arXiv subjects

Yang Li

Publications and source records attributed to Yang Li.

At least 1,531 records · Page 85Linked to original sources

arXiv2016

Coherent Product Superposition for Downlink Multiuser MIMO

In a two-user broadcast channel where one user has full CSIR and the other has none, a recent result showed that TDMA is strictly suboptimal and a product superposition requiring non-coherent signaling achieves DoF gains under many antenna configurations. This work introduces product superposition in the domain of coherent signaling with pilots, demonstrates the advantages of product superposition in low-SNR as well as high-SNR, and establishes DoF gains in a wider set of receiver antenna configurations. Two classes of decoders, with and without interference cancellation, are studied. Achievable rates are established by analysis and illustrated by simulations.

cs.IT↗

arXiv2016

Recurrent Regression for Face Recognition

To address the sequential changes of images including poses, in this paper we propose a recurrent regression neural network(RRNN) framework to unify two classic tasks of cross-pose face recognition on still images and video-based face recognition. To imitate the changes of images, we explicitly construct the potential dependencies of sequential images so as to regularize the final learning model. By performing progressive transforms for sequentially adjacent images, RRNN can adaptively memorize and forget the information that benefits for the final classification. For face recognition of still images, given any one image with any one pose, we recurrently predict the images with its sequential poses to expect to capture some useful information of others poses. For video-based face recognition, the recurrent regression takes one entire sequence rather than one image as its input. We verify RRNN in static face dataset MultiPIE and face video dataset YouTube Celebrities(YTC). The comprehensive experimental results demonstrate the effectiveness of the proposed RRNN method.

cs.CV↗

arXiv2016

Gland Instance Segmentation by Deep Multichannel Neural Networks

In this paper, we propose a new image instance segmentation method that segments individual glands (instances) in colon histology images. This is a task called instance segmentation that has recently become increasingly important. The problem is challenging since not only do the glands need to be segmented from the complex background, they are also required to be individually identified. Here we leverage the idea of image-to-image prediction in recent deep learning by building a framework that automatically exploits and fuses complex multichannel information, regional, location and boundary patterns in gland histology images. Our proposed system, deep multichannel framework, alleviates heavy feature design due to the use of convolutional neural networks and is able to meet multifarious requirement by altering channels. Compared to methods reported in the 2015 MICCAI Gland Segmentation Challenge and other currently prevalent methods of instance segmentation, we observe state-of-the-art results based on a number of evaluation metrics.

cs.CV↗

arXiv2016

Gland Instance Segmentation by Deep Multichannel Side Supervision

In this paper, we propose a new image instance segmentation method that segments individual glands (instances) in colon histology images. This is a task called instance segmentation that has recently become increasingly important. The problem is challenging since not only do the glands need to be segmented from the complex background, they are also required to be individually identified. Here we leverage the idea of image-to-image prediction in recent deep learning by building a framework that automatically exploits and fuses complex multichannel information, regional and boundary patterns, with side supervision (deep supervision on side responses) in gland histology images. Our proposed system, deep multichannel side supervision (DMCS), alleviates heavy feature design due to the use of convolutional neural networks guided by side supervision. Compared to methods reported in the 2015 MICCAI Gland Segmentation Challenge, we observe state-of-the-art results based on a number of evaluation metrics.

cs.CV↗

arXiv2016

Convergence Error Estimates of the Crank-Nicolson Scheme for Solving Decoupled FBSDEs

The Crank-Nicolson (short for C-N) scheme for solving {\it backward stochastic differential equation} (BSDE), driven by Brownian motions, was first developed by the authors W. Zhao, L. Chen and S. Peng [SIAM J. Sci. Comput., 28 (2006), 1563--1581], and numerical experiments showed that the accuracy of this C-N scheme was of second order for solving BSDE. This C-N scheme was extended to solve decoupled {\it forward-backward stochastic differential equations} (FBSDEs) by W. Zhao, Y. Li and Y. Fu [Sci. China. Math., 57 (2014), 665--686], and it was numerically shown that the accuracy of the extended C-N scheme was also of second order. To our best knowledge, among all one-step (two-time level) numerical schemes with second-order accuracy for solving BSDE or FBSDEs, such as the ones in the above two papers and the one developed by the authors D. Crisan and K. Manolarakis [Ann. Appl. Probab., 24, 2 (2014), 652--678], the C-N scheme is the simplest one in applications. The theoretical proofs of second-order error estimates reported in the literature for these schemes for solving decoupled FBSDEs did not include the C-N scheme. The purpose of this work is to theoretically analyze the error estimate of the C-N scheme for solving decoupled FBSDEs. Based on the Taylor and Itô-Taylor expansions, the Malliavin calculus theory (e.g., the multiple Malliavin integration-by-parts formula), and our new truncation error cancelation techniques, we rigorously prove that the strong convergence rate of the C-N scheme is of second order for solving decoupled FBSDEs, which fills the gap between the second-order numerical and theoretical analysis of the C-N scheme.

