Spin fluctuations and pairing symmetry in Ax_{x}Fe2−y_{2-y}Se2_{2}: dual effect of the itinerant and the localized nature of electrons

We investigate the spin fluctuations and the pairing symmetry in A$_{x}$Fe$_{2-y}$Se$_{2}$ by the fluctuation exchange approximation. Besides the on-site interactions, the next-nearest-neighbor antiferromagnetic coupling $J_{2}$ is also included. We find that both the itinerant and the localized natures of electrons are important to describe the recent experimental results of the spin fluctuations and the pairing symmetry. In particular, a small $J_{2}$ coupling can change the pairing gap from the d-wave symmetry to the s-wave symmetry. We have also studied the real-space structures of the gap functions for different orbits in order to gain more insight on the nature of the pairing mechanism.Comment: 8 pages, 6 figure

Time-resolved quantum spin transport through an Aharonov-Casher ring

After obtaining an exact analytical time-varying solution for the Aharonov-Casher conducting ring embedded in a textured static/dynamic electric field, we investigate the spin-resolved quantum transport in the structure. It is shown that the interference patterns are governed by not only the Aharonov-Casher geometry phase but also the instantaneous phase difference of spin precession through different traveling paths. This dynamic phase is determined by the strength of applied electric field and can have substantial effects on the charge/spin conductances, especially in the weak field regime as the period of spin precession comparable to that of the orbital motion. Our studies suggest that a low-frequency normal electric field with moderate strength possesses more degrees of freedom for manipulating the spin interference of incident electrons.Comment: 5 pages, 6 figure

Multipartite unextendible entangled basis

The unextendible entangled basis with any arbitrarily given Schmidt number $k$ (UEBk) in $\mathbb{C}^{d_1}\otimes\mathbb{C}^{d_2}$ is proposed in [Phys. Rev. A 90 (2014) 054303], $1<k\leq \min\{d_1,d_2\}$, which is a set of orthonormal entangled states with Schmidt number $k$ in a $d_1\otimes d_2$ system consisting of fewer than $d_1d_2$ vectors which have no additional entangled vectors with Schmidt number $k$ in the complementary space. In this paper, we extend it to multipartite case and a general way of constructing $(m+1)$-partite UEBk from $m$-partite UEBk is proposed ($m\geq 2$). Consequently, we show that there are infinitely many UEBks in $\mathbb{C}^{d_1}\otimes\mathbb{C}^{d_2}\otimes\cdots\otimes\mathbb{C}^{d_N}$ with any dimensions and any $N\geq3$.Comment: 16 pages. Some minors are correcte

Parallel D2-Clustering: Large-Scale Clustering of Discrete Distributions

The discrete distribution clustering algorithm, namely D2-clustering, has demonstrated its usefulness in image classification and annotation where each object is represented by a bag of weighed vectors. The high computational complexity of the algorithm, however, limits its applications to large-scale problems. We present a parallel D2-clustering algorithm with substantially improved scalability. A hierarchical structure for parallel computing is devised to achieve a balance between the individual-node computation and the integration process of the algorithm. Additionally, it is shown that even with a single CPU, the hierarchical structure results in significant speed-up. Experiments on real-world large-scale image data, Youtube video data, and protein sequence data demonstrate the efficiency and wide applicability of the parallel D2-clustering algorithm. The loss in clustering accuracy is minor in comparison with the original sequential algorithm

Periodically Driven Holographic Superconductor

As a first step towards our holographic investigation of the far-from-equilibrium physics of periodically driven systems at strong coupling, we explore the real time dynamics of holographic superconductor driven by a monochromatically alternating electric field with various frequencies. As a result, our holographic superconductor is driven to the final oscillating state, where the condensate is suppressed and the oscillation frequency is controlled by twice of the driving frequency. In particular, in the large frequency limit, the three distinct channels towards the final steady state are found, namely under damped to superconducting phase, over damped to superconducting and normal phase, which can be captured essentially by the low lying spectrum of quasi-normal modes in the time averaged approximation, reminiscent of the effective field theory perspective.Comment: JHEP style, 1+18 pages, 10 figures, version to appear in JHE

Image Quality Assessment for Omnidirectional Cross-reference Stitching

Along with the development of virtual reality (VR), omnidirectional images play an important role in producing multimedia content with immersive experience. However, despite various existing approaches for omnidirectional image stitching, how to quantitatively assess the quality of stitched images is still insufficiently explored. To address this problem, we establish a novel omnidirectional image dataset containing stitched images as well as dual-fisheye images captured from standard quarters of 0$^\circ$, 90$^\circ$, 180$^\circ$ and 270$^\circ$. In this manner, when evaluating the quality of an image stitched from a pair of fisheye images (e.g., 0$^\circ$ and 180$^\circ$), the other pair of fisheye images (e.g., 90$^\circ$ and 270$^\circ$) can be used as the cross-reference to provide ground-truth observations of the stitching regions. Based on this dataset, we further benchmark six widely used stitching models with seven evaluation metrics for IQA. To the best of our knowledge, it is the first dataset that focuses on assessing the stitching quality of omnidirectional images

