arXiv subjects

Peng Wang

Publications and source records attributed to Peng Wang.

At least 1,027 records · Page 57Linked to original sources

arXiv2015

Magnetoelectricity coupled exchange bias in BaMnF$_4$

Multiferroic BaMnF$_4$ powder were prepared by hydrothermal method. Hysteretic field dependent magnetization curve at 5 K confirms the weak ferromagnetism aroused from the canted antiferromagnetic spins by magnetoelectric coupling. The blocking temperature of 65 K for exchange bias coincides well with the peak at 65 K in the zero-field cooled temperature-dependent magnetization curve, which has been assigned to the onset temperature of two-dimensional antiferromagnetism. An upturn kink of exchange field and coercivity with decreasing temperature was observed from 40 K to 20 K, which is consistent with the two-dimensional to three-dimensional antiferromagnetic transition at Néel temperature (~26 K). In contrast to the conventional mechanism of magnetization pinned by interfacial exchange coupling in multiphases, the exchange bias in BaMnF$_4$ is argued to be a bulk effect in single phase, due to the magnetization pinned by the polarization through magnetoelectric coupling.

cond-mat.mtrl-sci↗

arXiv2015

Entropic Effects of Thermal Rippling on van der Waals Interactions between Monolayer Graphene and a Rigid Substrate

Graphene monolayer, with extremely low flexural stiffness, displays spontaneous rippling due to thermal fluctuations at a finite temperature. When a graphene membrane is placed on a solid substrate, the adhesive interactions between graphene and the substrate could considerably suppress thermal rippling. On the other hand, the statistical nature of thermal rippling adds an entropic contribution to the graphene-substrate interactions. In this paper we present a statistical mechanics analysis on thermal rippling of monolayer graphene supported on a rigid substrate, assuming a generic form of van der Waals interactions between graphene and substrate at T = 0 K. The rippling amplitude, the equilibrium average separation, and the average interaction energy are predicted simultaneously and compared with molecular dynamics (MD) simulations. While the amplitude of thermal rippling is reduced by adhesive interactions, the entropic contribution leads to an effective repulsion. As a result, the equilibrium average separation increases and the effective adhesion energy decreases with increasing temperature. Moreover, the effect of a biaxial pre-strain in graphene is considered, and a buckling instability is predicted at a critical compressive strain that depends on both the temperature and the adhesive interactions. Limited by the harmonic approximations, the theoretical predictions agree with MD simulations only for relatively small rippling amplitudes but can be extended to account for the anharmonic effects.

cond-mat.mes-hall↗

arXiv2015

Performance evaluation of the general characteristics based off-lattice Boltzmann and DUGKS methods for low speed continuum flows: A comparative study

The general characteristics based off-lattice Boltzmann scheme (BKG) proposed by Bardow et~al.(2006), and the discrete unified gas kinetic scheme (DUGKS) are two methods that successfully overcome the time step restriction by the collision time, which is commonly seen in many other kinetic schemes. Basically, the BKG scheme is a time splitting scheme, while the DUGKS is an un-split finite volume scheme. In this work, we first perform a theoretical analysis of the two schemes in the finite volume framework by comparing their numerical flux evaluations. It is found that the effects of collision term are considered in the reconstructions of the cell-interface distribution function in both schemes, which explains why they can overcome the time step restriction and can give accurate results even as the time step is much larger than the collision time. The difference between the two schemes lies in the treatment of the integral of the collision term, in which the Bardow's scheme uses the rectangular rule while the DUGKS uses the trapezoidal rule. The performance of the two schemes, i.e., accuracy, stability, and efficiency are then compared by simulating several two dimensional flows, including the unsteady Taylor-Green vortex flow, the steady lid-driven cavity flow, and the laminar boundary layer problem. It is observed that, the DUGKS can give more accurate results than the BKG scheme. Furthermore, the numerical stability of the BKG scheme decreases as the Courant-Friedrichs-Lewy (CFL) number approaches to 1, while the stability of DUGKS is not affected by the CFL number apparently as long as CFL<1. It is also observed that the BKG scheme is about one time faster than the DUGKS scheme with the same computational mesh and time step.

