arXiv subjects

Peng Zhou

Publications and source records attributed to Peng Zhou.

At least 181 records · Page 10Linked to original sources

arXiv2018

Full-Field Interferometric Imaging of Propagating Action Potentials

Currently, cellular action potentials are detected using either electrical recordings or exogenous fluorescent probes sensing calcium concentration or transmembrane voltage. Ca imaging has low temporal resolution, while voltage indicators are vulnerable to phototoxicity, photobleaching and heating. Here we report full-field interferometric imaging of individual action potentials by detecting the movement across the entire cell membrane. Using spike-triggered averaging of the movies synchronized to electrical recording, we demonstrate deformations of up to 3 nm (0.9 mrad) during the action potential in spiking HEK-293 cells, with a rise time of 4 ms. The time course of the optically-recorded spikes matches electrical waveforms. Since the shot noise limit of the camera (~2 mrad/pix) precludes detection of the action potential in a single frame, for all-optical spike detection, images are acquired at 50 kHz, and 50 frames are binned into 1 ms steps to achieve a sensitivity of 0.3 mrad in a single pixel. Using self-reinforcing sensitivity enhancement algorithm based on iteratively expanding the region of interest for spatial averaging, individual spikes can be detected by matching the previously extracted template of the action potential with the optical recording. This allows all-optical full-field imaging of the propagating action potentials without exogeneous labels or electrodes.

physics.bio-ph↗

arXiv2018

Pointwise Weyl laws for Partial Bergman kernels

This is a partly expository article for the volume "Algebraic and Analytic Microlocal Analysis" on pointwise Weyl laws for spectral projections kernels in the Kaehler setting. We prove a 2-term pointwise Weyl law for projections onto sums of eigenspaces of spectral width $\hbar=k^{-1}$ of Toeplitz quantizations $\hat{H}_k$ of Hamiltonians on a Kaehler manifold. The first result is a complete asymptotic expansion for smoothed spectral projections in terms of periodic orbit data. When the orbit is `strongly hyperbolic' the leading coefficient defines a uniformly continuous measure on $\R$ and a semi-classical Tauberian theorem implies the 2-term expansion. As in previous works in the series, we use scaling asymptotics of the Boutet-de-Monvel-Sjostrand parametrix and Taylor expansions to reduce the proof to the Bargmann-Fock case.

math.CV↗

arXiv2018

Learning Rich Features for Image Manipulation Detection

Image manipulation detection is different from traditional semantic object detection because it pays more attention to tampering artifacts than to image content, which suggests that richer features need to be learned. We propose a two-stream Faster R-CNN network and train it endto- end to detect the tampered regions given a manipulated image. One of the two streams is an RGB stream whose purpose is to extract features from the RGB image input to find tampering artifacts like strong contrast difference, unnatural tampered boundaries, and so on. The other is a noise stream that leverages the noise features extracted from a steganalysis rich model filter layer to discover the noise inconsistency between authentic and tampered regions. We then fuse features from the two streams through a bilinear pooling layer to further incorporate spatial co-occurrence of these two modalities. Experiments on four standard image manipulation datasets demonstrate that our two-stream framework outperforms each individual stream, and also achieves state-of-the-art performance compared to alternative methods with robustness to resizing and compression.

cs.CV↗

arXiv2018

Interface asymptotics of Partial Bergman kernels around a critical level

In a recent series of articles (arXiv:1604.06655, arXiv:1708.09267), the authors have studied the transition behavior of partial Bergman kernels $Π_{k, [E_1, E_2]}(z,w)$ and the associated DOS (density of states) $Π_{k, [E_1, E_2]}(z)$ across the interface $\ccal$ between the allowed and forbidden regions. Partial Bergman kernels are Toeplitz Hamiltonians quantizing Morse functions $H: M \to \R$ on a \kahler manifold. The allowed region is $H^{-1}([E_1, E_2])$ and the interface $\ccal$ is its boundary. In prior articles it was assumed that the endpoints $E_j$ were regular values of $H$. This article completes the series by giving parallel results when an endpoint is a critical value of $H$. In place of the Erf scaling asymptotics in a $k^{-\half} $ tube around $\ccal$ for regular interfaces, one obtains $δ$-asymptotics in $k^{-\frac{1}{4}}$-tubes around singular points of a critical interface. In $k^{-\half}$ tubes, the transition law is given by the osculating metaplectic propagator.

