arXiv subjects

Xin Wang

Publications and source records attributed to Xin Wang.

At least 1,729 records · Page 96Linked to original sources

arXiv2017

Periodic and rational solutions of the reduced Maxwell-Bloch equations

We investigate the reduced Maxwell-Bloch (RMB) equations which describe the propagation of short optical pulses in dielectric materials with resonant non-degenerate transitions. The general Nth-order periodic solutions are provided by means of the Darboux transformation, and from two different limiting cases of the obtained general periodic solutions, the Nth-order degenerate periodic and Nth-order rational solutions containing several free parameters with compact determinant representations are derived, respectively. Explicit expressions of these solutions from first to second order are presented. Typical nonlinear wave patterns for the four components of the RMB equations such as single-peak, double-peak-double-dip, double-peak and single-dip structures in the second-order rational solutions are shown. This kind of the rational solutions correspond to rogue waves in the reduced Maxwell-Bloch equations.

nlin.SI↗

arXiv2017

Isobaric Reconstruction of the Baryonic Acoustic Oscillation

In this paper, we report a significant recovery of the linear baryonic acoustic oscillation (BAO) signature by applying the isobaric reconstruction algorithm to the non-linear matter density field. Assuming only the longitudinal component of the displacement being cosmologically relevant, this algorithm iteratively solves the coordinate transform between the Lagrangian and Eulerian frames without requiring any specific knowledge of the dynamics. For dark matter field, it produces the non-linear displacement potential with very high fidelity. The reconstruction error at the pixel level is within a few percent, and is caused only by the emergence of the transverse component after the shell-crossing. As it circumvents the strongest non-linearity of the density evolution, the reconstructed field is well-described by linear theory and immune from the bulk-flow smearing of the BAO signature. Therefore this algorithm could significantly improve the measurement accuracy of the sound horizon scale. For a perfect large-scale structure survey at redshift zero without Poisson or instrumental noise, the fractional error is reduced by a factor of 2.7, very close to the ideal limit with linear power spectrum and Gaussian covariance matrix.

astro-ph.CO↗

arXiv2017

Hybrid quantum device with a carbon nanotube and a flux qubit for dissipative quantum engineering

We describe a hybrid quantum system composed of a micrometer-size carbon nanotube (CNT) longitudinally coupled to a flux qubit. We demonstrate the usefulness of this device for generating high-fidelity nonclassical states of the CNT via dissipative quantum engineering. Sideband cooling of the CNT to its ground state and generating a squeezed ground state, as a mechanical analogue of the optical squeezed vacuum, are two additional examples of the dissipative quantum engineering studied here. Moreover, we show how to generate a long-lived macroscopically-distinct superposition (i.e., a Schrödinger cat-like) state. This cat state can be trapped, under some conditions, in a dark state, as can be verified by detecting the optical response of control fields.

quant-ph↗

arXiv2017

Energy spectrum, exchange interaction and gate crosstalk in a pair of double-quantum-dot system: a molecular orbital calculation

We present a theoretical study of a four-electron four-quantum-dot system based on molecular orbital methods, which hosts a pair of singlet-triplet spin qubits. We explicitly take into account of the admixture of electron wave functions in all dots, and have found that this mixing of wave functions has consequences on the energy spectrum, exchange interaction and the gate crosstalk of the system. Specifically, we have found that when the two singlet-triplet qubits are close enough, some of the states are no longer dominated by the computational basis states and the exchange interaction can not simply be understood as the energy difference between the singlet and triplet states. Using the Hund-Mulliken calculation of the Hubbard parameters, we characterize the effective exchange interaction of the system and have found good agreement with results calculated by taking energy differences where applicable. We have studied the two commonly conceived schemes coupling two qubits, the exchange and capacitive coupling, and have found that when the inter-qubit distance is at certain intermediate values, the two kinds of coupling are comparable in strength, complicating analyses of the evolution of the two qubits. We also investigate the gate crosstalk in the system due to the quantum mechanical mixing of electron states and have found that while this effect is typically very weak, it should not be ignored if the spacing between the qubits are similar to or less than the distance between the double dots that constitute the qubit.

quant-ph↗

arXiv2017

Indistinguishability of bipartite states by positive-partial-transpose operations in the many-copy scenario

