arXiv subjects

Yu Zhang

Publications and source records attributed to Yu Zhang.

At least 1,441 records · Page 80Linked to original sources

arXiv2019

A framework for quantum homomorphic encryption with experimental demonstration

Quantum homomorphic encryption (QHE) is an encryption method that allows quantum computation to be performed on one party's private data with the program provided by another party, without revealing much information about the data nor the program to the opposite party. We propose a framework for (interactive) QHE based on the universal circuit approach. It contains a subprocedure of calculating a classical linear polynomial, which can be implemented with quantum or classical methods; apart from the subprocedure, the framework has low requirement on the quantum capabilities of the party who provides the circuit. We illustrate the subprocedure using a quite simple classical protocol with some privacy tradeoff. For a special case of such protocol, we obtain a scheme similar to blind quantum computation but with the output on a different party. Another way of implementing the subprocedure is to use a recently studied quantum check-based protocol, which has low requirement on the quantum capabilities of both parties. The subprocedure could also be implemented with a classical additive homomorphic encryption scheme. We demonstrate some key steps of the outer part of the framework in a quantum optics experiment.

quant-ph↗

arXiv2019

Patterning Sn-based EUV resists with low-energy electrons

Extreme Ultraviolet (EUV) lithography is the newest technology that will be used in the semiconductor industry for printing circuitry in the sub-20 nm scale. Low-energy electrons (LEEs) produced upon illumination of resist materials with EUV photons (92 eV) play a central role in the formation of the nanopatterns. However, up to now the details of this process are not well understood. In this work, a novel experimental approach that combines Low-Energy Electron Microscopy (LEEM), Electron Energy Loss Spectroscopy (EELS), and Atomic Force Microscopy (AFM) is used to study changes induced by electrons in the 0-40 eV range in thin films of molecular organometallic EUV resists known as tin-oxo cages. LEEM-EELS spectroscopic experiments were used to detect surface charging upon electron exposure and to estimate the electron landing energy. AFM post-exposure analyses revealed that irradiation of the resist with LEEs leads to the densification of the resist layer associated to carbon loss. The same chemical processes that yield densification render the solubility change responsible for the pattern formation in the lithographic application. Remarkably, electrons as low as 1.2 eV are able to induce chemical reactions in the Sn-based resist. Based on the thickness profiles resulting from LEE exposures in the 3-48 mC/cm 2 dose range, a simplified reaction model is proposed where the resist undergoes sequential chemical reactions, yielding first a sparsely cross-linked network, followed by the formation of a denser cross-linked network. This model allows us to estimate a maximum reaction volume on the initial material of 0.15 nm 3 per incident electron in the energy range studied, which means that less than 10 LEEs per molecule on average are needed to turn the material insoluble and thus render a pattern.

physics.app-ph↗

arXiv2019

Non-Adiabatic Molecular Dynamics of Molecules in the Presence of Strong Light-Matter Interactions

When the interaction between a molecular system and confined light modes in an optical or plasmonic cavity is strong enough to overcome the dissipative process, hybrid light-matter states (polaritons) become the fundamental excitations in the system. The mixing between the light and matter characters modifies the photophysical and photochemical properties. Especially, it was reported that these polaritons can be employed to control photochemical reactions, charge and energy transfer, and other processes. In addition, according to recent studies, vibrational strong coupling can be employed to resonantly enhance the thermally-activated chemical reactions. In this work, a theoretical model and an efficient numerical method for studying the dynamics of molecules strongly interacting with quantum light are developed based on non-adiabatic excited-state molecular dynamics. The methodology was employed to study the \textit{cis-trans} photoisomerization of a realistic molecule in a cavity. Numerical simulations demonstrate that the photochemical reactions can be controlled by tuning the properties of the cavity. In the calculated example, the isomerization is suppressed when polaritonic states develop a local minimum on the lower polaritonic state. Moreover, the observed reduction of isomerization is tunable via the photon energy and light-molecule coupling strength. But the fluctuation in transition dipole screens the effect of light-matter, which makes it harder to tune the photochemical properties via the coupling strength. These insights suggest quantum control of photochemical reactions is possible by specially designed photonic or plasmonic cavities.