math.CV↗

arXiv2018

Two-Stream Neural Networks for Tampered Face Detection

We propose a two-stream network for face tampering detection. We train GoogLeNet to detect tampering artifacts in a face classification stream, and train a patch based triplet network to leverage features capturing local noise residuals and camera characteristics as a second stream. In addition, we use two different online face swapping applications to create a new dataset that consists of 2010 tampered images, each of which contains a tampered face. We evaluate the proposed two-stream network on our newly collected dataset. Experimental results demonstrate the effectiveness of our method.

cs.CV↗

arXiv2018

Central Limit theorem for toric \kahler manifolds

Associated to the Bergman kernels of a polarized toric \kahler manifold $(M, ω, L, h)$ are sequences of measures $\{μ_k^z\}_{k=1}^{\infty}$ parametrized by the points $z \in M$. For each $z$ in the open orbit, we prove a central limit theorem for $μ_k^z$. The center of mass of $μ_k^z$ is the image of $z$ under the moment map; after re-centering at $0$ and dilating by $\sqrt{k}$, the re-normalized measure tends to a centered Gaussian whose variance is the Hessian of the \kahler potential at $z$. We further give a remainder estimate of Berry-Esseen type. The sequence $\{μ_k^z\}$ is generally not a sequence of convolution powers and the proofs only involve \kahler analysis.

math.PR↗

arXiv2017

Central Limit theorem for spectral Partial Bergman kernels

Partial Bergman kernels $Π_{k, E}$ are kernels of orthogonal projections onto subspaces $\mathcal{k} \subset H^0(M, L^k)$ of holomorphic sections of the $k$th power of an ample line bundle over a Kahler manifold $(M, ω)$. The subspaces of this article are spectral subspaces $\{\hat{H}_k \leq E\}$ of the Toeplitz quantization $\hat{H}_k$ of a smooth Hamiltonian $H: M \to \mathbb{R}$. It is shown that the relative partial density of states $\frac{Π_{k, E}(z)}{Π_k(z)} \to {1}_{\mathcal{A}}$ where $\mathcal{A} = \{H < E\}$. Moreover it is shown that this partial density of states exhibits `Erf'-asymptotics along the interface $\partial \mathcal{A}$, that is, the density profile asymptotically has a Gaussian error function shape interpolating between the values $1,0$ of ${1}_{\mathcal{A}}$. Such `erf'-asymptotics are a universal edge effect. The different types of scaling asymptotics are reminiscent of the law of large numbers and central limit theorem

math.CV↗

arXiv2017

Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme

Joint extraction of entities and relations is an important task in information extraction. To tackle this problem, we firstly propose a novel tagging scheme that can convert the joint extraction task to a tagging problem. Then, based on our tagging scheme, we study different end-to-end models to extract entities and their relations directly, without identifying entities and relations separately. We conduct experiments on a public dataset produced by distant supervision method and the experimental results show that the tagging based methods are better than most of the existing pipelined and joint learning methods. What's more, the end-to-end model proposed in this paper, achieves the best results on the public dataset.

cs.CL↗

arXiv2017

Interface asymptotics of partial Bergman kernels on $S^1$-symmetric Kaehler manifolds

This article is concerned with asymptotics of equivariant Bergman kernels and partial Bergman kernels for polarized projective Kahler manifolds invariant under a Hamiltonian holomorphic $S^1$ action. Asymptotics of partial Bergman kernel are obtained in the allowed region $\mathcal{A}$ resp. forbidden region $\mathcal{F}$, generalizing results of Shiffman-Zelditch, Shiffman-Tate-Zelditch and Pokorny-Singer for toric Kahler manifolds. The main result gives scaling asymptotics of equivariant Bergman kernels and partial Bergman kernels in the transition region around the interface $\partial \mathcal{A}$, generalizing recent work of Ross-Singer on partial Bergman kernels, and refining the Ross-Singer transition asymptotics to apply to equivariant Bergman kernels.

