A large accretion disk of extreme eccentricity in the TDE ASASSN-14li

In the canonical model for tidal disruption events (TDEs), the stellar debris circularizes quickly to form an accretion disk of size about twice the orbital pericenter of the star. Most TDEs and candidates discovered in the optical/UV have broad optical emission lines with complex and diverse profiles of puzzling origin. Liu et al. recently developed a relativistic elliptical disk model of constant eccentricity in radius for the broad optical emission lines of TDEs and well reproduced the double-peaked line profiles of the TDE candidate PTF09djl with a large and extremely eccentric accretion disk. In this paper, we show that the optical emission lines of the TDE ASASSN-14li with radically different profiles are well modelled with the relativistic elliptical disk model, too. The accretion disk of ASASSN-14li has an eccentricity 0.97 and semimajor axis of 847 times the Schwarzschild radius (r_S) of the black hole (BH). It forms as the consequence of tidal disruption of a star passing by a massive BH with orbital pericenter 25r_S. The optical emission lines of ASASSN-14li are powered by an extended X-ray source of flat radial distribution overlapping the bulk of the accretion disk and the single-peaked asymmetric line profiles are mainly due to the orbital motion of the emitting matter within the disk plane of inclination about 26\degr and of pericenter orientation closely toward the observer. Our results suggest that modelling the complex line profiles is powerful in probing the structures of accretion disks and coronal X-ray sources in TDEs.Comment: 10 pages, 8 figures, accepted for publication in the MNRA

Isotropic and Anisotropic Regimes of the Field-Dependent Spin Dynamics in Sr2IrO4: Raman Scattering Studies

A major focus of experimental interest in Sr2IrO4 has been to clarify how the magnetic excitations of this strongly spin-orbit coupled system differ from the predictions of anisotropic 2D spin-1/2 Heisenberg model and to explore the extent to which strong spin-orbit coupling affects the magnetic properties of iridates. Here, we present a high-resolution inelastic light (Raman) scattering study of the low energy magnetic excitation spectrum of Sr2IrO4 and doped Eu-doped Sr2IrO4 as functions of both temperature and applied magnetic field. We show that the high-field (H>1.5 T) in-plane spin dynamics of Sr2IrO4 are isotropic and governed by the interplay between the applied field and the small in-plane ferromagnetic spin components induced by the Dzyaloshinskii-Moriya interaction. However, the spin dynamics of Sr2IrO4 at lower fields (H<1.5 T) exhibit important effects associated with interlayer coupling and in-plane anisotropy, including a spin-flop transition at Hc in Sr2IrO4 that occurs either discontinuously or via a continuous rotation of the spins, depending upon the in-plane orientation of the applied field. These results show that in-plane anisotropy and interlayer coupling effects play important roles in the low-field magnetic and dynamical properties of Sr2IrO4.Comment: 8 pages, 4 figures, submitte

A Stacked Multi-Granularity Convolution Denoising Auto-Encoder

With the development of big data, artificial intelligence has provided many intelligent solutions to urban life. For instance, an image-based intelligent technology, such as image classification of diseases, is widely used in daily life. However, the image in real life is mostly unlabeled, so the performance of many image-based intelligent models shows limitations. Therefore, how to use a large amount of unlabeled image data to build an efficient and high-quality model for better urban life has been an urgent research topic. In this paper, we propose an unsupervised image feature extraction method that is referred to as a stacked multi-granularity convolution denoising auto-encoder (SMGCDAE). The algorithm is based on a convolutional neural network (CNN), yet it introduces a multi-granularity kernel. This approach resolved issues with image unicity by extracting a diverse category of high-level features. In addition, the denoising auto-encoder ensures stability and improves the classification accuracy by extracting more robust features. The algorithm was assessed using three image benchmark datasets and a series of meningitis images, achieving higher average accuracy than other methods. These results suggest that the algorithm is capable of extracting more discriminative high-level features and thus offers superior performance compared with the existing methodologies

Tuning Jeff = 1/2 Insulating State via Electron Doping and Pressure in Double-Layered Iridate Sr3Ir2O7

Sr3Ir2O7 exhibits a novel Jeff=1/2 insulating state that features a splitting between Jeff=1/2 and 3/2 bands due to spin-orbit interaction. We report a metal-insulator transition in Sr3Ir2O7 via either dilute electron doping (La3+ for Sr2+) or application of high pressure up to 35 GPa. Our study of single-crystal Sr3Ir2O7 and (Sr1-xLax)3Ir2O7 reveals that application of high hydrostatic pressure P leads to a drastic reduction in the electrical resistivity by as much as six orders of magnitude at a critical pressure, PC = 13.2 GPa, manifesting a closing of the gap; but further increasing P up to 35 GPa produces no fully metallic state at low temperatures, possibly as a consequence of localization due to a narrow distribution of bonding angles {\theta}. In contrast, slight doping of La3+ ions for Sr2+ ions in Sr3Ir2O7 readily induces a robust metallic state in the resistivity at low temperatures; the magnetic ordering temperature is significantly suppressed but remains finite for (Sr0.95La0.05)3Ir2O7 where the metallic state occurs. The results are discussed along with comparisons drawn with Sr2IrO4, a prototype of the Jeff = 1/2 insulator.Comment: five figure