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Yu Zhang

Publications and source records attributed to Yu Zhang.

At least 1,459 records · Page 81Linked to original sources
arXiv2019

Optimizing Quantum Programs against Decoherence: Delaying Qubits into Quantum Superposition

Quantum computing technology has reached a second renaissance in the last decade. However, in the NISQ era pointed out by John Preskill in 2018, quantum noise and decoherence, which affect the accuracy and execution effect of quantum programs, cannot be ignored and corrected by the near future NISQ computers. In order to let users more easily write quantum programs, the compiler and runtime system should consider underlying quantum hardware features such as decoherence. To address the challenges posed by decoherence, in this paper, we propose and prototype QLifeReducer to minimize the qubit lifetime in the input OpenQASM program by delaying qubits into quantum superposition. QLifeReducer includes three core modules, i.e.,the parser, parallelism analyzer and transformer. It introduces the layered bundle format to express the quantum program, where a set of parallelizable quantum operations is packaged into a bundle. We evaluate quantum programs before and after transformed by QLifeReducer on both real IBM Q 5 Tenerife and the self-developed simulator. The experimental results show that QLifeReducer reduces the error rate of a quantum program when executed on IBMQ 5 Tenerife by 11%; and can reduce the longest qubit lifetime as well as average qubit lifetime by more than 20% on most quantum workloads.

quant-ph↗
arXiv2019

Learning to Speak Fluently in a Foreign Language: Multilingual Speech Synthesis and Cross-Language Voice Cloning

We present a multispeaker, multilingual text-to-speech (TTS) synthesis model based on Tacotron that is able to produce high quality speech in multiple languages. Moreover, the model is able to transfer voices across languages, e.g. synthesize fluent Spanish speech using an English speaker's voice, without training on any bilingual or parallel examples. Such transfer works across distantly related languages, e.g. English and Mandarin. Critical to achieving this result are: 1. using a phonemic input representation to encourage sharing of model capacity across languages, and 2. incorporating an adversarial loss term to encourage the model to disentangle its representation of speaker identity (which is perfectly correlated with language in the training data) from the speech content. Further scaling up the model by training on multiple speakers of each language, and incorporating an autoencoding input to help stabilize attention during training, results in a model which can be used to consistently synthesize intelligible speech for training speakers in all languages seen during training, and in native or foreign accents.

cs.CL↗
arXiv2019

Probing invisible decay of dark photon at BESIII and future STCF via monophoton searches

We propose to search the monophoton events at the BESIII detector and future Super Tau Charm Factory to probe the sub-GeV dark photon decay into lighter dark matter. We compute the cross section due to the dark photon associated a standard model photon production, and study the corresponding standard model irreducible/reducible backgrounds. By using the data about 17 fb$^{-1}$ collected at the BESIII detector since 2011, we derive new leading limits of the mixing strength $\varepsilon$, $\varepsilon\lesssim(1.1-1.6)\times 10^{-4}$, in the mass range of 0.04 GeV $\lesssim m_{A^\prime} \lesssim$ 3 GeV. With 30 ab$^{-1}$ data, STCF running at $\sqrt{s} = 2$ GeV, can probe $\varepsilon$ down to 5.1$\times 10^{-6}$ when $m_{A^\prime}=1$ GeV. For models of scalar and fermionic light thermal dark matter production via dark photon, we present the constrains on the dimensionless dark matter parameter $y=\varepsilon^2α_D(m_χ/m_{A^\prime})^4$ as function of the DM mass $m_χ$ at BESIII and future STCF, conventionally assuming the dark coupling constant $α_D=0.5$ and $m_{A^\prime}=3 m_χ$. We find that BESIII can exclude model of scalar, Majorana, and pseudo-Dirac (with a small splitting) DM for the mass region 0.03$\sim$1 GeV, 0.04$\sim$1 GeV and 0.4$\sim$1 GeV respectively. For values $α_D\lesssim 0.005$, combining the results from 2 GeV STCF with 30 ab$^{-1}$ data and BaBar, one can exclude the above three DM models in the mass region 0.001 GeV $\lesssim m_χ \lesssim$ 1 GeV.