math.CV↗

arXiv2017

Twisted Polytope Sheaves and Coherent-Constructible Correspondence for Toric Varieties

Given a smooth projective toric variety $X_Σ$ of complex dimension $n$, Fang-Liu-Treumann-Zaslow \cite{FLTZ} showed that there is a quasi-embedding of the differential graded (dg) derived category of coherent sheaves $Coh(X_Σ)$ into the dg derived category of constructible sheaves on a torus $Sh(T^n, Λ_Σ)$. Recently, Kuwagaki \cite{Ku2} proved that the quasi-embedding is a quasi-equivalence, and generalized the result to toric stacks. Here we give a different proof in the smooth projective case, using non-characteristic deformation of sheaves to find twisted polytope sheaves that co-represent the stalk functors.

math.AG↗

arXiv2016

Text Classification Improved by Integrating Bidirectional LSTM with Two-dimensional Max Pooling

Recurrent Neural Network (RNN) is one of the most popular architectures used in Natural Language Processsing (NLP) tasks because its recurrent structure is very suitable to process variable-length text. RNN can utilize distributed representations of words by first converting the tokens comprising each text into vectors, which form a matrix. And this matrix includes two dimensions: the time-step dimension and the feature vector dimension. Then most existing models usually utilize one-dimensional (1D) max pooling operation or attention-based operation only on the time-step dimension to obtain a fixed-length vector. However, the features on the feature vector dimension are not mutually independent, and simply applying 1D pooling operation over the time-step dimension independently may destroy the structure of the feature representation. On the other hand, applying two-dimensional (2D) pooling operation over the two dimensions may sample more meaningful features for sequence modeling tasks. To integrate the features on both dimensions of the matrix, this paper explores applying 2D max pooling operation to obtain a fixed-length representation of the text. This paper also utilizes 2D convolution to sample more meaningful information of the matrix. Experiments are conducted on six text classification tasks, including sentiment analysis, question classification, subjectivity classification and newsgroup classification. Compared with the state-of-the-art models, the proposed models achieve excellent performance on 4 out of 6 tasks. Specifically, one of the proposed models achieves highest accuracy on Stanford Sentiment Treebank binary classification and fine-grained classification tasks.

cs.CL↗

arXiv2016

Scaling of Harmonic Oscillator Eigenfunctions and Their Nodal Sets Around the Caustic

We study the scaling asymptotics of the eigenspace projection kernels $Π_{\hbar, E}(x,y)$ of the isotropic Harmonic Oscillator $- \hbar ^2 Δ+ |x|^2$ of eigenvalue $E = \hbar(N + \frac{d}{2})$ in the semi-classical limit $\hbar \to 0$. The principal result is an explicit formula for the scaling asymptotics of $Π_{\hbar, E}(x,y)$ for $x,y$ in a $\hbar^{2/3}$ neighborhood of the caustic $\mathcal C_E$ as $\hbar \to 0.$ The scaling asymptotics are applied to the distribution of nodal sets of Gaussian random eigenfunctions around the caustic as $\hbar \to 0$. In previous work we proved that the density of zeros of Gaussian random eigenfunctions of $\hat{H}_{\hbar}$ have different orders in the Planck constant $\hbar$ in the allowed and forbidden regions: In the allowed region the density is of order $\hbar^{-1}$ while it is $\hbar^{-1/2}$ in the forbidden region. Our main result on nodal sets is that the density of zeros is of order $\hbar^{-\frac{2}{3}}$ in an $\hbar^{\frac{2}{3}}$-tube around the caustic. This tube radius is the `critical radius'. For annuli of larger inner and outer radii $\hbar^α$ with $0< α< \frac{2}{3}$ we obtain density results which interpolate between this critical radius result and our prior ones in the allowed and forbidden region. We also show that the Hausdorff $(d-2)$-dimensional measure of the intersection of the nodal set with the caustic is of order $\hbar^{- \frac{2}{3}}$.

