arXiv subjects

Guang Yang

Publications and source records attributed to Guang Yang.

At least 487 records · Page 27Linked to original sources

arXiv2019

Auxetic tetrahex-carbon with ultrahigh strength and direct band gap

Tetrahex-carbon is a recently predicted two dimensional (2D) carbon allotrope which is composed of tetragonal and hexagonal rings. Unlike flat graphene, this new 2D carbon structure is buckled, possesses a direct band gap ~ 2.6 eV and high carrier mobility with anisotropic feature. In this work, we employ first-principles density-functional theory calculations to explore mechanical properties of tetrahex-C under uniaxial tensile strain. We find that tetrahex-C demonstrates ultrahigh ideal strength, outperforming both graphene and penta-graphene. It shows superior ductility and sustains uniaxial tensile strain up to 20% (16%) till phonon instability occurs, and the corresponding maximal strength is 38.3 N/m (37.8 N/m) in the zigzag (armchair) direction. It shows intrinsic negative Poisson's ratio. This exotic in-plane Poisson's ratio takes place when axial strain reaches a threshold value of 7% (5%) in the zigzag (armchair) direction. We also find that tetrahex-C holds a direct band gap of 2.64 eV at the center of Brillouin zone. This direct-band-gap feature maintains intact upon strain application with no direction-indirect gap transition. The ultrahigh ideal strength, negative Poisson's ratio and integrity of direct-gap under strain in tetrahex-C suggest it may have potential applications in nanomechanics and nanoelectronics.

cond-mat.mtrl-sci↗

arXiv2019

Gate-tunable h/e-period magnetoresistance oscillations in Bi2O2Se nanowires

We report on the successful synthesis and low-temperature electron transport investigations of a new form of material - Bi2O2Se semiconducting nanowires. Gate-tunable 0- and $π$-h/e (h is the Planck constant and e the elementary charge) periodic resistance oscillations in longitudinal magnetic field were observed unexpectedly, demonstrating novel quasi-ballistic, phase-coherent surface states in Bi2O2Se nanowires. By reaching a very good agreement between the calculated density of states and the experimental data, we clarified the mechanism to be the one dimensional subbands formed along the circumference of the nanowire rather than the usually considered Aharonov-Bohm interference. A qualitative physical picture based on downward band bending associated with the complex band structure is proposed to describe the formation of the surface states.

cond-mat.mes-hall↗

arXiv2019

Probing black hole accretion tracks, scaling relations and radiative efficiencies from stacked X-ray active galactic nuclei

The masses of supermassive black holes at the centres of local galaxies appear to be tightly correlated with the mass and velocity dispersions of their galactic hosts. However, the local Mbh-Mstar relation inferred from dynamically measured inactive black holes is up to an order-of-magnitude higher than some estimates from active black holes, and recent work suggests that this discrepancy arises from selection bias on the sample of dynamical black hole mass measurements. In this work we combine X-ray measurements of the mean black hole accretion luminosity as a function of stellar mass and redshift with empirical models of galaxy stellar mass growth, integrating over time to predict the evolving Mbh-Mstar relation. The implied relation is nearly independent of redshift, indicating that stellar and black hole masses grow, on average, at similar rates. Matching the de-biased local Mbh-Mstar relation requires a mean radiative efficiency ~0.15, in line with theoretical expectations for accretion onto spinning black holes. However, matching the "raw" observed relation for inactive black holes requires a mean radiative efficiency around 0.02, far below theoretical expectations. This result provides independent evidence for selection bias in dynamically estimated black hole masses, a conclusion that is robust to uncertainties in bolometric corrections, obscured active black hole fractions, and kinetic accretion efficiency. For our fiducial assumptions, they favour moderate-to-rapid spins of typical supermassive black holes, to achieve a mean radiative efficiency ~0.12-0.20. Our approach has similarities to the classic Soltan analysis, but by using galaxy-based data instead of integrated quantities we are able to focus on regimes where observational uncertainties are minimized.

