arXiv subjects

Guang Yang

Publications and source records attributed to Guang Yang.

At least 541 records · Page 30Linked to original sources

arXiv2017

X-ray spectral analyses of AGNs from the 7Ms Chandra Deep Field-South survey: the distribution, variability, and evolution of AGN's obscuration

We present a detailed spectral analysis of the brightest Active Galactic Nuclei (AGN) identified in the 7Ms Chandra Deep Field South (CDF-S) survey over a time span of 16 years. Using a model of an intrinsically absorbed power-law plus reflection, with possible soft excess and narrow Fe K$α$ line, we perform a systematic X-ray spectral analysis, both on the total 7Ms exposure and in four different periods with lengths of 2-21 months. With this approach, we not only present the power-law slopes, column densities $N_H$, observed fluxes, and absorption-corrected 2-10~keV luminosities $L_X$ for our sample of AGNs, but also identify significant spectral variabilities among them on time scales of years. We find that the $N_H$ variabilities can be ascribed to two different types of mechanisms, either flux-driven or flux-independent. We also find that the correlation between the narrow Fe line EW and $N_H$ can be well explained by the continuum suppression with increasing $N_H$. Accounting for the sample incompleteness and bias, we measure the intrinsic distribution of $N_H$ for the CDF-S AGN population and present re-selected subsamples which are complete with respect to $N_H$. The $N_H$-complete subsamples enable us to decouple the dependences of $N_H$ on $L_X$ and on redshift. Combining our data with that from C-COSMOS, we confirm the anti-correlation between the average $N_H$ and $L_X$ of AGN, and find a significant increase of the AGN obscured fraction with redshift at any luminosity. The obscured fraction can be described as $f_{obscured}\thickapprox 0.42\ (1+z)^{0.60}$.

astro-ph.GA↗

arXiv2017

Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks

A major challenge in brain tumor treatment planning and quantitative evaluation is determination of the tumor extent. The noninvasive magnetic resonance imaging (MRI) technique has emerged as a front-line diagnostic tool for brain tumors without ionizing radiation. Manual segmentation of brain tumor extent from 3D MRI volumes is a very time-consuming task and the performance is highly relied on operator's experience. In this context, a reliable fully automatic segmentation method for the brain tumor segmentation is necessary for an efficient measurement of the tumor extent. In this study, we propose a fully automatic method for brain tumor segmentation, which is developed using U-Net based deep convolutional networks. Our method was evaluated on Multimodal Brain Tumor Image Segmentation (BRATS 2015) datasets, which contain 220 high-grade brain tumor and 54 low-grade tumor cases. Cross-validation has shown that our method can obtain promising segmentation efficiently.

cs.CV↗

arXiv2017

Fully Automatic Segmentation and Objective Assessment of Atrial Scars for Longstanding Persistent Atrial Fibrillation Patients Using Late Gadolinium-Enhanced MRI

Purpose: Atrial fibrillation (AF) is the most common cardiac arrhythmia and is correlated with increased morbidity and mortality. It is associated with atrial fibrosis, which may be assessed non-invasively using late gadolinium-enhanced (LGE) magnetic resonance imaging (MRI) where scar tissue is visualised as a region of signal enhancement. In this study, we proposed a novel fully automatic pipeline to achieve an accurate and objective atrial scarring segmentation and assessment of LGE MRI scans for the AF patients. Methods: Our fully automatic pipeline uniquely combined: (1) a multi-atlas based whole heart segmentation (MA-WHS) to determine the cardiac anatomy from an MRI Roadmap acquisition which is then mapped to LGE MRI, and (2) a super-pixel and supervised learning based approach to delineate the distribution and extent of atrial scarring in LGE MRI. Results: Both our MA-WHS and atrial scarring segmentation showed accurate delineations of cardiac anatomy (mean Dice = 89%) and atrial scarring (mean Dice =79%) respectively compared to the established ground truth from manual segmentation. Compared with previously studied methods with manual interventions, our innovative pipeline demonstrated comparable results, but was computed fully automatically. Conclusion: The proposed segmentation methods allow LGE MRI to be used as an objective assessment tool for localisation, visualisation and quantification of atrial scarring.