math-ph↗

arXiv2016

Wafer-scale arrayed p-n junctions based on few-layer epitaxial GaTe

Two-dimensional (2D) materials have attracted substantial attention in electronic and optoelectronic applications with superior advantages of being flexible, transparent and highly tunable. Gapless graphene exhibits ultra-broadband and fast photoresponse while the 2D semiconducting MoS2 and GaTe unveil high sensitivity and tunable responsivity to visible light. However, the device yield and the repeatability call for a further improvement of the 2D materials to render large-scale uniformity. Here we report a layer-by-layer growth of wafer-scale GaTe with a hole mobility of 28.4 cm2/Vs by molecular beam epitaxy. The arrayed p-n junctions were developed by growing few-layer GaTe directly on three-inch Si wafers. The resultant diodes reveal good rectifying characteristics, photoresponse with a maximum photoresponsivity of 2.74 A/W and a high photovoltaic external quantum efficiency up to 62%. The photocurrent reaches saturation fast enough to capture a time constant of 22 μs and shows no sign of device degradation after 1.37 million cycles of operation. Most strikingly, such high performance has been achieved across the entire wafer, making the volume production of devices accessible. Finally, several photo-images were acquired by the GaTe/Si photodiodes with a reasonable contrast and spatial resolution, demonstrating for the first time the potential of integrating the 2D materials with the silicon technology for novel optoelectronic devices.

cond-mat.mtrl-sci↗

arXiv2016

Arrayed van der Waals Vertical Heterostructures based on 2D GaSe Grown by Molecular Beam Epitaxy

Vertically stacking two dimensional (2D) materials can enable the design of novel electronic and optoelectronic devices and realize complex functionality. However, the fabrication of such artificial heterostructures in wafer scale with an atomically-sharp interface poses an unprecedented challenge. Here, we demonstrate a convenient and controllable approach for the production of wafer-scale 2D GaSe thin films by molecular beam epitaxy. In-situ reflection high-energy electron diffraction oscillations and Raman spectroscopy reveal a layer-by-layer van der Waals epitaxial growth mode. Highly-efficient photodetector arrays were fabricated based on few-layer GaSe on Si. These photodiodes show steady rectifying characteristics and a relatively high external quantum efficiency of 23.6%. The resultant photoresponse is super-fast and robust with a response time of 60 us. Importantly, the device shows no sign of degradation after 1 million cycles of operation. Our study establishes a new approach to produce controllable, robust and large-area 2D heterostructures and presents a crucial step for further practical applications.

cond-mat.mes-hall↗

arXiv2016

Direct observation of Landau level resonance and mass generation in Dirac semimetal Cd3As2 thin films

Three-dimensional topological Dirac semimetals have hitherto stimulated unprecedented research interests as a new class of quantum materials. Breaking certain types of symmetries has been proposed to enable the manipulation of Dirac fermions; and that was soon realized by external modulations such as magnetic fields. However, an intrinsic manipulation of Dirac states, which is more efficient and desirable, remains a significant challenge. Here, we report a systematic study of quasi-particle dynamics and band evolution in Cd3As2 thin films with controlled Chromium (Cr) doping by both magneto-infrared spectroscopy and electrical transport. For the first time, we observe square-root-B relation of inter-Landau-level resonance in undoped Cd3As2 Dirac semimetal, an important signature of ultra-relativistic Dirac state inaccessible in previous optical experiments. A crossover from quantum to quasi-classical behavior makes it possible to directly probe the mass of Dirac fermions. Importantly, Cr doping allows for a Dirac mass acquisition and topological phase transition enabling a desired dynamic control of Dirac fermions. Corroborating with the density-functional theory calculations, we show that the mass generation is essentially driven by explicit C4 rotation symmetry breaking and the resultant Dirac gap engineering through Cr substitution for Cd atoms. The manipulation of the system symmetry and Dirac mass in Cd3As2 thin films provides a tuning knob to explore the exotic states stemming from the parent phase of Dirac semimetals.