math.NA↗

arXiv2016

Heavy Quarkonium in a Holographic Basis

We study the heavy quarkonium within the basis light-front quantization approach. We implement the one-gluon exchange interaction and a confining potential inspired by light-front holography. We adopt the holographic light-front wavefunction (LFWF) as our basis function and solve the non-perturbative dynamics by diagonalizing the Hamiltonian matrix. We obtain the mass spectrum for charmonium and bottomonium. With the obtained LFWFs, we also compute the decay constants and the charge form factors for selected eigenstates. The results are compared with the experimental measurements and with other established methods.

hep-ph↗

arXiv2016

Morphological and Embedded Computation in a Self-contained Soft Robotic Hand

We present a self-contained, soft robotic hand composed of soft pneumatic actuator modules that are equipped with strain and pressure sensing. We show how this data can be used to discern whether a grasp was successful. Co-locating sensing and embedded computation with the actuators greatly simplifies control and system integration. Equipped with a small pump, the hand is self-contained and needs only power and data supplied by a single USB connection to a PC. We demonstrate its function by grasping a variety of objects ranging from very small to large and heavy objects weighing more than the hand itself. The presented system nicely illustrates the advantages of soft robotics: low cost, low weight, and intrinsic compliance. We exploit morphological computation to simplify control, which allows successful grasping via underactuation. Grasping indeed relies on morphological computation at multiple levels, ranging from the geometry of the actuator which determines the actuator's kinematics, embedded strain sensors to measure curvature, to maximizing contact area and applied force during grasping. Morphological computation reaches its limitations, however, when objects are too bulky to self-align with the gripper or when the state of grasping is of interest. We therefore argue that efficient and reliable grasping also requires not only intrinsic compliance, but also embedded sensing and computation. In particular, we show how embedded sensing can be used to detect successful grasps and vary the force exerted onto an object based on local feedback, which is not possible using morphological computation alone.

cs.RO↗

arXiv2016

Early Time Dynamics of Gluon Fields in High Energy Nuclear Collisions

Nuclei colliding at very high energy create a strong, quasi-classical gluon field during the initial phase of their interaction. We present an analytic calculation of the initial space-time evolution of this field in the limit of very high energies using a formal recursive solution of the Yang-Mills equations. We provide analytic expressions for the initial chromo-electric and chromo-magnetic fields and for their energy-momentum tensor. In particular, we discuss event-averaged results for energy density and energy flow as well as for longitudinal and transverse pressure of this system. Our results are generally applicable if $τ< 1/Q_s$. The transverse energy flow of the gluon field exhibits hydrodynamic-like contributions that follow transverse gradients of the energy density. In addition, a rapidity-odd energy flow also emerges from the non-abelian analog of Gauss' Law and generates non-vanishing angular momentum of the field. We will discuss the space-time picture that emerges from our analysis and its implications for observables in heavy ion collisions.

nucl-th↗

arXiv2016

Probing dark particles indirectly at the CEPC

When dark matter candidate and its parent particles are nearly degenerate, it would be difficult to probe them at the Large Hadron Collider directly. We propose to explore their quantum loop effects at the CEPC through the golden channel process $e^+e^-\to μ^+μ^-$. We use a renormalizable toy model consisting of a new scalar and a fermion to describe new physics beyond the Standard Model. The new scalar and fermion are general multiplets of the $SU(2)_L\times U(1)_Y$ symmetry, and couple to the muon lepton through Yukawa interaction. We calculate their loop contributions to anomalous $γμ^+μ^-$ and $Zμ^+μ^-$ couplings which can be applied to many new physics models. The prospects of their effects at the CEPC are also examined assuming a 0.002 accuracy in the cross section measurement.