cond-mat.mes-hall↗

arXiv2019

Speech Recognition with Augmented Synthesized Speech

Recent success of the Tacotron speech synthesis architecture and its variants in producing natural sounding multi-speaker synthesized speech has raised the exciting possibility of replacing expensive, manually transcribed, domain-specific, human speech that is used to train speech recognizers. The multi-speaker speech synthesis architecture can learn latent embedding spaces of prosody, speaker and style variations derived from input acoustic representations thereby allowing for manipulation of the synthesized speech. In this paper, we evaluate the feasibility of enhancing speech recognition performance using speech synthesis using two corpora from different domains. We explore algorithms to provide the necessary acoustic and lexical diversity needed for robust speech recognition. Finally, we demonstrate the feasibility of this approach as a data augmentation strategy for domain-transfer. We find that improvements to speech recognition performance is achievable by augmenting training data with synthesized material. However, there remains a substantial gap in performance between recognizers trained on human speech those trained on synthesized speech.

cs.CL↗

arXiv2019

Wide-range Prandtl/Schmidt number power spectrum of optical turbulence and its application to oceanic light propagation

Light influenced by the turbulent ocean can be fully characterized with the help of the power spectrum of the water's refractive index fluctuations, resulting from the combined effect of two scalars, temperature and salinity concentration advected by the velocity field. The Nikishovs' model [ Fluid Mech. Res. 27, 8298 (2000)] frequently used in the analysis of light evolution through the turbulent ocean channels is the linear combination of the temperature spectrum, the salinity spectrum and their co-spectrum, each being described by an approximate expression developed by Hill [ J. Fluid Mech. 88, 541562 (1978)] in the first of his four suggested models. The fourth of the Hill's models provides much more precise power spectrum than the first one expressed via a non-linear differential equation that does not have a closed-form solution. We develop an accurate analytic approximation to the fourth Hill's model valid for Prandtl/Schmidt numbers in the interval [3, 3000] and use it for the development of a more precise oceanic power spectrum. To illustrate the advantage of our model, we include numerical examples relating to the spherical wave scintillation index evolving in the underwater turbulent channels with different average temperatures, and, hence, different Prandtl numbers for temperature and different Schmidt numbers for salinity. Since our model is valid for a large range of Prandtl number (or/and Schmidt number), it can be readily adjusted to oceanic waters with seasonal or extreme average temperature and/or salinity or any other turbulent fluid with one or several advected quantities.

physics.ao-ph↗

arXiv2019

Selectivity or Invariance: Boundary-aware Salient Object Detection

Typically, a salient object detection (SOD) model faces opposite requirements in processing object interiors and boundaries. The features of interiors should be invariant to strong appearance change so as to pop-out the salient object as a whole, while the features of boundaries should be selective to slight appearance change to distinguish salient objects and background. To address this selectivity-invariance dilemma, we propose a novel boundary-aware network with successive dilation for image-based SOD. In this network, the feature selectivity at boundaries is enhanced by incorporating a boundary localization stream, while the feature invariance at interiors is guaranteed with a complex interior perception stream. Moreover, a transition compensation stream is adopted to amend the probable failures in transitional regions between interiors and boundaries. In particular, an integrated successive dilation module is proposed to enhance the feature invariance at interiors and transitional regions. Extensive experiments on six datasets show that the proposed approach outperforms 16 state-of-the-art methods.

