arXiv subjects

Xiaoyu Wang

Publications and source records attributed to Xiaoyu Wang.

279 records · Page 16Linked to original sources

arXiv2015

A phenomenological study on the $\cosϕ_h$ azimuthal asymmetry in double longitudinally Polarized SIDIS

We study the $\cos{ϕ_h}$ azimuthal asymmetry in double polarized semi-inclusive pion production by considering dynamical twist-3 effects. In particular, we evaluate the role of the transverse momentum dependent distributions $e_L(x, k_T^2)$ and $g_L^\perp(x, k_T^2)$ on the asymmetry. Using two different sets of spectator model results for these distributions, we predict the $\cos{ϕ_h}$ asymmetry of $π^+$, $π^-$, and $π^0$ at the kinematic configuration available at CLAS, HERMES and COMPASS. Our estimates show that the asymmetries are positive for all the pions and could be accessed by CLAS and HERMES. We also find that $g_L^\perp$ gives the dominant contribution to the $\cosϕ_h$ asymmetry, while the contribution of $e_L$ is almost negligible.

hep-ph↗

arXiv2015

Magnetic order without tetragonal-symmetry-breaking in iron arsenides: microscopic mechanism and spin-wave spectrum

Most iron-based superconductors undergo a transition to a magnetically ordered state characterized by staggered stripes of parallel spins. With ordering vectors $(π,0)$ or $(0,π)$, this magnetic state breaks the high-temperature tetragonal symmetry of the system, which is manifested by a splitting of the lattice Bragg peaks. Remarkably, recent experiments in hole-doped iron arsenides reported an ordered state that displays magnetic Bragg peaks at $(π,0)$ and $(0,π)$ but remains tetragonal. Despite being inconsistent with a magnetic stripe configuration, this unusual magnetic phase can be described in terms of a double-$\mathbf{Q}$ magnetic structure consisting of an equal-weight superposition of the ordering vectors $(π,0)$ and $(0,π)$. Here we show that a non-collinear double-$\mathbf{Q}$ magnetic configuration, dubbed \emph{orthomagnetic}, arises naturally within an itinerant three-band microscopic model for the iron pnictides. In particular, we find that strong deviations from perfect nesting and residual interactions between the electron pockets favor the orthomagnetic over the stripe magnetic state. Using an effective low-energy model, we also calculate the spin-wave spectrum of the orthomagnetic state. In contrast to the stripe state, there are three Goldstone modes, manifested in all diagonal and one off-diagonal component of the spin-spin correlation function. The total magnetic structure factor displays two anisotropic spin-wave branches emerging from both $(π,0)$ and $(0,π)$ momenta, in contrast to the case of domains of stripe order, where only one spin-wave branch emerges from each momentum. We propose that these unique features of the orthomagnetic state can be used to unambiguously distinguish it from the stripe state via neutron scattering experiments, and discuss the implications of its existence to the nature of the magnetism of the iron arsenides.

cond-mat.supr-con↗

arXiv2014

Interplay between tetragonal magnetic order, stripe magnetism, and superconductivity in iron-based materials

Motivated by recent experiments in Ba$_{1-x}$K$_{x}$Fe$_{2}$As$_{2}$ {[}A. E. Böhmer \textit{et al}, to be published{]}, we analyze the type of spin-density wave (SDW) order in doped iron-pnictides and the discontinuities of the superconducting transition temperature $T_{c}$ in the coexistence phase with SDW magnetism. By tracking the magnetic transition line $T_{N}(x)$ towards optimal doping within an itinerant fermionic model, we find a sequence of transitions from the stripe-orthorhombic ($C_{2}$) SDW order to the tetragonal ($C_{4}$) order and then back to the $C_{2}$ order. We argue that the superconducting $T_{c}$ has two discontinuities -- it jumps to a smaller value upon entering the coexistence region with the $C_{4}$ magnetic phase, and then jumps to a larger value inside the SDW state when it crosses the boundary between the $C_{4}$ and $C_{2}$ SDW orders. The full agreement with the experimental phase diagram provides a strong indication that the itinerant approach is adequate to describe the physics of weakly/moderately doped iron-pnictides.

cond-mat.str-el↗

arXiv2014

Object-centric Sampling for Fine-grained Image Classification

This paper proposes to go beyond the state-of-the-art deep convolutional neural network (CNN) by incorporating the information from object detection, focusing on dealing with fine-grained image classification. Unfortunately, CNN suffers from over-fiting when it is trained on existing fine-grained image classification benchmarks, which typically only consist of less than a few tens of thousands training images. Therefore, we first construct a large-scale fine-grained car recognition dataset that consists of 333 car classes with more than 150 thousand training images. With this large-scale dataset, we are able to build a strong baseline for CNN with top-1 classification accuracy of 81.6%. One major challenge in fine-grained image classification is that many classes are very similar to each other while having large within-class variation. One contributing factor to the within-class variation is cluttered image background. However, the existing CNN training takes uniform window sampling over the image, acting as blind on the location of the object of interest. In contrast, this paper proposes an \emph{object-centric sampling} (OCS) scheme that samples image windows based on the object location information. The challenge in using the location information lies in how to design powerful object detector and how to handle the imperfectness of detection results. To that end, we design a saliency-aware object detection approach specific for the setting of fine-grained image classification, and the uncertainty of detection results are naturally handled in our OCS scheme. Our framework is demonstrated to be very effective, improving top-1 accuracy to 89.3% (from 81.6%) on the large-scale fine-grained car classification dataset.