physics.flu-dyn↗

arXiv2015

The accretion of dark matter subhaloes within the cosmic web: primordial anisotropic distribution and its universality

The distribution of galaxies displays anisotropy on different scales and it is often referred as galaxy alignment. To understand the origin of galaxy alignments on small scales, one must investigate how galaxies were accreted in the early universe and quantify their primordial anisotropic at the time of accretion. In this paper we use N-body simulations to investigate the accretion of dark matter subhaloes, focusing on their alignment with the host halo shape and the orientation of mass distribution on large scale, defined using the hessian matrix of the density field. The large/small (e1/e3) eigenvalues of the hessian matrix define the fast/slow collapse direction of dark matter on large scale. We find that: 1) the halo major axis is well aligned with the e3 (slow collapse) direction, and it is stronger for massive haloes; 2) subhaloes are predominately accreted along the major axis of the host halo, and the alignment increases with the host halo mass. Most importantly, this alignment is universal; 3) accretion of subhaloes with respect to the e3 direction is not universal. In massive haloes, subhaloes are accreted along the e3 (even stronger than the alignment with the halo major axis), but in low-mass haloes subhaloes are accreted perpendicular to the e3. The transit mass is lower at high redshift. The last result well explains the puzzled correlation (both in recent observations and simulations) that massive galaxies/haloes have their spin perpendicular to the filament, and the spin of low-mass galaxies/haloes is slightly aligned with the filament, under the assumption that the orbital angular momentum of subhaloes is converted to halo spin.

astro-ph.CO↗

arXiv2015

Efficient Semidefinite Branch-and-Cut for MAP-MRF Inference

We propose a Branch-and-Cut (B&C) method for solving general MAP-MRF inference problems. The core of our method is a very efficient bounding procedure, which combines scalable semidefinite programming (SDP) and a cutting-plane method for seeking violated constraints. In order to further speed up the computation, several strategies have been exploited, including model reduction, warm start and removal of inactive constraints. We analyze the performance of the proposed method under different settings, and demonstrate that our method either outperforms or performs on par with state-of-the-art approaches. Especially when the connectivities are dense or when the relative magnitudes of the unary costs are low, we achieve the best reported results. Experiments show that the proposed algorithm achieves better approximation than the state-of-the-art methods within a variety of time budgets on challenging non-submodular MAP-MRF inference problems.

cs.CV↗

arXiv2015

Willmore surfaces in spheres via loop groups III: on minimal surfaces in space forms

The family of Willmore immersions from a Riemann surface into $S^{n+2}$ can be divided naturally into the subfamily of Willmore surfaces conformally equivalent to a minimal surface in $\R^{n+2}$ and those which are not conformally equivalent to a minimal surface in $\R^{n+2}$. On the level of their conformal Gauss maps into $Gr_{1,3}(\R^{1,n+3})=SO^+(1,n+3)/SO^+(1,3)\times SO(n)$ these two classes of Willmore immersions into $S^{n+2}$ correspond to conformally harmonic maps for which every image point, considered as a 4-dimensional Lorentzian subspace of $\R^{1,n+3}$, contains a fixed lightlike vector or where it does not contain such a "constant lightlike vector". Using the loop group formalism for the construction of Willmore immersions we characterize in this paper precisely those normalized potentials which correspond to conformally harmonic maps containing a lightlike vector. Since the special form of these potentials can easily be avoided, we also precisely characterize those potentials which produce Willmore immersions into $ S^{n+2}$ which are not conformal to a minimal surface in $\R^{n+2}$. It turns out that our proof also works analogously for minimal immersions into the other space forms.

math.DG↗

arXiv2015

Semiconductor quantum dots enhanced graphene/CdTe heterostructure solar cells by photo-induced doping

We report a type of solar cells based on graphene/CdTe Schottky heterostructure, which can be improved by surface engineering as graphene is one-atomic thin. By coating a layer of ultrathin CdSe quantum dots onto graphene/CdTe heterostructure, the power conversion efficiency is increased from 2.08% to 3.1%. Photo-induced doping is mainly accounted for this enhancement, as evidenced by transport, photoluminescence and quantum efficiency measurements. This work demonstrates a feasible way of designing solar cells with incorporating one dimensional and two dimensional materials.