astro-ph.GA↗

arXiv2019

Haptic Teleoperation of UAVs through Control Barrier Functions

This paper presents a novel approach to haptic teleoperation. Specifically, we use control barrier functions (CBFs) to generate force feedback to help human operators safely fly quadrotor UAVs. CBFs take a control signal as input and output a control signal that is as close as possible to the initial control signal, while also meeting specified safety constraints. In the proposed method, we generate haptic force feedback based on the difference between a command issued by the human operator and the safe command returned by a CBF. In this way, if the user issues an unsafe control command, the haptic feedback will help guide the user towards the safe input command that is closest to their current command. We conducted a within-subject user study, in which 12 participants flew a simulated UAV in a virtual hallway environment. Participants completed the task with our proposed CBF-based haptic feedback, no haptic feedback, and haptic feedback generated via parametric risk fields, which is a state-of-the-art method described in the literature. The results of this study show that CBF-based haptic feedback can improve a human operator's ability to safely fly a UAV and reduce the operator's perceived workload, without sacrificing task efficiency.

cs.RO↗

arXiv2019

Querying a Matrix through Matrix-Vector Products

We consider algorithms with access to an unknown matrix $M\in\mathbb{F}^{n \times d}$ via matrix-vector products, namely, the algorithm chooses vectors $\mathbf{v}^1, \ldots, \mathbf{v}^q$, and observes $M\mathbf{v}^1,\ldots, M\mathbf{v}^q$. Here the $\mathbf{v}^i$ can be randomized as well as chosen adaptively as a function of $ M\mathbf{v}^1,\ldots,M\mathbf{v}^{i-1}$. Motivated by applications of sketching in distributed computation, linear algebra, and streaming models, as well as connections to areas such as communication complexity and property testing, we initiate the study of the number $q$ of queries needed to solve various fundamental problems. We study problems in three broad categories, including linear algebra, statistics problems, and graph problems. For example, we consider the number of queries required to approximate the rank, trace, maximum eigenvalue, and norms of a matrix $M$; to compute the AND/OR/Parity of each column or row of $M$, to decide whether there are identical columns or rows in $M$ or whether $M$ is symmetric, diagonal, or unitary; or to compute whether a graph defined by $M$ is connected or triangle-free. We also show separations for algorithms that are allowed to obtain matrix-vector products only by querying vectors on the right, versus algorithms that can query vectors on both the left and the right. We also show separations depending on the underlying field the matrix-vector product occurs in. For graph problems, we show separations depending on the form of the matrix (bipartite adjacency versus signed edge-vertex incidence matrix) to represent the graph. Surprisingly, this fundamental model does not appear to have been studied on its own, and we believe a thorough investigation of problems in this model would be beneficial to a number of different application areas.

cs.CC↗

arXiv2019

Automatic Prostate Zonal Segmentation Using Fully Convolutional Network with Feature Pyramid Attention

Our main objective is to develop a novel deep learning-based algorithm for automatic segmentation of prostate zone and to evaluate the proposed algorithm on an additional independent testing data in comparison with inter-reader consistency between two experts. With IRB approval and HIPAA compliance, we designed a novel convolutional neural network (CNN) for automatic segmentation of the prostatic transition zone (TZ) and peripheral zone (PZ) on T2-weighted (T2w) MRI. The total study cohort included 359 patients from two sources; 313 from a deidentified publicly available dataset (SPIE-AAPM-NCI PROSTATEX challenge) and 46 from a large U.S. tertiary referral center with 3T MRI (external testing dataset (ETD)). The TZ and PZ contours were manually annotated by research fellows, supervised by genitourinary (GU) radiologists. The model was developed using 250 patients and tested internally using the remaining 63 patients from the PROSTATEX (internal testing dataset (ITD)) and tested again (n=46) externally using the ETD. The Dice Similarity Coefficient (DSC) was used to evaluate the segmentation performance. DSCs for PZ and TZ were 0.74 and 0.86 in the ITD respectively. In the ETD, DSCs for PZ and TZ were 0.74 and 0.792, respectively. The inter-reader consistency (Expert 2 vs. Expert 1) were 0.71 (PZ) and 0.75 (TZ). This novel DL algorithm enabled automatic segmentation of PZ and TZ with high accuracy on both ITD and ETD without a performance difference for PZ and less than 10% TZ difference. In the ETD, the proposed method can be comparable to experts in the segmentation of prostate zones.

eess.IV↗

arXiv2019

Distributed and Consistent Multi-Image Feature Matching via QuickMatch

In this work we consider the multi-image object matching problem, extend a centralized solution of the problem to a distributed solution, and present an experimental application of the centralized solution. Multi-image feature matching is a keystone of many applications, including simultaneous localization and mapping, homography, object detection, and structure from motion. We first review the QuickMatch algorithm for multi-image feature matching. We then present a scheme for distributing sets of features across computational units (agents) that largely preserves feature match quality and minimizes communication between agents (avoiding, in particular, the need of flooding all data to all agents). Finally, we show how QuickMatch performs on an object matching test with low quality images. The centralized QuickMatch algorithm is compared to other standard matching algorithms, while the Distributed QuickMatch algorithm is compared to the centralized algorithm in terms of preservation of match consistency. The presented experiment shows that QuickMatch matches features across a large number of images and features in larger numbers and more accurately than standard techniques.