cs.CV↗

arXiv2017

Deep De-Aliasing for Fast Compressive Sensing MRI

Fast Magnetic Resonance Imaging (MRI) is highly in demand for many clinical applications in order to reduce the scanning cost and improve the patient experience. This can also potentially increase the image quality by reducing the motion artefacts and contrast washout. However, once an image field of view and the desired resolution are chosen, the minimum scanning time is normally determined by the requirement of acquiring sufficient raw data to meet the Nyquist-Shannon sampling criteria. Compressive Sensing (CS) theory has been perfectly matched to the MRI scanning sequence design with much less required raw data for the image reconstruction. Inspired by recent advances in deep learning for solving various inverse problems, we propose a conditional Generative Adversarial Networks-based deep learning framework for de-aliasing and reconstructing MRI images from highly undersampled data with great promise to accelerate the data acquisition process. By coupling an innovative content loss with the adversarial loss our de-aliasing results are more realistic. Furthermore, we propose a refinement learning procedure for training the generator network, which can stabilise the training with fast convergence and less parameter tuning. We demonstrate that the proposed framework outperforms state-of-the-art CS-MRI methods, in terms of reconstruction error and perceptual image quality. In addition, our method can reconstruct each image in 0.22ms--0.37ms, which is promising for real-time applications.

cs.CV↗

arXiv2016

Analysis on 60 GHz Wireless Communications with Beamwidth-Dependent Misalignment

High speed wireless access on 60 GHz spectrum relies on high-gain directional antennas to overcome the severe signal attenuation. However, perfect alignment between transmitting and receiving antenna beams is rare in practice and overheard signals from concurrent transmissions may cause significant interference. In this paper we analyze the impact of antenna beam misalignment on the system performance of 60 GHz wireless access. We quantify the signal power loss caused by beam misalignment and the interference power accumulated from neighboring concurrent transmissions whose signals are leaked either via the main-beam pointing in the similar direction or via side-lobe emission, and derive the probability distribution of the signal to interference plus noise power ratio (SINR). For scenarios where interfering transmitters are distributed uniformly at random, we derive upper and lower bounds on the cumulative distribution function (abbreviated as CDF or c.d.f.) of SINR, which can be easily applied to evaluate system performance. We validate our analytical results by simulations where random nodes are uniformly distributed within a circular hall, and evaluate the sensitivity of average throughput and outage probability against two parameters: the half-power (3 dB) beamwidth to main-lobe beamwidth ratio and the beam misalignment deviation to main-lobe beamwidth ratio. Our results indicate that the derived lower bound performs well when the half-power beamwidth to main-lobe beamwidth ratio or the number of concurrent transmission links is small. When the number of active links is high, it is desirable in antenna design to balance the degradation caused by beam misalignment (wider beam is better) and the interference from concurrent transmission (narrower beam is better).

cs.IT↗

arXiv2016

Observation of Anomalous Magnetic Moments in Superconducting Bi/Ni Bilayer

There have been continuous efforts in searching for unconventional superconductivity over the past five decades. Compared to the well-established d-wave superconductivity in cuprates, the existence of superconductivity with other high-angular-momentum pairing symmetries is less conclusive. Bi/Ni epitaxial bilayer is a potential unconventional superconductor with broken time reversal symmetry (TRS), for that it demonstrates superconductivity and ferromagnetism simultaneously at low temperatures. We employ a specially designed superconducting quantum interference device (SQUID) to detect, on the Bi/Ni bilayer, the orbital magnetic moment which is expected if the TRS is broken. An anomalous hysteretic magnetic response has been observed in the superconducting state, providing the evidence for the existence of chiral superconducting domains in the material.

cond-mat.supr-con↗

arXiv2016

Neural Networks Designing Neural Networks: Multi-Objective Hyper-Parameter Optimization

Artificial neural networks have gone through a recent rise in popularity, achieving state-of-the-art results in various fields, including image classification, speech recognition, and automated control. Both the performance and computational complexity of such models are heavily dependant on the design of characteristic hyper-parameters (e.g., number of hidden layers, nodes per layer, or choice of activation functions), which have traditionally been optimized manually. With machine learning penetrating low-power mobile and embedded areas, the need to optimize not only for performance (accuracy), but also for implementation complexity, becomes paramount. In this work, we present a multi-objective design space exploration method that reduces the number of solution networks trained and evaluated through response surface modelling. Given spaces which can easily exceed 1020 solutions, manually designing a near-optimal architecture is unlikely as opportunities to reduce network complexity, while maintaining performance, may be overlooked. This problem is exacerbated by the fact that hyper-parameters which perform well on specific datasets may yield sub-par results on others, and must therefore be designed on a per-application basis. In our work, machine learning is leveraged by training an artificial neural network to predict the performance of future candidate networks. The method is evaluated on the MNIST and CIFAR-10 image datasets, optimizing for both recognition accuracy and computational complexity. Experimental results demonstrate that the proposed method can closely approximate the Pareto-optimal front, while only exploring a small fraction of the design space.

cs.NE↗

arXiv2016

Mechanisms governing phonon scattering by topological defects in graphene nanoribbons