physics.optics↗

arXiv2015

Ultrasensitive and broadband MoS2 photodetector driven by ferroelectrics

Photodetectors based on two dimensional materials have attracted growing interest. However, the sensitivity is still unsatisfactory even under high gate voltage. Here we demonstrate a MoS2 photodetector with a poly(vinylidene fluoride-trifluoroethylene) ferroelectric layer in place of the oxide layer in a traditional field effect transistor. The dark current of the photodetector is strongly suppressed by ferroelectric polarization. A high detectivity 2.21012 Jones) and photoresponsitivity (2570 A W) detector has been achieved under ZERO gate bias at a wavelength of 635 nm. Most strikingly, the band gap of few-layer MoS2 can be tuned by the ultra-high electrostatic field from the ferroelectric polarization. With this characteristic, photoresponse wavelengths of the photodetector are extended into the near infrared (0.85-1.55m). A ferroelectrics optoelectronics hybrid structure is an effective way to achieve high performance 2D electronic optoelectronic devices.

cond-mat.mes-hall↗

arXiv2015

Thermodynamics and Luminosities of Rainbow Black Holes

Doubly special relativity (DSR) is an effective model for encoding quantum gravity in flat spacetime. As a result of the nonlinearity of the Lorentz transformation, the energy-momentum dispersion relation is modified. One simple way to import DSR to curved spacetime is \textquotedblleft Gravity's rainbow", where the spacetime background felt by a test particle would depend on its energy. Focusing on the \textquotedblleft Amelino-Camelia dispersion relation" which is $E^{2}=m^{2}+p^{2}\left[ 1-η\left( E/m_{p}\right) ^{n}\right] $ with $n>0$, we investigate the thermodynamical properties of a Schwarzschild black hole and a static uncharged black string for all possible values of $η$ and $n$ in the framework of rainbow gravity. It shows that there are non-vanishing minimum masses for these two black holes in the cases with $η<0$ and $n\geq2$. Considering effects of rainbow gravity on both the Hawking temperature and radius of the event horizon, we use the geometric optics approximation to compute luminosities of a 2D black hole, a Schwarzschild one and a static uncharged black string. It is found that the luminosities can be significantly suppressed or boosted depending on the values of $η$ and $n$.

gr-qc↗

arXiv2015

Opening the band gap of graphene through silicon doping for improved performance of graphene/GaAs heterojunction solar cells

Graphene has attracted increasing interests due to its remarkable properties, however, the zero band gap of monolayer graphene might limit its further electronic and optoelectronic applications. Herein, we have successfully synthesized monolayer silicon-doped graphene (SiG) in large area by chemical vapor deposition method. Raman spectroscopy and X-ray photoelectron spectroscopy measurements evidence silicon atoms are doped into graphene lattice with the doping level of 3.4 at%. The electrical measurement based on field effect transistor indicates that the band gap of graphene has been opened by silicon doping, which is around 0. 28 eV supported by the first-principle calculations, and the ultraviolet photoelectron spectroscopy demonstrates the work function of SiG is 0.13 eV larger than that of graphene. Moreover, the SiG/GaAs heterostructure solar cells show an improved power conversion efficiency of 33.7% in average than that of graphene/GaAs solar cells, which are attributed to the increased barrier height and improved interface quality. Our results suggest silicon doping can effectively engineer the band gap of monolayer graphene and SiG has great potential in optoelectronic device applications.

cond-mat.mtrl-sci↗

arXiv2015

Electrocatalytic Hydrogen Evolution Reaction on Edges of a Few Layer Molybdenum Disulfide Nanodots