cs.CV↗

arXiv2019

MRI Brain Tumor Segmentation using Random Forests and Fully Convolutional Networks

In this paper, we propose a novel learning based method for automated segmentation of brain tumor in multimodal MRI images, which incorporates two sets of machine -learned and hand crafted features. Fully convolutional networks (FCN) forms the machine learned features and texton based features are considered as hand-crafted features. Random forest (RF) is used to classify the MRI image voxels into normal brain tissues and different parts of tumors, i.e. edema, necrosis and enhancing tumor. The method was evaluated on BRATS 2017 challenge dataset. The results show that the proposed method provides promising segmentations. The mean Dice overlap measure for automatic brain tumor segmentation against ground truth is 0.86, 0.78 and 0.66 for whole tumor, core and enhancing tumor, respectively.

cs.CV↗

arXiv2019

Probing the minigap in topological insulator-based Josephson junctions under radio frequency irradiation

Recently, a contact-resistance-measurement method was developed to detect the minigap, hence the Andreev bound states (ABSs), in Josephson junctions constructed on the surface of three-dimensional topological insulators (3D TIs). In this work, we further generalize that method to the circumstance with radio frequency (rf) irradiation. We find that with the increase of rf power, the measured minigap becomes broadened and extends to higher energies, in a way similar to the rf power dependence of the outer border of the Shapiro step region. We show that the corresponding data of contact resistance under rf irradiation can be well interpreted by using the resistively shunted Josephson junction model (RSJ model) and the Blonder-Tinkham-Klapwijk (BTK) theory. Our findings could be useful when using the contact-resistance-measurement method to study the Majorana-related physics in topological insulator-based Josephson junctions under rf irradiation.

cond-mat.mes-hall↗

arXiv2019

Model reduction for coupled free flow over porous media: a hybrid dimensional pore network model approach

Modeling coupled systems of free flow adjacent to a porous medium by means of fully resolved Navier-Stokes equations is limited by the immense computational cost and is thus only feasible for relatively small domains. Model reduction allows to decrease a model's complexity while maintaining an acceptable degree of accuracy. Starting from a fully resolved three-dimensional numerical model, which is compared to high-resolution micro-PIV experimental data obtained from a previous study (Terzis et al.,2019), we perform a two-fold model reduction: first, a quasi-3D model incorporating a wall friction term is successfully compared to the fully resolved model. Second, we employ a pore-network model to account for the porous part of the domain and couple it to the quasi-3D model which still resolves the free-flow part of the domain (Weishaupt et al., 2019). We have extended this coupling approach here to include slip velocities at the pore throats intersecting with the free-flow domain. The proposed method is simple, accurate and comes at no additional run-time penalty. The coupled model deviates by less than 10 % from the other two model concepts. Several hours of run-time was required for the three-dimensional model compared to eleven and five minutes necessary for the quasi-3D and coupled model which highlights the benefits of model reduction.

physics.comp-ph↗

arXiv2019

Fast and Exact Nearest Neighbor Search in Hamming Space on Full-Text Search Engines

A growing interest has been witnessed recently from both academia and industry in building nearest neighbor search (NNS) solutions on top of full-text search engines. Compared with other NNS systems, such solutions are capable of effectively reducing main memory consumption, coherently supporting multi-model search and being immediately ready for production deployment. In this paper, we continue the journey to explore specifically how to empower full-text search engines with fast and exact NNS in Hamming space (i.e., the set of binary codes). By revisiting three techniques (bit operation, subs-code filtering and data preprocessing with permutation) in information retrieval literature, we develop a novel engineering solution for full-text search engines to efficiently accomplish this special but important NNS task. In the experiment, we show that our proposed approach enables full-text search engines to achieve significant speed-ups over its state-of-the-art term match approach for NNS within binary codes.