hep-ph↗
arXiv2019

Energy-efficient Alternating Iterative Secure Structure of Maximizing Secrecy Rate for Directional Modulation Networks

In a directional modulation (DM) network, the issues of security and privacy have taken on an increasingly important role. Since the power allocation of confidential message and artificial noise will make a constructive effect on the system performance, it is important to jointly consider the relationship between the beamforming vectors and the power allocation (PA) factors. To maximize the secrecy rate (SR), an alternating iterative structure (AIS) between the beamforming and PA is proposed. With only two or three iterations, it can rapidly converge to its rate ceil. Simulation results indicate that the SR performance of proposed AIS is much better than the null-space projection (NSP) based PA strategy in the medium and large signal-to-noise ratio (SNR) regions, especially when the number of antennas at the DM transmitter is small.

cs.IT↗
arXiv2019

Super-Resolution Channel Estimation for Arbitrary Arrays in Hybrid Millimeter-Wave Massive MIMO Systems

This paper develops efficient channel estimation techniques for millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems under practical hardware limitations, including an arbitrary array geometry and a hybrid hardware structure. Taking on an angle-based approach, this work adopts a generalized array manifold separation approach via Jacobi-Anger approximation, which transforms a non-ideal, non-uniform array manifold into a virtual array domain with a desired uniform geometric structure to facilitate super-resolution angle estimation and channel acquisition. Accordingly, structure-based optimization techniques are developed to effectively estimate both the channel covariance and the instantaneous channel state information (CSI) within a short sensing time. In particular, the difference in time-variation of channel path angles and path gains is capitalized to design a two-step CSI estimation scheme that can quickly sense fading channels. Theoretical results are provided on the fundamental limits of the proposed technique in terms of sample efficiency. For computational efficiency, a fast iterative algorithm is developed via the alternating direction method of multipliers. Other related issues such as spurious-peak cancellation in nonuniform linear arrays and extensions to higher-dimensional cases are also discussed. Simulations testify the effectiveness of the proposed approaches in hybrid mmWave massive MIMO systems with arbitrary arrays.

eess.SP↗
arXiv2019

Topological Quillen localization of structured ring spectra

The aim of this short paper is two-fold: (i) to construct a TQ-localization functor on algebras over a spectral operad O, in the case where no connectivity assumptions are made on the O-algebras, and (ii) more generally, to establish the associated TQ-local homotopy theory as a left Bousfield localization of the usual model structure on O-algebras, which itself is almost never left proper, in general. In the resulting TQ-local homotopy theory, the "weak equivalences" are the TQ-homology equivalences, where "TQ-homology" is short for topological Quillen homology, which is also weakly equivalent to stabilization of O-algebras. More generally, we establish these results for TQ-homology with coefficients in a spectral algebra A. A key observation, that goes back to the work of Goerss-Hopkins on moduli problems, is that the usual left properness assumption may be replaced with a strong cofibration condition in the desired subcell lifting arguments: Our main result is that the TQ-local homotopy theory can be established (e.g., a semi-model structure in the sense of Goerss-Hopkins and Spitzweck, that is both cofibrantly generated and simplicial) by localizing with respect to a set of strong cofibrations that are TQ-equivalences.

math.AT↗
arXiv2019

Integrating neural networks into the blind deblurring framework to compete with the end-to-end learning-based methods

Recently, end-to-end learning-based methods based on deep neural network (DNN) have been proven effective for blind deblurring. Without human-made assumptions and numerical algorithms, they are able to restore images with fewer artifacts and better perceptual quality. However, in practice, we also find some of their drawbacks. Without the theoretical guidance, these methods can not perform well when the motion is complex and sometimes generate unreasonable results. In this paper, for overcoming these drawbacks, we integrate deep convolution neural networks into conventional deblurring framework. Specifically, we build Stacked Estimation Residual Net (SEN) to estimate the motion flow map and Recurrent Prior Generative and Adversarial Net (RP-GAN) to learn the implicit image prior in the optimization model. Comparing with state-of-the-art end-to-end learning-based methods, our method restores reasonable details and shows better generalization ability.