A bipartite subspace $S$ is called strongly positive-partial-transpose-unextendible (PPT-unextendible) if for every positive integer $k$, there is no PPT operator supporting on the orthogonal complement of $S^{\otimes k}$. We show that a subspace is strongly PPT-unextendible if it contains a PPT-definite operator (a positive semidefinite operator whose partial transpose is positive definite). Based on these, we are able to propose a simple criterion for verifying whether a set of bipartite orthogonal quantum states is indistinguishable by PPT operations in the many copy scenario. Utilizing this criterion, we further point out that any entangled pure state and its orthogonal complement cannot be distinguished by PPT operations in the many copy scenario. On the other hand, we investigate that the minimum dimension of strongly PPT-unextendible subspaces in an $m\otimes n$ system is $m+n-1$, which involves a generalization of the result that non-positive-partial-transpose (NPT) subspaces can be as large as any entangled subspace [N. Johnston, Phys. Rev. A 87: 064302 (2013)].

quant-ph↗

arXiv2017

Multimodal Transfer: A Hierarchical Deep Convolutional Neural Network for Fast Artistic Style Transfer

Transferring artistic styles onto everyday photographs has become an extremely popular task in both academia and industry. Recently, offline training has replaced on-line iterative optimization, enabling nearly real-time stylization. When those stylization networks are applied directly to high-resolution images, however, the style of localized regions often appears less similar to the desired artistic style. This is because the transfer process fails to capture small, intricate textures and maintain correct texture scales of the artworks. Here we propose a multimodal convolutional neural network that takes into consideration faithful representations of both color and luminance channels, and performs stylization hierarchically with multiple losses of increasing scales. Compared to state-of-the-art networks, our network can also perform style transfer in nearly real-time by conducting much more sophisticated training offline. By properly handling style and texture cues at multiple scales using several modalities, we can transfer not just large-scale, obvious style cues but also subtle, exquisite ones. That is, our scheme can generate results that are visually pleasing and more similar to multiple desired artistic styles with color and texture cues at multiple scales.

cs.CV↗

arXiv2017

Deep Reinforcement Learning for Visual Object Tracking in Videos

In this paper we introduce a fully end-to-end approach for visual tracking in videos that learns to predict the bounding box locations of a target object at every frame. An important insight is that the tracking problem can be considered as a sequential decision-making process and historical semantics encode highly relevant information for future decisions. Based on this intuition, we formulate our model as a recurrent convolutional neural network agent that interacts with a video overtime, and our model can be trained with reinforcement learning (RL) algorithms to learn good tracking policies that pay attention to continuous, inter-frame correlation and maximize tracking performance in the long run. The proposed tracking algorithm achieves state-of-the-art performance in an existing tracking benchmark and operates at frame-rates faster than real-time. To the best of our knowledge, our tracker is the first neural-network tracker that combines convolutional and recurrent networks with RL algorithms.

cs.CV↗

arXiv2017

The Grism Lens-Amplified Survey from Space (GLASS). XI. Detection of CIV in Multiple Images of $z=6.11$ Ly$α$ Emitter Behind RXCJ2248.7-4431

The CIII] and CIV rest-frame UV emission lines are powerful probes of the ionizations states of galaxies. They have furthermore been suggested as alternatives for spectroscopic redshift confirmation of objects at the epoch of reionization ($z>6$), where the most frequently used redshift indicator, Ly$α$, is attenuated by the high fraction of neutral hydrogen in the inter-galactic medium. However, currently only very few confirmations of carbon UV lines at these high redshifts exist, making it challenging to quantify these claims. Here, we present the detection of CIV$λλ$1548,1551Å in \HST\ slitless grism spectroscopy obtained by GLASS of a Ly$α$ emitter at $z=6.11$ multiply imaged by the massive foreground galaxy cluster RXJ2248. The CIV emission is detected at the 3--5$σ$ level in two images of the source, with marginal detection in two other images. We do not detect significant CIII]$λλ$1907,1909Å emission implying an equivalent width EW$_\textrm{CIII]}<20$Å (1$σ$) and $\textrm{CIV/CIII}>0.7$ (2$σ$). Combined with limits on the rest-frame UV flux from the HeII$λ$1640Å emission line and the OIII]$λλ$1661,1666Å doublet, we put constraints on the metallicity and the ionization state of the galaxy. The estimated line ratios and equivalent widths do not support a scenario where an AGN is responsible for ionizing the carbon atoms. SED fits including nebular emission lines imply a source with a mass of log(M/M$_\odot)\sim9$, SFR of around 10M$_\odot$/yr, and a young stellar population $<50$Myr old. The source shows a stronger ionizing radiation field than objects with detected CIV emission at $z<2$ and adds to the growing sample of low-mass (log(M/M$_\odot)\lesssim9$) galaxies at the epoch of reionization with strong radiation fields from star formation.