Relativistic correction to gluon fragmentation function into pseudoscalar quarkonium

Inspired by the recent measurements of the $\eta_c$ meson production at LHC, we investigate the relativistic correction effect for the fragmentation function of the gluon into $\eta_c$, which constitutes the crucial nonperturbative elements to understand $\eta_c$ production at high $p_T$. Employing three distinct methods, we calculate the leading relativistic correction to the $g\to\eta_c$ fragmentation function in the NRQCD factorization framework, as well as verify the existing NLO result for the $c\to \eta_c$ fragmentation function. We also study the evolution behavior of these fragmentation functions with the aid of DGLAP equation.Comment: 15 pages, 4 figures, 1 table, submitted to Chinese Physics

Getting the Most from Detection of Galactic Supernova Neutrinos in Future Large Liquid-Scintillator Detectors

Future large liquid-scintillator detectors can be implemented to observe neutrinos from a core-collapse supernova (SN) in our galaxy in various reaction channels: (1) The inverse beta decay $\overline{\nu}^{}_e + p \to n + e^+$; (2) The elastic neutrino-proton scattering $\nu + p \to \nu + p$; (3) The elastic neutrino-electron scattering $\nu + e^- \to \nu + e^-$; (4) The charged-current $\nu^{}_e$ interaction $\nu^{}_e + {^{12}}{\rm C} \to e^- + {^{12}}{\rm N}$; (5) The charged-current $\overline{\nu}^{}_e$ interaction $\overline{\nu}^{}_e + {^{12}}{\rm C} \to e^+ + {^{12}}{\rm B}$; (6) The neutral-current interaction $\nu + {^{12}}{\rm C} \to \nu + {^{12}}{\rm C}^*$. The less abundant $^{13}{\rm C}$ atoms in the liquid scintillator are also considered as a target, and both the charged-current interaction $\nu^{}_e + {^{13}}{\rm C} \to e^- + {^{13}}{\rm N}$ and the neutral-current interaction $\nu + {^{13}}{\rm C} \to \nu + {^{13}}{\rm C}^*$ are taken into account. In this work, we show for the first time that a global analysis of all these channels at a single {liquid-}scintillator detector, such as Jiangmen Underground Neutrino Observatory (JUNO), is very important to test the average-energy hierarchy of SN neutrinos and how the total energy is partitioned among neutrino flavors. In addition, the dominant channels for reconstructing neutrino spectra and the impact of other channels are discussed in great detail.Comment: 24 pages, 6 figures, Adding the C13 CC and NC interaction channels, more discussions and reference

Sequential Dual Deep Learning with Shape and Texture Features for Sketch Recognition

Recognizing freehand sketches with high arbitrariness is greatly challenging. Most existing methods either ignore the geometric characteristics or treat sketches as handwritten characters with fixed structural ordering. Consequently, they can hardly yield high recognition performance even though sophisticated learning techniques are employed. In this paper, we propose a sequential deep learning strategy that combines both shape and texture features. A coded shape descriptor is exploited to characterize the geometry of sketch strokes with high flexibility, while the outputs of constitutional neural networks (CNN) are taken as the abstract texture feature. We develop dual deep networks with memorable gated recurrent units (GRUs), and sequentially feed these two types of features into the dual networks, respectively. These dual networks enable the feature fusion by another gated recurrent unit (GRU), and thus accurately recognize sketches invariant to stroke ordering. The experiments on the TU-Berlin data set show that our method outperforms the average of human and state-of-the-art algorithms even when significant shape and appearance variations occur.Comment: 8 pages, 8 figure

Mask Propagation Network for Video Object Segmentation

In this work, we propose a mask propagation network to treat the video segmentation problem as a concept of the guided instance segmentation. Similar to most MaskTrack based video segmentation methods, our method takes the mask probability map of previous frame and the appearance of current frame as inputs, and predicts the mask probability map for the current frame. Specifically, we adopt the Xception backbone based DeepLab v3+ model as the probability map predictor in our prediction pipeline. Besides, instead of the full image and the original mask probability, our network takes the region of interest of the instance, and the new mask probability which warped by the optical flow between the previous and current frames as the inputs. We also ensemble the modified One-Shot Video Segmentation Network to make the final predictions in order to retrieve and segment the missing instance