cs.CV↗
arXiv2019

An optical and X-ray study of the contact binary, BH Cassiopeiae

We present the revised and high quality CCD time series observations in 2017 and 2018 of the W UMa-type contact binary BH~Cas. The combination of our new determinations of minimum times and those collected from the literatures reveal a long-term period increase with a rate of $\textit{dP/dt}\,=\,+3.27 \times 10^{-7} \textrm{d}\,\textrm{yr}^{-1}$, which can be accounted for by angular momentum transfer as the less-massive component loses its mass to the more massive one. One cyclical oscillation ($A'=0.00300$~days and $P'=20.09$~yrs) superimposed on the long-term period increase tendency is attributed to one additional object that orbits BH Cas. The low-resolution spectra of this source are observed at phase $\sim$0.0 and $\sim$0.5 in 2018 and 2019, and the spectral types are identified as K3V$\,\pm\,$1 and G8V$\,\pm\,$2. According to the luminosity contributions and spectra at these phases, the spectral type of the primary star is close to K3V$\,\pm\,$1. We infer a cool spot on the hotter and less-massive component to fit the asymmetry of light curves. In addition, changes in the location, temperature, and area of spots on the secondary star in different observations may indicate that the magnetic field activity of the secondary is more active than that of the primary. Such strong spot activities and optical flare are both detected at the same time from a W UMa-type star for the first time. With the \emph{XMM-Newton} observations taken in 2003 and 2012, the X-ray light curve is obtained and the X-ray spectra can be well described with a black-body or a bremsstrahlung model. The soft X-ray luminosity of BH Cas is estimated as 8.8\,--\,9.7$\,\times\,10^{30}$\,erg\,s$^{-1}$.

astro-ph.SR↗
arXiv2019

Brain Network Construction and Classification Toolbox (BrainNetClass)

Brain functional network has become an increasingly used approach in understanding brain functions and diseases. Many network construction methods have been developed, whereas the majority of the studies still used static pairwise Pearson's correlation-based functional connectivity. The goal of this work is to introduce a toolbox namely "Brain Network Construction and Classification" (BrainNetClass) to the field to promote more advanced brain network construction methods. It comprises various brain network construction methods, including some state-of-the-art methods that were recently developed to capture more complex interactions among brain regions along with connectome feature extraction, reduction, parameter optimization towards network-based individualized classification. BrainNetClass is a MATLAB-based, open-source, cross-platform toolbox with graphical user-friendly interfaces for cognitive and clinical neuroscientists to perform rigorous computer-aided diagnosis with interpretable result presentations even though they do not possess neuroimage computing and machine learning knowledge. We demonstrate the implementations of this toolbox on real resting-state functional MRI datasets. BrainNetClass (v1.0) can be downloaded from https://github.com/zzstefan/BrainNetClass.

q-bio.NC↗
arXiv2019

Federated Hierarchical Hybrid Networks for Clickbait Detection

Online media outlets adopt clickbait techniques to lure readers to click on articles in a bid to expand their reach and subsequently increase revenue through ad monetization. As the adverse effects of clickbait attract more and more attention, researchers have started to explore machine learning techniques to automatically detect clickbaits. Previous work on clickbait detection assumes that all the training data is available locally during training. In many real-world applications, however, training data is generally distributedly stored by different parties (e.g., different parties maintain data with different feature spaces), and the parties cannot share their data with each other due to data privacy issues. It is challenging to build models of high-quality federally for detecting clickbaits effectively without data sharing. In this paper, we propose a federated training framework, which is called federated hierarchical hybrid networks, to build clickbait detection models, where the titles and contents are stored by different parties, whose relationships must be exploited for clickbait detection. We empirically demonstrate that our approach is effective by comparing our approach to the state-of-the-art approaches using datasets from social media.