cs.CV↗

arXiv2014

A Revised Incremental Conductance MPPT Algorithm for Solar PV Generation Systems

A revised Incremental Conductance (IncCond) maximum power point tracking (MPPT) algorithm for PV generation systems is proposed in this paper. The commonly adopted traditional IncCond method uses a constant step size for voltage adjustment and is difficult to achieve both a good tracking performance and quick elimination of the oscillations, especially under the dramatic changes of the environment conditions. For the revised algorithm, the incremental voltage change step size is adaptively adjusted based on the slope of the power-voltage (P-V) curve. An accelerating factor and a decelerating factor are further applied to adjust the voltage step change considering whether the sign of the P-V curve slope remains the same or not in a subsequent tracking step. In addition, the upper bound of the maximum voltage step change is also updated considering the information of sign changes. The revised MPPT algorithm can quickly track the maximum power points (MPPs) and remove the oscillation of the actual operation points around the real MPPs. The effectiveness of the revised algorithm is demonstrated using a simulation.

cs.CE↗

arXiv2014

Generic Object Detection With Dense Neural Patterns and Regionlets

This paper addresses the challenge of establishing a bridge between deep convolutional neural networks and conventional object detection frameworks for accurate and efficient generic object detection. We introduce Dense Neural Patterns, short for DNPs, which are dense local features derived from discriminatively trained deep convolutional neural networks. DNPs can be easily plugged into conventional detection frameworks in the same way as other dense local features(like HOG or LBP). The effectiveness of the proposed approach is demonstrated with the Regionlets object detection framework. It achieved 46.1% mean average precision on the PASCAL VOC 2007 dataset, and 44.1% on the PASCAL VOC 2010 dataset, which dramatically improves the original Regionlets approach without DNPs.

cs.CV↗

arXiv2014

Impact of local-moment fluctuations on the magnetic degeneracy of iron arsenide superconductors

We investigate the fate of the orthorhombic stripe-type magnetic state (ordering vectors $\left(π,0\right)$/$\left(0,π\right)$), observed in most iron-pnictide superconductors, in the presence of localized magnetic moments that tend to form a Neel state (ordering vector $\left(π,π\right)$). We show that before long-range Neel order sets in, the coupling between the conduction electrons and the fluctuations of the local moments favors an unusual magnetic state consisting of a coherent superposition of the $\left(π,0\right)$ and $\left(0,π\right)$ orders that preserves tetragonal symmetry. The magnetization of this state is non-uniform and induces a simultaneous checkerboard charge order. We discuss signatures of this magnetic configuration on the electronic spectrum and its impact on the superconducting state, showing that its phase space for coexistence with the $s^{+-}$ state is smaller than the stripe-type state. Our results shed light on recent experimental observations on $\mathrm{Ba(Fe_{1-x}Mn_{x})_{2}As_{2}}$ compounds, where the Neel-type local Mn moments interact with the Fe conduction electrons.

cond-mat.str-el↗

arXiv2012

Extracting respiratory signals from thoracic cone beam CT projections

Patient respiratory signal associated with the cone beam CT (CBCT) projections is important for lung cancer radiotherapy. In contrast to monitoring an external surrogate of respiration, such signal can be extracted directly from the CBCT projections. In this paper, we propose a novel local principle component analysis (LPCA) method to extract the respiratory signal by distinguishing the respiration motion-induced content change from the gantry rotation-induced content change in the CBCT projections. The LPCA method is evaluated by comparing with three state-of-the-art projection-based methods, namely, the Amsterdam Shroud (AS) method, the intensity analysis (IA) method, and the Fourier-transform based phase analysis (FT-p) method. The clinical CBCT projection data of eight patients, acquired under various clinical scenarios, were used to investigate the performance of each method. We found that the proposed LPCA method has demonstrated the best overall performance for cases tested and thus is a promising technique for extracting respiratory signal. We also identified the applicability of each existing method.

physics.med-ph↗

arXiv2010

Constraints Imposed by Symmetry on Pairing Operators for the Pnictides

Considering model Hamiltonians that respect the symmetry properties of the pnictides, it is argued that pairing interactions that couple electrons at different orbitals with an orbital-dependent pairing strength inevitably lead to interband pairing matrix elements, at least in some regions of the Brillouin zone. Such interband pairing has not been considered of relevance in multiorbital systems in previous investigations. It is also observed that if, instead, a purely intraband pairing interaction is postulated, this requires that the pairing operator has the form $Δ^+(k)=f(k) \sum_α d^+_{k,α,\uparrow}d^+_{-k, α,\downarrow}$ where $α$ labels the orbitals considered in the model and f(k) arises from the spatial location of the coupled electrons or holes. This means that the gaps at two different Fermi surfaces involving momenta $k_F$ and $k'_F$ can only differ by the ratio $f(k_F)/ f(k'_F)$ and that electrons in different orbitals must be subject to the same pairing attraction, thus requiring fine tuning. These results suggest that previously neglected interband pairing tendencies could actually be of relevance in a microscopic description of the pairing mechanism in the pnictides.

cond-mat.supr-con↗