cs.CV↗

arXiv2019

Expected Sarsa($λ$) with Control Variate for Variance Reduction

Off-policy learning is powerful for reinforcement learning. However, the high variance of off-policy evaluation is a critical challenge, which causes off-policy learning falls into an uncontrolled instability. In this paper, for reducing the variance, we introduce control variate technique to $\mathtt{Expected}$ $\mathtt{Sarsa}$($λ$) and propose a tabular $\mathtt{ES}$($λ$)-$\mathtt{CV}$ algorithm. We prove that if a proper estimator of value function reaches, the proposed $\mathtt{ES}$($λ$)-$\mathtt{CV}$ enjoys a lower variance than $\mathtt{Expected}$ $\mathtt{Sarsa}$($λ$). Furthermore, to extend $\mathtt{ES}$($λ$)-$\mathtt{CV}$ to be a convergent algorithm with linear function approximation, we propose the $\mathtt{GES}$($λ$) algorithm under the convex-concave saddle-point formulation. We prove that the convergence rate of $\mathtt{GES}$($λ$) achieves $\mathcal{O}(1/T)$, which matches or outperforms lots of state-of-art gradient-based algorithms, but we use a more relaxed condition. Numerical experiments show that the proposed algorithm performs better with lower variance than several state-of-art gradient-based TD learning algorithms: $\mathtt{GQ}$($λ$), $\mathtt{GTB}$($λ$) and $\mathtt{ABQ}$($ζ$).

cs.LG↗

arXiv2019

Gradient Q$(σ, λ)$: A Unified Algorithm with Function Approximation for Reinforcement Learning

Full-sampling (e.g., Q-learning) and pure-expectation (e.g., Expected Sarsa) algorithms are efficient and frequently used techniques in reinforcement learning. Q$(σ,λ)$ is the first approach unifies them with eligibility trace through the sampling degree $σ$. However, it is limited to the tabular case, for large-scale learning, the Q$(σ,λ)$ is too expensive to require a huge volume of tables to accurately storage value functions. To address above problem, we propose a GQ$(σ,λ)$ that extends tabular Q$(σ,λ)$ with linear function approximation. We prove the convergence of GQ$(σ,λ)$. Empirical results on some standard domains show that GQ$(σ,λ)$ with a combination of full-sampling with pure-expectation reach a better performance than full-sampling and pure-expectation methods.

cs.LG↗

arXiv2019

Gate-tunable Rashba spin-orbit coupling and spin polarization at diluted oxide interfaces

Diluted oxide interface of LaAl1-xMnxO/SrTiO3 (LAMO/STO) provides a new way of tuning the ground states of the interface between the two band insulators of LAO and STO from metallic/superconducting to highly insulating. Increasing the Mn doping level (x) leads to a delicate control of the carrier density as well as a raise in the electron mobility and spin polarization. Herein, we demonstrate a tunable Rashba spin-orbit coupling (SOC) and spin polarization of LAMO/STO (0.2 <= x <= 0.3) by applying a back gate. The presence of SOC causes the splitting of energy band into two branches by a spin splitting energy. The maximum spin splitting energy depends on the Mn doping and decreases with the increasing Mn content and then vanishes at x = 0.3. The carrier density dependence of the spin splitting energy for different compositions shows a dome-shaped behavior with a maximum at different normalized carrier density. These findings have not yet been observed in LAO/STO interfaces. A fully back-gate-tunable spin-polarized 2DEL is observed at the interface with x = 0.3 where only dxy orbits are populated (5.3E12 cm-2 <= ns <= 1.0E13 cm-2). The present results shed light on unexplored territory in SOC at STO-base oxide heterostructures and make LAMO/STO an intriguing platform for spin-related phenomena in 3d-electron systems.

cond-mat.str-el↗

arXiv2019

Heterogeneous Domain Adaptation via Soft Transfer Network

Heterogeneous domain adaptation (HDA) aims to facilitate the learning task in a target domain by borrowing knowledge from a heterogeneous source domain. In this paper, we propose a Soft Transfer Network (STN), which jointly learns a domain-shared classifier and a domain-invariant subspace in an end-to-end manner, for addressing the HDA problem. The proposed STN not only aligns the discriminative directions of domains but also matches both the marginal and conditional distributions across domains. To circumvent negative transfer, STN aligns the conditional distributions by using the soft-label strategy of unlabeled target data, which prevents the hard assignment of each unlabeled target data to only one category that may be incorrect. Further, STN introduces an adaptive coefficient to gradually increase the importance of the soft-labels since they will become more and more accurate as the number of iterations increases. We perform experiments on the transfer tasks of image-to-image, text-to-image, and text-to-text. Experimental results testify that the STN significantly outperforms several state-of-the-art approaches.