cs.IR↗
arXiv2019

Photometric investigations on two totally eclipsing contact binaries: V342 UMa and V509 Cam

By analyzing two sets of complete $BVR_cI_c$ light curves of V342 UMa and three sets of complete $BVR_cI_c$ light curves of V509 Cam, we determined that the two systems are both W-subtype contact binaries and that V342 UMa shows a shallow contact configuration, while V509 Cam exhibits a medium contact configuration. Since both of them are totally eclipsing binaries, the physical parameters derived only by the photometric light curves are reliable.Meanwhile, the period changes of the two targets were analyzed based on all available eclipsing times. We discovered that V342 UMa shows long-term period decrease with a rate of $-1.02(\pm0.54)\times10^{-7}$ days/year and that V509 Cam exhibits long-term period increase with a rate of $3.96(\pm0.90)\times10^{-8}$ days/year. Both the conservative mass transfer and AML via magnetic stellar winds can interpret the long-term period decrease of V342 UMa. The long-term period increase of V509 Cam can be explained by mass transfer from the less massive star to the more massive one. The absolute parameters of the two binaries were estimated according to the Gaia distances and our derived photometric solution results. This method can be extended to other contact binaries without radial velocities but with reliable photometric solutions. The evolutionary states of them were discussed, we found that they reveal identical properties of other W-subtype contact systems.

astro-ph.SR↗
arXiv2019

Cycle-consistency training for end-to-end speech recognition

This paper presents a method to train end-to-end automatic speech recognition (ASR) models using unpaired data. Although the end-to-end approach can eliminate the need for expert knowledge such as pronunciation dictionaries to build ASR systems, it still requires a large amount of paired data, i.e., speech utterances and their transcriptions. Cycle-consistency losses have been recently proposed as a way to mitigate the problem of limited paired data. These approaches compose a reverse operation with a given transformation, e.g., text-to-speech (TTS) with ASR, to build a loss that only requires unsupervised data, speech in this example. Applying cycle consistency to ASR models is not trivial since fundamental information, such as speaker traits, are lost in the intermediate text bottleneck. To solve this problem, this work presents a loss that is based on the speech encoder state sequence instead of the raw speech signal. This is achieved by training a Text-To-Encoder model and defining a loss based on the encoder reconstruction error. Experimental results on the LibriSpeech corpus show that the proposed cycle-consistency training reduced the word error rate by 14.7% from an initial model trained with 100-hour paired data, using an additional 360 hours of audio data without transcriptions. We also investigate the use of text-only data mainly for language modeling to further improve the performance in the unpaired data training scenario.

cs.CL↗
arXiv2019

A Novel ground state in a new dimer iridate Ba13Ir6O30 with Ir6+(5d3) Ions

We have synthesized and studied a new iridate, Ba13Ir6O30, with unusual Ir oxidation states: 2/3 Ir6+(5d3) ions and 1/3 Ir5+(5d4) ions. Its crystal structure features dimers of face-sharing IrO6 octahedra, and IrO6 monomers, that are linked via long, zigzag Ir-O-Ba-O-Ir pathways. Nevertheless, Ba13Ir6O30 exhibits two transitions at TN1 = 4.7 K and TN2 = 1.6 K. This magnetic order is accompanied by a huge Sommerfeld coefficient 200 mJ/mole K below TN2, signaling a coexisting frustrated/disordered state persisting down to at least 0.05 K. This iridate hosts unusually large Jeff=3/2 degrees of freedom, which is enabled by strong spin-orbit interactions (SOI) in the monomers with Ir6+ ions and a joint effect of molecular orbitals and SOI in the dimers occupied by Ir5+ and Ir6+ ions. Features displayed by the magnetization and heat capacity suggest that the combination of covalency, SOI and large effective spins leads to highly frustrated ferrimagnetic ordering, possibly into a skyrmion crystal, a novelty of this new high-spin iridate.