The design and development of inexpensive highly efficient electrocatalysts for hydrogen production, underpins several emerging clean-energy technologies. In this work, for the first time, molybdenum disulfide (MoS2) nanodots have been synthesized by ionic liquid assisted grinding exfoliation of bulk platelets and isolated by sequential centrifugation. The nanodots have a thickness of up to 7 layers (4 nm) and an average lateral size smaller than 20 nm. Detailed structural characterization established that the nanodots retained the crystalline quality and low oxidation states of the bulk material. The small lateral size and reduced number of layers provided these nanodots with an easier path for the electron transport and plentiful active sites for the catalysis of hydrogen evolution reaction (HER) in acidic electrolyte. The MoS2 nanodots exhibited good durability and a Tafel slope of 61 mVdec-1 with an estimated onset potential of -0.09 V vs RHE, which are considered among the best values achieved for 2H phase. It is envisaged that this work may provide a simplistic route to synthesize a wide range of 2D layered nanodots that have applications in water splitting and other energy related technologies. KEYWORDS: MoS2 nanosheets, hydrogen evolution reaction, electrocatalysis, edges, nanodots, ionic liquid exfoliation, water splitting

cond-mat.mtrl-sci↗

arXiv2015

Equivalence of open/closed strings

In this paper, we prove that the open and closed strings are $O(D,D)$ equivalent. The equivalence requires an AdS geometry near the boundaries. The $O(D,D)$ invariance is introduced into the Polyakov action by the Tseytlin's action. Traditionally, there exist disconnected open-open or closed-closed configurations in the solution space of the Tseytlin's action. The open-closed configuration is ruled out by the mixed terms of the dual fields. We show that, under some very general guidances, the dual fields are consistently decoupled if and only if the near horizon geometry is $AdS_5$. We then have open-closed and closed-open configurations in different limits of the distances of the $D3$-brane pairs. Inherited from the definition of the theory, these four configurations are of course related to each other by $O(D,D)$ transformations. We therefore conclude that both the open/closed relation and open/closed duality can be derived from $O(D,D)$ symmetries. We then demonstrate the open/closed relation does connect commutative open and closed strings. By analyzing the couplings of the configurations, the low energy effective limits of our results consequently predicts the AdS/CFT correspondence, Higher spin theory, weak gauge/weak gravity duality and a yet to be proposed strong gauge/strong gravity duality. Furthermore, we also have the Seiberg duality and a weak/strong gravitation duality as consequences of $O(D,D)$ symmetries.

hep-th↗

arXiv2015

Implementation of Training Convolutional Neural Networks

Deep learning refers to the shining branch of machine learning that is based on learning levels of representations. Convolutional Neural Networks (CNN) is one kind of deep neural network. It can study concurrently. In this article, we gave a detailed analysis of the process of CNN algorithm both the forward process and back propagation. Then we applied the particular convolutional neural network to implement the typical face recognition problem by java. Then, a parallel strategy was proposed in section4. In addition, by measuring the actual time of forward and backward computing, we analysed the maximal speed up and parallel efficiency theoretically.

cs.CV↗

arXiv2015

High performance solar cells based on graphene-GaAs heterostructures

The honeycomb connection of carbon atoms by covalent bonds in a macroscopic two-dimensional scale leads to fascinating graphene and solar cell based on graphene/silicon Schottky diode has been widely studied. For solar cell applications, GaAs is superior to silicon as it has a direct band gap of 1.42 eV and its electron mobility is six times of that of silicon. However, graphene/GaAs solar cell has been rarely explored. Herein, we report graphene/GaAs solar cells with conversion efficiency (Eta) of 10.4% and 15.5% without and with anti-reflection layer on graphene, respectively. The Eta of 15.5% is higher than the state of art efficiency for graphene/Si system (14.5%). Furthermore, our calculation points out Eta of 25.8% can be reached by reasonably optimizing the open circuit voltage, junction ideality factor, resistance of graphene and metal/graphene contact. This research strongly support graphene/GaAs hetero-structure solar cell have great potential for practical applications.

cond-mat.mes-hall↗

arXiv2015

Black Hole Radiation with Modified Dispersion Relation in Tunneling Paradigm: Free-fall Frame