cond-mat.mtrl-sci↗

arXiv2015

ReS2-based field-effect transistors and photodetectors

Atomically-thin two-dimensional (2D) layered transition metal dichalcogenides (TMDs) have been extensively studied in recent years because of their appealing electrical and optical properties. Here, we report on the fabrication of ReS2 field-effect transistors via the encapsulation of ReS2 nanosheets in a high-\k{appa} Al2O3 dielectric environment. Low-temperature transport measurements allowed us to observe a direct metal-to-insulator transition originating from strong electron-electron interactions. Remarkably, the photodetectors based on ReS2 exhibit gate-tunable photoresponsivity up to 16.14 A/W and external quantum efficiency reaching 3,168 %, showing a competitive device performance to those reported in graphene, MoSe2, GaS and GaSe-based photodetectors. Our study unambiguously distinguishes ReS2 as a new candidate for future applications in electronics and optoelectronics.

cond-mat.mtrl-sci↗

arXiv2015

Magnetotransport properties of Cd3As2 nanostructures

Three-dimensional (3D) topological Dirac semimetal is a new kind of material that has a linear energy dispersion in 3D momentum space and can be viewed as an analog of graphene. Extensive efforts have been devoted to the understanding of bulk materials, but yet it remains a challenge to explore the intriguing physics in low-dimensional Dirac semimetals. Here, we report on the synthesis of Cd3As2 nanowires and nanobelts and a systematic investigation of their magnetotransport properties. Temperature-dependent ambipolar behavior is evidently demonstrated, suggesting the presence of finite-size of bandgap in nanowires. Cd3As2 nanobelts, however, exhibit metallic characteristics with a high carrier mobility exceeding 32,000 cm2V-1s-1 and pronounced anomalous double-period Shubnikov-de Haas (SdH) oscillations. Unlike the bulk counterpart, the Cd3As2 nanobelts reveal the possibility of unusual change of the Fermi sphere owing to the suppression of the dimensionality. More importantly, their SdH oscillations can be effectively tuned by the gate voltage. The successful synthesis of Cd3As2 nanostructures and their rich physics open up exciting nanoelectronic applications of 3D Dirac semimetals.

cond-mat.mtrl-sci↗

arXiv2014

Analysis on Irreversible Processes using the Phase-Field Variational Approach with the Entropy or Energy Functional

The variational approach usually used in phase field models (PFVA) is applied here to analyse complex irreversible processes such as thermoelectric (TE) effects and thermally driven mass transport (TDMT). Complex irreversible processes arise from the coupling effects between simple irreversible processes. Each simple irreversible process is assiciated with an entropy or energy density function. During complex irreversible processes with multiple fields present, this entropy or energy density function is assumed to be dependent on all independent field variables. Using the total entropy functionals, the TE effects and TDMT are analysed and important kinetic coefficients such as the Seebeck coefficient and the heat of transport are determined with straightforward physical contents. Using the total energy functionals, the linear irreversible processes are analysed with the Onsager approach and the nonlinear irreversible processes with PFVA. It is found both the Onsager's relations and the fluxes defined using PFVA guarantee the satisfaction of the first law of thermodynamics during the process of conversion of energies. To analyze the diffusion process under the influence of elasticity, PFVA is also modified to incorporate the reversible evolution of elastic fields. It is shown energies are conserved via both the irreversible diffusion process and the reversible evolution of the elastic fields. Finally, PFVA is generalized to study nonequilibrium thermodynamics using an extra kinetic contribution to the entropy density function. The analyses can be extended to a nonequilibrium thermodynamic system with multiple physical fields present. Thus, it is believed PFVA has the potential of not only significantly advancing our understanding of the thermodynamics of irreversible processes, but also making thermodynamics as a discipline and the study of it truly dynamic.

cond-mat.stat-mech↗