cond-mat.str-el↗
arXiv2019

Experimental demonstration of quantum walks with initial superposition states

The preparation of initial superposition states of discrete-time quantum walks (DTQWs) are necessary for the study and applications of DTQWs. In linear optics, it is easy to prepare initial superposition states of the coin, which are always encoded by polarization states; while the preparation of superposition states of the walker is challenging. Based on a novel encoding method, we here propose a DTQW protocol in linear optics which enables the preparation of arbitrary initial superposition states of the walker and the coin. With this protocol, we report an experimental demonstration of DTQW with the walker initially in superposition states, by using only passive linear-optical elements. The effects of the walker's different initial superposition states on the spread speed of the DTQW and on the entanglement between the coin and the walker are also experimentally investigated, which have not been reported before. When the walker starts with superposition states, we show that the properties of DTQW are very different from those of DTQW starting with a single position. Our findings reveal different properties of DTQW and paves an avenue to study DTQW with arbitrary initial states. Moreover, the encoding method enables one to encode an arbitrary high-dimensional quantum state using a single physical qubit and may be adopted to implement other quantum information tasks.

quant-ph↗
arXiv2019

Non-conforming Crouzeix-Raviar element approximation for Stekloff eigenvalues in inverse scattering

In this paper, we use the non-conforming Crouzeix-Raviart element method to solve a Stekloff eigenvalue problem arising in inverse scattering. The weak formulation corresponding to this problem is non-selfadjoint and does not satisfy $H^{1}$-elliptic condition,and its Crouzeix-Raviart element discretization does not meet the Strang lemma condition. We use the standard duality techniques to prove an extension of Strang lemma. And we prove the convergence and error estimate of discrete eigenvalues and eigenfunctions using the spectral perturbation theory for compact operators. Finally, we present some numerical examples not only on uniform meshes but also in an adaptive refined meshes to show that the Crouzeix-Raviart method is efficient for computing real and complex eigenvalues as expected.

math.NA↗
arXiv2019

Pulsations of the SX Phe Star BL Camelopardalis

We carried out photometric observations of the SX Phe star BL Cam in 2014, 2017 and 2018 using Nanshan 1-m telescope. In addition to the dominated frequency of 25.5790(3) cd$^{-1}$ and its two harmonics, an independent frequency of 25.247 (2) cd$^{-1}$, which is a nonradial mode frequency, was detected from the data in 2014. A total of 123 new times of light maxima were determined from our light curves in the three years, which, together with that published in the literature, were used to analyze the $O$$-$$C$ diagram. The change rate of the main period was derived as (1/P)(dP/dt) = -2.39 (8)$\times$10$^{-8}$ yr$^{-1}$, which is lower than that published in previous literature. A periodical change with a period of 14.01 (9) yr was found in the residuals of the $O$$-$$C$ curve fitting. If it was caused by the light-time effect, BL Cam should be a binary system. The mass of the companion was restricted as low as that of a brown dwarf. No evidence of the triple system suggested by previous authors was shown in our analysis.

astro-ph.SR↗
arXiv2019

Image Quality Assessment for Omnidirectional Cross-reference Stitching

Along with the development of virtual reality (VR), omnidirectional images play an important role in producing multimedia content with immersive experience. However, despite various existing approaches for omnidirectional image stitching, how to quantitatively assess the quality of stitched images is still insufficiently explored. To address this problem, we establish a novel omnidirectional image dataset containing stitched images as well as dual-fisheye images captured from standard quarters of 0$^\circ$, 90$^\circ$, 180$^\circ$ and 270$^\circ$. In this manner, when evaluating the quality of an image stitched from a pair of fisheye images (e.g., 0$^\circ$ and 180$^\circ$), the other pair of fisheye images (e.g., 90$^\circ$ and 270$^\circ$) can be used as the cross-reference to provide ground-truth observations of the stitching regions. Based on this dataset, we further benchmark six widely used stitching models with seven evaluation metrics for IQA. To the best of our knowledge, it is the first dataset that focuses on assessing the stitching quality of omnidirectional images.

cs.CV↗