cs.LG↗

arXiv2019

FLEET: Butterfly Estimation from a Bipartite Graph Stream

We consider space-efficient single-pass estimation of the number of butterflies, a fundamental bipartite graph motif, from a massive bipartite graph stream where each edge represents a connection between entities in two different partitions. We present a space lower bound for any streaming algorithm that can estimate the number of butterflies accurately, as well as FLEET, a suite of algorithms for accurately estimating the number of butterflies in the graph stream. Estimates returned by the algorithms come with provable guarantees on the approximation error, and experiments show good tradeoffs between the space used and the accuracy of approximation. We also present space-efficient algorithms for estimating the number of butterflies within a sliding window of the most recent elements in the stream. While there is a significant body of work on counting subgraphs such as triangles in a unipartite graph stream, our work seems to be one of the few to tackle the case of bipartite graph streams.

cs.DS↗

arXiv2019

Lower bounds for eigenvalues of the Steklov eigenvalue problem with variable coefficients

In this paper, using new correction to the Crouzeix-Raviart finite element eigenvalue approximations, we obtain lower eigenvalue bounds for the Steklov eigenvalue problem with variable coefficients on d-dimensional domains (d = 2,3). In addition, we prove that the corrected eigenvalues asymptotically converge to the exact ones from below whether the eigenfunctions are singular or smooth and whether the eigenvalues are large enough or not. Further, we prove that the corrected eigenvalues still maintain the same convergence order as that of uncorrected eigenvalues. Finally, numerical experiments validate our theoretical results.

math.NA↗

arXiv2019

ADMM Enabled Hybrid Precoding in Wideband Distributed Phased Arrays Based MIMO Systems

Distributed phased arrays based multiple-input multiple-output (DPA-MIMO) is a recently proposed highly reconfigurable architecture enabling both spatial multiplexing and beamforming in millimeter-wave (mmWave) systems. In this work, we focus on coping with the hybrid precoding for the wideband DPA-MIMO system with orthogonal frequency division multiplexing (OFDM) modulation. More specifically, we propose an alternating direction method of multipliers (ADMM) enabled hybrid precoding approach based on an alternating optimization framework, abbreviated to ADMM-AltMin, for such cooperative array-of-subarrays structures. Simulation results show that the proposed ADMM-AltMin method achieves favourable performance with practical quantization of phase shifters taken into account.

cs.IT↗

arXiv2019

Multi-Spectral Visual Odometry without Explicit Stereo Matching

Multi-spectral sensors consisting of a standard (visible-light) camera and a long-wave infrared camera can simultaneously provide both visible and thermal images. Since thermal images are independent from environmental illumination, they can help to overcome certain limitations of standard cameras under complicated illumination conditions. However, due to the difference in the information source of the two types of cameras, their images usually share very low texture similarity. Hence, traditional texture-based feature matching methods cannot be directly applied to obtain stereo correspondences. To tackle this problem, a multi-spectral visual odometry method without explicit stereo matching is proposed in this paper. Bundle adjustment of multi-view stereo is performed on the visible and the thermal images using direct image alignment. Scale drift can be avoided by additional temporal observations of map points with the fixed-baseline stereo. Experimental results indicate that the proposed method can provide accurate visual odometry results with recovered metric scale. Moreover, the proposed method can also provide a metric 3D reconstruction in semi-dense density with multi-spectral information, which is not available from existing multi-spectral methods.

cs.CV↗

arXiv2019

Scanning tunneling microscope characterizations of a circular graphene resonator realized with p-p junctions