Understanding phonon scattering by topological defects in graphene is of particular interest for thermal management in graphene-based devices. We present a study that quantifies the roles of the different mechanisms governing defect phonon scattering by comparing the effects of ten different defect structures using molecular dynamics. Our results show that phonon scattering is mainly influenced by mass density difference, with general trends governed by the defect formation energy and typical softening behaviors in the phonon density of state. The phonon scattering cross-section is found to be far larger than that geometrically occupied by the defects. We also show that the lattice thermal conductivity can be reduced by a factor of up to ~30 in the presence of the grain boundaries formed by these defects.

cond-mat.mtrl-sci↗

arXiv2016

Delay and Backlog Analysis for 60 GHz Wireless Networks

To meet the ever-increasing demands on higher throughput and better network delay performance, 60 GHZ networking is proposed as a promising solution for the next generation of wireless communications. To successfully deploy such networks, its important to understand their performance first. However, due to the unique fading characteristic of the 60 GHz channel, the characterization of the corresponding service process, offered by the channel, using the conventional methodologies may not be tractable. In this work, we provide an alternative approach to derive a closed-form expression that characterizes the cumulative service process of the 60 GHz channel in terms of the moment generating function (MGF) of its instantaneous channel capacity. We then use this expression to derive probabilistic upper bounds on the backlog and delay that are experienced by a flow traversing this network, using results from the MGF-based network calculus. The computed bounds are validated using simulation. We provide numerical results for different networking scenarios and for different traffic and channel parameters and we show that the 60 GHz wireless network is capable of satisfying stringent quality-of-Service (QoS) requirements, in terms of network delay and reliability. With this analysis approach at hand, a larger scale 60 GHz network design and optimization is possible.

cs.PF↗

arXiv2016

The deepest X-ray view of high-redshift galaxies: constraints on low-rate black-hole accretion

We exploit the 7 Ms \textit{Chandra} observations in the \chandra\,Deep Field-South (\mbox{CDF-S}), the deepest X-ray survey to date, coupled with CANDELS/GOODS-S data, to measure the total X-ray emission arising from 2076 galaxies at $3.5\leq z < 6.5$. This aim is achieved by stacking the \textit{Chandra} data at the positions of optically selected galaxies, reaching effective exposure times of $\geq10^9\mathrm{s}$. We detect significant ($>3.7σ$) X-ray emission from massive galaxies at $z\approx4$. We also report the detection of massive galaxies at $z\approx5$ at a $99.7\%$ confidence level ($2.7σ$), the highest significance ever obtained for X-ray emission from galaxies at such high redshifts. No significant signal is detected from galaxies at even higher redshifts. The stacking results place constraints on the BHAD associated with the known high-redshift galaxy samples, as well as on the SFRD at high redshift, assuming a range of prescriptions for X-ray emission due to X- ray binaries. We find that the X-ray emission from our sample is likely dominated by processes related to star formation. Our results show that low-rate mass accretion onto SMBHs in individually X-ray-undetected galaxies is negligible, compared with the BHAD measured for samples of X-ray detected AGN, for cosmic SMBH mass assembly at high redshift. We also place, for the first time, constraints on the faint-end of the AGN X-ray luminosity function ($\mathrm{logL_X\sim42}$) at $z>4$, with evidence for fairly flat slopes. The implications of all of these findings are discussed in the context of the evolution of the AGN population at high redshift.

astro-ph.GA↗

arXiv2016

Room temperature magnetism on the zigzag edges of phosphorene nanoribbons

Searching for room temperature ferromagnetic semiconductors has evolved into a broad field of material science and spintronics for decades, nevertheless, these novel states remain rare. Phosphorene, a monolayer black phosphorus with a puckered honeycomb lattice structure possessing a finite band gap and high carrier mobility, has been synthesized recently. Here we show, by means of two different large scale quantum Monte-Carlo methods, that relatively weak interactions can lead to remarkable edge magnetism in the phosphorene nanoribbons. The ground state constrained path quantum Monte-Carlo simulations reveal strong ferromagnetic correlations along the zigzag edges, and the finite temperature determinant quantum Monte-Carlo calculations show a high Curie temperature up to room temperature.

cond-mat.str-el↗

arXiv2016

Analysis of Multi-Hop Outdoor 60 GHz Wireless Networks with Full-Duplex Buffered Relays

The abundance of unlicensed spectrum in the 60 GHz band makes it an attractive alternative for future wireless communication systems. Such systems are expected to provide data transmission rates in the order of multi-gigabits per second in order to satisfy the ever-increasing demand for high rate data communication. Unfortunately, 60 GHz radio is subject to severe path loss which limits its usability for long-range outdoor communication. In this work, we propose a multi-hop 60 GHz wireless network for outdoor communication where multiple full-duplex buffered relays are used to extend the communication range while providing end-to-end performance guarantees to the traffic traversing the network. We provide a cumulative service process characterization for the 60 GHz outdoor propagation channel with self-interference in terms of the moment generating function (MGF) of its channel capacity. We then use this characterization to compute probabilistic upper bounds on the overall network performance, i.e., total backlog and end-to-end delay. Furthermore, we study the effect of self-interference on the network performance and propose an optimal power allocation scheme to mitigate its impact in order to enhance network performance. Finally, we investigate the relation between relay density and network performance under a total power budget constraint. We show that increasing relay density may have adverse effects on network performance unless self-interference can be kept sufficiently small.