cs.IR↗

arXiv2019

Discriminative Consistent Domain Generation for Semi-supervised Learning

Deep learning based task systems normally rely on a large amount of manually labeled training data, which is expensive to obtain and subject to operator variations. Moreover, it does not always hold that the manually labeled data and the unlabeled data are sitting in the same distribution. In this paper, we alleviate these problems by proposing a discriminative consistent domain generation (DCDG) approach to achieve a semi-supervised learning. The discriminative consistent domain is achieved by a double-sided domain adaptation. The double-sided domain adaptation aims to make a fusion of the feature spaces of labeled data and unlabeled data. In this way, we can fit the differences of various distributions between labeled data and unlabeled data. In order to keep the discriminativeness of generated consistent domain for the task learning, we apply an indirect learning for the double-sided domain adaptation. Based on the generated discriminative consistent domain, we can use the unlabeled data to learn the task model along with the labeled data via a consistent image generation. We demonstrate the performance of our proposed DCDG on the late gadolinium enhancement cardiac MRI (LGE-CMRI) images acquired from patients with atrial fibrillation in two clinical centers for the segmentation of the left atrium anatomy (LA) and proximal pulmonary veins (PVs). The experiments show that our semi-supervised approach achieves compelling segmentation results, which can prove the robustness of DCDG for the semi-supervised learning using the unlabeled data along with labeled data acquired from a single center or multicenter studies.

cs.LG↗

arXiv2019

Recurrent Aggregation Learning for Multi-View Echocardiographic Sequences Segmentation

Multi-view echocardiographic sequences segmentation is crucial for clinical diagnosis. However, this task is challenging due to limited labeled data, huge noise, and large gaps across views. Here we propose a recurrent aggregation learning method to tackle this challenging task. By pyramid ConvBlocks, multi-level and multi-scale features are extracted efficiently. Hierarchical ConvLSTMs next fuse these features and capture spatial-temporal information in multi-level and multi-scale space. We further introduce a double-branch aggregation mechanism for segmentation and classification which are mutually promoted by deep aggregation of multi-level and multi-scale features. The segmentation branch provides information to guide the classification while the classification branch affords multi-view regularization to refine segmentations and further lessen gaps across views. Our method is built as an end-to-end framework for segmentation and classification. Adequate experiments on our multi-view dataset (9000 labeled images) and the CAMUS dataset (1800 labeled images) corroborate that our method achieves not only superior segmentation and classification accuracy but also prominent temporal stability.

eess.IV↗

arXiv2019

Sampling-based Motion Planning via Control Barrier Functions

Robot motion planning is central to real-world autonomous applications, such as self-driving cars, persistence surveillance, and robotic arm manipulation. One challenge in motion planning is generating control signals for nonlinear systems that result in obstacle free paths through dynamic environments. In this paper, we propose Control Barrier Function guided Rapidly-exploring Random Trees (CBF-RRT), a sampling-based motion planning algorithm for continuous-time nonlinear systems in dynamic environments. The algorithm focuses on two objectives: efficiently generating feasible controls that steer the system toward a goal region, and handling environments with dynamical obstacles in continuous time. We formulate the control synthesis problem as a Quadratic Program (QP) that enforces Control Barrier Function (CBF) constraints to achieve obstacle avoidance. Additionally, CBF-RRT does not require nearest neighbor or collision checks when sampling, which greatly reduce the run-time overhead when compared to standard RRT variants.

cs.RO↗

arXiv2019

Searching for fast extragalactic X-ray transients in Chandra surveys

Recent works have discovered two fast ($\approx 10$ ks) extragalactic X-ray transients in the Chandra Deep Field-South (CDF-S XT1 and XT2). These findings suggest that a large population of similar extragalactic transients might exist in archival X-ray observations. We develop a method that can effectively detect such transients in a single Chandra exposure, and systematically apply it to Chandra surveys of CDF-S, CDF-N, DEEP2, UDS, COSMOS, and E-CDF-S, totaling 19~Ms of exposure. We find 13 transient candidates, including CDF-S XT1 and XT2. With the aid of available excellent multiwavelength observations, we identify the physical nature of all these candidates. Aside from CDF-S XT1 and XT2, the other 11 sources are all stellar objects, and all of them have $z$-band magnitudes brighter than 20. We estimate an event rate of $59^{+77}_{-38}\ \rm{evt\ yr^{-1} deg^{-2}}$ for CDF-S XT-like transients with 0.5-7 keV peak fluxes $\log F_{\rm peak} \gtrsim -12.6$ (erg cm$^{-2}$ s$^{-1}$). This event rate translates to $\approx 15^{+20}_{-10}$ transients existing among Chandra archival observations at Galactic latitudes $|b|>20^{\circ}$, which can be probed in future work. Future missions such as Athena and the Einstein Probe with large grasps (effective area $\times$ field of view) are needed to discover a large sample ($\sim$ thousands) of fast extragalactic X-ray transients.