Using low-temperature high-magnetic-field scanning tunneling microscopy and spectroscopy (STM/STS), we systematically study a graphene quantum dot (GQD) defined by a circular graphene p-p junction. Inside the GQD, we observe a series of quasi-bound states arising from whispering-gallery-mode (WGM) confinement of the circular junction and directly visualize these quasi-bound states down to atomic dimensions. By applying a strong magnetic field, a large jump in energy of the quasi-bound states, which is about one-half the energy spacing between the quasi-bound states, is observed. Such a behavior results from turning on a π Berry phase of massless Dirac fermions in graphene by a magnetic field. Moreover, our experiment demonstrates that a quasi-bound state splits into two peaks with an energy separation of about 26 meV when the Fermi level crosses the quasi-bound state, indicating that there are strong electron-electron interactions in the GQD.

cond-mat.mes-hall↗

arXiv2019

Relativistic Artificial Molecules Realized by Two Coupled Graphene Quantum Dots

Coupled quantum dots (QDs), usually referred to as artificial molecules, are important not only in exploring fundamental physics of coupled quantum objects, but also in realizing advanced QD devices. However, previous studies have been limited to artificial molecules with nonrelativistic fermions. Here, we show that relativistic artificial molecules can be realized when two circular graphene QDs are coupled to each other. Using scanning tunneling microscopy (STM) and spectroscopy (STS), we observe the formation of bonding and antibonding states of the relativistic artificial molecule and directly visualize these states of the two coupled graphene QDs. The formation of the relativistic molecular states strongly alters distributions of massless Dirac fermions confined in the graphene QDs. Because of the relativistic nature of the molecular states, our experiment demonstrates that the degeneracy of different angular-momentum states in the relativistic artificial molecule can be further lifted by external magnetic fields. Then, both the bonding and antibonding states are split into two peaks.

cond-mat.mes-hall↗

arXiv2019

Evolution properties of coherent Gaussian vortex beams propagating through weak oceanic turbulence and its application for measurement

The cross-spectral density of coherent Gaussian vortex beams propagating through weak oceanic turbulence is derived from extended Huygens-Fresnel principle and Nikishov spectrum. The evolution of a coherent superposition field composed of dual Gaussian vortex beams with $+1$ and $-1$ topological charges respectively through weak oceanic turbulence is investigated in z plane and y plane. It is shown that the non-zero separation distance of two beams in x direction enhances the oceanic turbulence effect on interference light field. The variation of intensity distribution in z plane and on the central axis of two beams in y plane are both related to the strength of oceanic turbulence, separation distance, propagation distance and waist width. The extra fluctuation of the intensity on the central axis of two beams in y plane leads to high sensitivity of oceanic turbulence. This characteristic has potential application in non-contact optical tomography of oceanic turbulence strength along the beam propagation path by lateral scattering intensity.

physics.optics↗

arXiv2019

Double Core Hole Valence-to-Core X-ray Emission Spectroscopy: A Theoretical Exploration Using Time-Dependent Density Functional Theory

With the help of newly developed X-ray free-electron laser (XFEL) sources, creating double core holes simultaneously at the same or different atomic sites in a molecule has now become possible. Double core hole (DCH) X-ray emission is a new form of X-ray nonlinear spectroscopy that can be studied with a XFEL. Here we computationally explore the metal K-edge valence-to-core (VtC) X-ray emission spectroscopy (XES) of metal/metal and metal/ligand double core hole states in a series of transition metal complexes with time-dependent density functional theory. The simulated DCH VtC-XES signals are compared with conventional single core hole (SCH) XES signals. The energy shifts and intensity changes of the DCH emission lines with respect to the corresponding SCH-XES features are fingerprints of the coupling between the second core hole and the occupied orbitals around the DCHs that contain important chemical bonding information of the complex. The core hole localization effect on DCH VtC-XES is also briefly discussed. We theoretically demonstrate that DCH XES provides subtle information on the local electronic structure around metal centers in transition metal complexes beyond conventional linear XES. Our predicted changes from calculations between SCH-XES and DCH-XES features should be detectable with modern XFEL sources.

physics.chem-ph↗