cs.NI↗

arXiv2016

Determination of the hyperfine coupling constant of cesium 7S1/2 state

We report the hyperfine splitting (HFS) measurement of cesium (Cs) 7S1/2 state by optical-optical double-resonance spectroscopy in the 6S1/2-6P3/2-7S1/2 (852 nm + 1470 nm) ladder-type system. The HFS frequency calibration is performed by employing a phase-type waveguide electro-optic modulator together with a stable confocal Fabry-Perot cavity. From the measured HFS between F"= 3 and F"= 4 manifolds of Cs 7S1/2 state [HFS = 2183.273(37) MHz], we have determined the magnetic dipole hyperfine coupling constant [A = 545.818(09) MHz], which is in good agreement with the previous work but much more accurate.

physics.atom-ph↗

arXiv2016

Majorana bound states in magnetic skyrmions

Magnetic skyrmions are highly mobile nanoscale topological spin textures. We show, both analytically and numerically, that a magnetic skyrmion of an even azimuthal winding number placed in proximity to an s-wave superconductor hosts a zero-energy Majorana bound state in its core, when the exchange coupling between the itinerant electrons and the skyrmion is strong. This Majorana bound state is stabilized by the presence of a spin-orbit interaction. We propose the use of a superconducting tri-junction to realize non-Abelian statistics of such Majorana bound states.

cond-mat.supr-con↗

arXiv2016

Single top and Higgs associated production in the minimal $B-L$ model at the LHC

In this paper, we study the single top production in association with a Higgs boson in the $U(1)_{B-L}$ extension of the Standard Model at the LHC. We calculate the production cross sections of the processes $pp\rightarrow thX(h=H_{1},H_{2};X=j,b,W)$ in this model. Then we further study the observability of the process $pp\rightarrow tH_{2}j$ through $pp\rightarrow t(\rightarrow q\bar{q'} b)H_{2}(\rightarrow 4\ell)j$. We find that the systematic significance can be improved obviously, but it is still challenging for the 14 TeV LHC with high-luminosity to detect this signal.

hep-ph↗

arXiv2016

Neutrino mass hierarchy determination at reactor antineutrino experiments

After the neutrino mixing angle $θ_{13}$ has been precisely measured by the reactor antineutrino experiments, one of the most important open questions left in neutrino physics is the neutrino mass hierarchy. Jiangmen Underground Neutrino Observatory (JUNO) is designed to determine the neutrino mass hierarchy (MH) without exploring the matter effect. The JUNO site location is optimized to have the best sensitivity for the mass hierarchy determination. JUNO will employ a 20 kton liquid scintillator detector located in a laboratory 700 meters underground. The excellent energy resolution and PMT coverage will give us an unprecedented opportunity to reach a 3-4 $σ$ precision. In this paper, the JUNO detector design and simulation work will be presented. Also, RENO-50, another medium distance reactor antineutrino experiment, will do a similar measurement. With the efforts of these experiments, it is very likely that the neutrino mass hierarchy will be determined in the next 10 years.

physics.ins-det↗

arXiv2016

Fractional boundary charges in quantum dot arrays with density modulation

We show that fractional charges can be realized at the boundaries of a linear array of tunnel coupled quantum dots in the presence of a periodically modulated onsite potential. While the charge fractionalization mechanism is similar to the one in polyacetylene, here the values of fractional charges can be tuned to arbitrary values by varying the phase of the onsite potential or the total number of dots in the array. We also find that the fractional boundary charges, unlike the in-gap bound states, are stable against static random disorder. We discuss the minimum array size where fractional boundary charges can be observed.

cond-mat.mes-hall↗

arXiv2016

Diagnostics and future evolution analysis of the two parametric models

In this paper, we apply three diagnostics including $Om$, Statefinder hierarchy and the growth rate of perturbations into discriminating the two parametric models for the effective pressure with the $Λ$CDM model. By using the $Om$ diagnostic, we find that both the model 1 and the model 2 can be hardly distinguished from each other as well as the $Λ$CDM model in terms of 68\% confidence level. As a supplement, by using the Statefinder hierarchy diagnostics and the growth rate of perturbations, we discover that not only can our two parametric models be well distinguished from $Λ$CDM model, but also, by comparing with $Om$ diagnostic, the model 1 and the model 2 can be distinguished better from each other. In addition, we also explore the fate of universe evolution of our two models by means of the rip analysis.

gr-qc↗