astro-ph.HE↗

arXiv2019

Anisotropy engineering edge magnetism in zigzag honeycomb nanoribbons

It have been demonstrated that the zigzag honeycomb nanoribbons exhibit an intriguing edge magnetism. Here the effect of the anisotropy on the edge magnetism in zigzag honeycomb nanoribbons is investigated by using two kinds of large-scale quantum Monte Carlo simulations. The anisotropy in zigzag honeycomb nanoribbons is characterized by the ratios of nearest-neighboring hopping integrals $t_{1}$ in one direction and $t_{2}$ in another direction. Considering the electron-electron correlation, it is shown that the edge ferromagnetism could be enhanced greatly as $t_{2}/|t_{1}|$ increase from $1$ to $3$, which not only presenting the avenue for the control of this magnetism, but also being useful for exploring further novel magnetism in new nano-scale materials.

cond-mat.str-el↗

arXiv2019

The Host-Galaxy Properties of Type 1 Versus Type 2 Active Galactic Nuclei

The unified model of active galactic nuclei (AGNs) proposes that different AGN optical spectral types are caused by different viewing angles with respect to an obscuring 'torus'. Therefore, this model predicts that type 1 and type 2 AGNs should have similar host-galaxy properties. We investigate this prediction with 2463 X-ray selected AGNs in the COSMOS field. We divide our sample into type 1 and type 2 AGNs based on their spectra, morphologies, and variability. We derive their host-galaxy stellar masses ($M_\star$) through SED fitting, and find that the host $M_\star$ of type 1 AGNs tend to be slightly smaller than those of type 2 AGNs by $Δ\overline{\mathrm{log}M_\star}\approx0.2~\mathrm{dex}$ ($\approx 4σ$ significance). Besides deriving star-formation rates (SFRs) from SED fitting, we also utilize far-infrared (FIR) photometry and a stacking method to obtain FIR-based SFRs. We find that the SFRs of type 1 and type 2 sources are similar once their redshifts and X-ray luminosities are controlled. We also investigate cosmic environment, and find that the surface number densities (sub-Mpc) and cosmic-web environments ($\approx 1\text{--}10$~Mpc) are similar for both populations. In summary, our analyses show that the host galaxies of type 1 and type 2 AGNs have similar SFR and cosmic environment in general, but the former tend to have lower $M_\star$ than the latter. The difference in $M_\star$ indicates that the AGN unification model is not strictly correct and both host galaxy and torus may contribute to the optical obscuration of AGNs.

astro-ph.GA↗

arXiv2019

Revealing the Origin of Luminescence Center in 0D Cs4PbBr6 Perovskite

Zero dimensional perovskite Cs4PbBr6 has attracted considerable attention recently not only because of its highly efficient green photoluminescence (PL), but also its two highly debated opposing mechanisms of the luminescence: embedded CsPbBr3 nanocrystals versus intrinsic Br vacancy states. After a brief discussion on the root cause of the controversy, we provide sensitive but non-invasive methods that can not only directly correlate luminescence with the underlying structure, but also distinguish point defects from embedded nanostructures. We first synthesized both emissive and non-emissive Cs4PbBr6 crystals, obtained the complete Raman spectrum of Cs4PbBr6 and assigned all Raman bands based on density functional theory simulations. We then used correlated Raman-PL as a passive structure-property method to identify the difference between emissive and non-emissive Cs4PbBr6 crystals and revealed the existence of CsPbBr3 nanocrystals in emissive Cs4PbBr6. We finally employed a diamond anvil cell to probe the response of luminescence centers to hydrostatic pressure. The observations of fast red-shifting, diminishing and eventual disappearance of both green emission and Raman below Cs4PbBr6 phase transition pressure of ~3 GPa is compatible with CsPbBr3 nanocrystal inclusions as green PL emitters and cannot be explained by Br vacancies. The resolution of this long-lasting controversy paves the way for further device applications of low dimensional perovskites, and our comprehensive optical technique integrating structure-property with dynamic pressure response is generic and can be applied to other emerging optical materials to understand the nature of their luminescent centers.

cond-mat.mtrl-sci↗