Due to the exponential high gravitational red shift near the event horizon of a black hole, it might appear that the Hawking radiation would be highly sensitive to some unknown high energy physics. To study effects of any unknown physics at the Planck scale on the Hawking radiation, the dispersive field theory models have been proposed, which are variations of Unruh's sonic black hole analogy. In this paper, we use the Hamilton-Jacobi method to investigate the dispersive field theory models. The preferred frame is the free-fall frame of the black hole. The dispersion relation adopted agrees with the relativistic one at low energy but is modified near the Planck mass $m_{p}$. The corrections to the Hawking temperature are calculated for massive and charged particles to $\mathcal{O}\left( m_{p}^{-2}\right) $ and neutral and massless particles with $λ=0$ to all orders. The Hawking temperature of radiation agrees with the standard one at the leading order. After the spectrum of radiation near the horizon is obtained, we use the brick wall model to compute the thermal entropy of a massless scalar field near the horizon of a 4D spherically symmetric black hole and a 2D one. Finally, the luminosity of a Schwarzschild black hole is calculated by using the geometric optics approximation.

gr-qc↗

arXiv2015

Joint Object and Part Segmentation using Deep Learned Potentials

Segmenting semantic objects from images and parsing them into their respective semantic parts are fundamental steps towards detailed object understanding in computer vision. In this paper, we propose a joint solution that tackles semantic object and part segmentation simultaneously, in which higher object-level context is provided to guide part segmentation, and more detailed part-level localization is utilized to refine object segmentation. Specifically, we first introduce the concept of semantic compositional parts (SCP) in which similar semantic parts are grouped and shared among different objects. A two-channel fully convolutional network (FCN) is then trained to provide the SCP and object potentials at each pixel. At the same time, a compact set of segments can also be obtained from the SCP predictions of the network. Given the potentials and the generated segments, in order to explore long-range context, we finally construct an efficient fully connected conditional random field (FCRF) to jointly predict the final object and part labels. Extensive evaluation on three different datasets shows that our approach can mutually enhance the performance of object and part segmentation, and outperforms the current state-of-the-art on both tasks.

cs.CV↗

arXiv2015

Temporal Pyramid Pooling Based Convolutional Neural Networks for Action Recognition

Encouraged by the success of Convolutional Neural Networks (CNNs) in image classification, recently much effort is spent on applying CNNs to video based action recognition problems. One challenge is that video contains a varying number of frames which is incompatible to the standard input format of CNNs. Existing methods handle this issue either by directly sampling a fixed number of frames or bypassing this issue by introducing a 3D convolutional layer which conducts convolution in spatial-temporal domain. To solve this issue, here we propose a novel network structure which allows an arbitrary number of frames as the network input. The key of our solution is to introduce a module consisting of an encoding layer and a temporal pyramid pooling layer. The encoding layer maps the activation from previous layers to a feature vector suitable for pooling while the temporal pyramid pooling layer converts multiple frame-level activations into a fixed-length video-level representation. In addition, we adopt a feature concatenation layer which combines appearance information and motion information. Compared with the frame sampling strategy, our method avoids the risk of missing any important frames. Compared with the 3D convolutional method which requires a huge video dataset for network training, our model can be learned on a small target dataset because we can leverage the off-the-shelf image-level CNN for model parameter initialization. Experiments on two challenging datasets, Hollywood2 and HMDB51, demonstrate that our method achieves superior performance over state-of-the-art methods while requiring much fewer training data.

cs.CV↗

arXiv2015

Willmore surfaces in spheres via loop groups IV: on totally isotropic Willmore two-spheres in $S^6$

Totally isotropic surfaces in $S^6$ are not necessarily Willmore surfaces. Therefore it is the first goal of this paper to derive a geometric characterization of totally isotropic Willmore two-spheres in $S^6$. This will naturally yield to a description of such surfaces in terms of the loop group language. Moreover, applying the loop group method, we also obtain an algorithm to construct totally isotropic Willmore two-spheres in $S^6$. As an application, a new, totally isotropic Willmore two-sphere which is not S-Willmore (i.e., has no dual surface) in $S^6$ is constructed, illustrating the theory of this paper.

math.DG↗