hep-ph↗

arXiv2016

Ballistic Deposition of Nanoclusters

Nanoporous thin-films are an important class of materials, offering a way to observe fundamental surface and bulk processes with particles larger than individual atoms, but small enough to interact significantly with each other through mechanisms such as stress and surface mobility. In-Situ X-ray Reflectivity and Grazing Incidence Small Angle X-Ray Scattering (GISAXS) were used to monitor thin-films grown from Tungsten Disilicide (WSi$_2$) and Copper (Cu) nanoclusters. The nanoclusters ranged in size from 2 nm to 6 nm diameter and were made by high-pressure magnetron sputtering via plasma-gas condensation. X-Ray Reflectivity (XRR) measurements of the film at various stages of growth reveal that the resulting films exhibit very low density, approaching 15% of bulk density. This is consistent with a simple off-lattice ballistic deposition model where particles stick at the point of first contact without further restructuring. Furthermore, there is little merging or sintering of the clusters in these films.

cond-mat.mtrl-sci↗

arXiv2016

Tight Bounds for Single-Pass Streaming Complexity of the Set Cover Problem

We resolve the space complexity of single-pass streaming algorithms for approximating the classic set cover problem. For finding an $α$-approximate set cover (for any $α= o(\sqrt{n})$) using a single-pass streaming algorithm, we show that $Θ(mn/α)$ space is both sufficient and necessary (up to an $O(\log{n})$ factor); here $m$ denotes number of the sets and $n$ denotes size of the universe. This provides a strong negative answer to the open question posed by Indyk et al. (2015) regarding the possibility of having a single-pass algorithm with a small approximation factor that uses sub-linear space. We further study the problem of estimating the size of a minimum set cover (as opposed to finding the actual sets), and establish that an additional factor of $α$ saving in the space is achievable in this case and that this is the best possible. In other words, we show that $Θ(mn/α^2)$ space is both sufficient and necessary (up to logarithmic factors) for estimating the size of a minimum set cover to within a factor of $α$. Our algorithm in fact works for the more general problem of estimating the optimal value of a covering integer program. On the other hand, our lower bound holds even for set cover instances where the sets are presented in a random order.

cs.DS↗

arXiv2016

Topological end states in two-orbital double-exchange model for colossal magnetoresistive manganites

Manganites are famous mostly for the colossal magnetoresistive effect, which involves the phase separation between ferromagnetic phase and charge-ordered CE-type antiferromagnetic phases. Furthermore, manganites contain some typical magnetic ferroelectrics, e.g. E-type antiferromagnetic $o$-HoMnO$_3$. Here we re-examined these zigzag-winding antiferromagnetic phases (CE-type and E-type antiferromagnets) from the topological perspective. Our theoretical analysis proved that the E-type phase is a weak topological insulator belonging to the $\mathbb{Z}$ class. In momentum space, we classify the symmetries of this phase, and find the three symmetry operators for the chiral, particle-hole, and time-reversal symmetry. The CE-type phase can be described by the Duffin-Kemmer-Petiau algebra, implying that it is a new class of topological insulator and hence extends the existing classification. The corresponding topological end states are demonstrated via numerical calculations, which may implicate the experimental observed ferromagnetic edge states in manganite strips (Nat. Commun. 6, 6179 (2015)) and may play a crucial role in the colossal magnetoresistive effect.

cond-mat.mtrl-sci↗

arXiv2016

Form Factors and Generalized Parton Distributions in Basis Light-Front Quantization

We calculate the elastic form factors and the Generalized Parton Distributions (GPDs) for four low-lying bound states of a demonstration fermion-antifermion system, strong coupling positronium ($e \bar{e}$), using Basis Light-Front Quantization (BLFQ). Using this approach, we also calculate the impact-parameter dependent GPDs $q(x, {\vec b_\perp})$ to visualize the fermion density in the transverse plane (${\vec b_\perp}$). We compare selected results with corresponding quantities in the non-relativistic limit to reveal relativistic effects. Our results establish the foundation within BLFQ for investigating the form factors and the GPDs for hadronic systems.

nucl-th↗

arXiv2016

NMR experiments and electronic structure calculations in type-I BaAlGe clathrates

