both the thermal and Doppler broadening have been considered. It is found that the double-peaked profiles are present for high inclination angles between the axis of disk and the line of sight. The double-peaked profiles are smeared in low inclination cases, and completely disappear while the inclination angle is less than $15^{\circ}$, where the thermal and turbulent broadening dominated on the line profiles. We also note that the thermal line profile is affected by the location of the transition radius of ADAF. The self-similar height-integrated disk structure and the emissivity with power-law dependence of radius are adopted in our calculations. The results obtained in this work can be used as a diagnosis on the future X-ray observations of the thermal lines. Some important physical quantities of ADAFs could be inferred from future thermal line observations.Comment: 7 page

The perfect spin injection in silicene FS/NS junction

We theoretically investigate the spin injection from a ferromagnetic silicene to a normal silicene (FS/NS), where the magnetization in the FS is assumed from the magnetic proximity effect. Based on a silicene lattice model, we demonstrated that the pure spin injection could be obtained by tuning the Fermi energy of two spin species, where one is in the spin orbit coupling gap and the other one is outside the gap. Moreover, the valley polarity of the spin species can be controlled by a perpendicular electric field in the FS region. Our findings may shed light on making silicene-based spin and valley devices in the spintronics and valleytronics field.Comment: 6 pages, 3 figure

Classification and Ranking of Fermi LAT Gamma-ray Sources from the 3FGL Catalog using Machine Learning Techniques

We apply a number of statistical and machine learning techniques to classify and rank gamma-ray sources from the Third Fermi Large Area Telescope (LAT) Source Catalog (3FGL), according to their likelihood of falling into the two major classes of gamma-ray emitters: pulsars (PSR) or Active Galactic Nuclei (AGN). Using 1904 3FGL sources that have been identified/associated with AGN (1738) and PSR (166), we train (using 70% of our sample) and test (using 30%) our algorithms and find that the best overall accuracy (>96%) is obtained with the Random Forest (RF) technique, while using a logistic regression (LR) algorithm results in only marginally lower accuracy. We apply the same techniques on a sub-sample of 142 known gamma-ray pulsars to classify them into two major subcategories: young (YNG) and millisecond pulsars (MSP). Once more, the RF algorithm has the best overall accuracy (~90%), while a boosted LR analysis comes a close second. We apply our two best models (RF and LR) to the entire 3FGL catalog, providing predictions on the likely nature of {\it unassociated} sources, including the likely type of pulsar (YNG or MSP). We also use our predictions to shed light on the possible nature of some gamma-ray sources with known associations (e.g. binaries, SNR/PWN). Finally, we provide a list of plausible X-ray counterparts for some pulsar candidates, obtained using Swift, Chandra, and XMM. The results of our study will be of interest for both in-depth follow-up searches (e.g. pulsar) at various wavelengths, as well as for broader population studies.Comment: Accepted by Ap