We describe 27Al NMR experiments on Ba8AlxGe46-x type-I clathrates coupled with ab initio computational studies. For x=16, calculated spectra determined by the ab initio results gave good agreement with the measurements, with best-fitting configurations also corresponding to the computed lowest-energy atomic arrangements. Analysis of the NMR results showed that a distribution of Knight shifts dominates the central portion of the line. Computational results demonstrate that this stems from the large variation of carrier density on different sites. Al-deficient samples with x=12 and 13 exhibited a split central NMR peak, signaling two main local environments for Al ions, which we connected to the presence of vacancies. Modeling of the wide-line spectrum for x=12 indicates a configuration with more Al on the 24k site than for x=16. The results indicate the importance of nonbonding hybrids adjacent to the vacancies in the electronic structure near EF. We also address the static distortions from Pm-3n symmetry in these structures.

cond-mat.mtrl-sci↗

arXiv2016

Dilute magnetism and vibrational entropy in Fe2Al5

Fe2Al5 contains a Fe-Al matrix through which are threaded disordered one-dimensional chains of overlapping Al sites. We report magnetic, nuclear-magnetic-resonance (NMR), and specific-heat measurements addressing its magnetic and vibrational properties. The Curie-type susceptibility is found to be due to dilute moments, likely due to wrong-site Fe atoms. 27Al NMR shift and spin-lattice relaxation measurements confirm these to be indirectly coupled through a Ruderman-Kittel-Kasuya-Yoshida-type interaction. Specific-heat results indicate a large density of low-energy vibrational modes. These excitations generate a linear-T contribution to the specific heat, which however freezes out below about 10 K. These results are attributed to the presence of anharmonic vibrational modes associated with the disordered structural chains.

cond-mat.mtrl-sci↗

arXiv2016

A model for 3:2 HFQPO pairs in black hole binaries based on cosmic battery

A model for 3:2 high-frequency quasi-periodic oscillations (HFQPOs) with 3:2 pairs observed in four black hole X-ray binaries (BHXBs) is proposed by invoking the epicyclic resonances with the magnetic connection (MC) between a spinning black hole (BH) with a relativistic accretion disc. It turns out that the MC can be worked out due to Poynting-Robertson cosmic battery (PRCB), and the 3:2 HFQPO pairs associated with the steep power-law states can be fitted in this model. Furthermore, the severe damping problem in the epicyclic resonance model can be overcome by transferring energy from the BH to the inner disc via the MC process for emitting X-rays with sufficient amplitude and coherence to produce the HFQPOs. In addition, we discuss the important role of the magnetic field in state transition of BHXBs.

astro-ph.HE↗

arXiv2015

Algorithms for Provisioning Queries and Analytics

Provisioning is a technique for avoiding repeated expensive computations in what-if analysis. Given a query, an analyst formulates $k$ hypotheticals, each retaining some of the tuples of a database instance, possibly overlapping, and she wishes to answer the query under scenarios, where a scenario is defined by a subset of the hypotheticals that are "turned on". We say that a query admits compact provisioning if given any database instance and any $k$ hypotheticals, one can create a poly-size (in $k$) sketch that can then be used to answer the query under any of the $2^{k}$ possible scenarios without accessing the original instance. In this paper, we focus on provisioning complex queries that combine relational algebra (the logical component), grouping, and statistics/analytics (the numerical component). We first show that queries that compute quantiles or linear regression (as well as simpler queries that compute count and sum/average of positive values) can be compactly provisioned to provide (multiplicative) approximate answers to an arbitrary precision. In contrast, exact provisioning for each of these statistics requires the sketch size to be exponential in $k$. We then establish that for any complex query whose logical component is a positive relational algebra query, as long as the numerical component can be compactly provisioned, the complex query itself can be compactly provisioned. On the other hand, introducing negation or recursion in the logical component again requires the sketch size to be exponential in $k$. While our positive results use algorithms that do not access the original instance after a scenario is known, we prove our lower bounds even for the case when, knowing the scenario, limited access to the instance is allowed.

cs.DB↗

arXiv2015

On the Scale free laws of Urban Facilities

We implement a double stochastic process as the mathematical model for the spatial point patterns of urban facilities. We find that the model with power covariance function can produce the best fit not only to $K$ function (whose derivative gives the radial distribution $ρ(t) = K'(t)/2πt$) but also to additional facts of spatial point patterns. These facts include the mean-variance relationship of number of events in a series of expanding bins, and other statistics beyond the first two orders, such as inter-event distribution function $H(t)$ and nearest neighbor distribution functions $G(t)$ and $F(t)$.

physics.soc-ph↗