astro-ph.GA↗

arXiv2017

Increasing Trends of Guillain-Barré Syndrome (GBS) and Dengue in Hong Kong

Background: Guillain-Barré Syndrome (GBS) is a common type of severe acute paralytic neuropathy and associated with other virus infections such as dengue fever and Zika. This study investigate the relationship between GBS, dengue, local meteorological factors in Hong Kong and global climatic factors from January 2000 to June 2016. Methods: The correlations between GBS, dengue, Multivariate El Nino Southern Oscillation Index (MEI) and local meteorological data were explored by the Spearman Rank correlations and cross-correlations between these time series. Poisson regression models were fitted to identify nonlinear associations between MEI and dengue. Cross wavelet analysis was applied to infer potential non-stationary oscillating associations among MEI, dengue and GBS. Findings : An increasing trend was found for both GBS cases and imported dengue cases in Hong Kong. We found a weak but statistically significant negative correlation between GBS and local meteorological factors. MEI explained over 12\% of dengue's variations from Poisson regression models. Wavelet analyses showed that there is possible non-stationary oscillating association between dengue and GBS from 2005 to 2015 in Hong Kong. Our study has led to an improved understanding of the timing and relationship between GBS, dengue and MEI.

q-bio.PE↗

arXiv2017

Towards quantum entanglement of micromirrors via a two-level atom and radiation pressure

We propose a method to entangle two distant vibrating microsize mirrors (i.e., mechanical oscillators) in a cavity optomechanical system. In this scheme, we discuss both the resonant and large-detuning conditions, and show that the entanglement of two mechanical oscillators can be achieved with the assistance of a two-level atom and cavity-radiation pressure. In the resonant case, the operation time is relatively short, which is desirable to minimize the effects of decoherence. While in the large-detuning case, the cavity is only virtually excited during the interaction. Therefore, the decay of the cavity is effectively suppressed, which makes the efficient decoherence time of the cavity to be greatly prolonged. Thus, we observe that this virtual-photon process of microscopic objects may induce the entanglement of macroscopic objects. Moreover, in both cases, the generation of entanglement is deterministic and no measurements on the atom and the cavity are required. These are experimentally important. Finally, the decoherence effect and the experimental feasibility of the proposal are briefly discussed.

quant-ph↗

arXiv2017

Clipper: A Low-Latency Online Prediction Serving System

Machine learning is being deployed in a growing number of applications which demand real-time, accurate, and robust predictions under heavy query load. However, most machine learning frameworks and systems only address model training and not deployment. In this paper, we introduce Clipper, a general-purpose low-latency prediction serving system. Interposing between end-user applications and a wide range of machine learning frameworks, Clipper introduces a modular architecture to simplify model deployment across frameworks and applications. Furthermore, by introducing caching, batching, and adaptive model selection techniques, Clipper reduces prediction latency and improves prediction throughput, accuracy, and robustness without modifying the underlying machine learning frameworks. We evaluate Clipper on four common machine learning benchmark datasets and demonstrate its ability to meet the latency, accuracy, and throughput demands of online serving applications. Finally, we compare Clipper to the TensorFlow Serving system and demonstrate that we are able to achieve comparable throughput and latency while enabling model composition and online learning to improve accuracy and render more robust predictions.

cs.DC↗

arXiv2017

Stochastic Averaging for Constrained Optimization with Application to Online Resource Allocation

Existing approaches to resource allocation for nowadays stochastic networks are challenged to meet fast convergence and tolerable delay requirements. The present paper leverages online learning advances to facilitate stochastic resource allocation tasks. By recognizing the central role of Lagrange multipliers, the underlying constrained optimization problem is formulated as a machine learning task involving both training and operational modes, with the goal of learning the sought multipliers in a fast and efficient manner. To this end, an order-optimal offline learning approach is developed first for batch training, and it is then generalized to the online setting with a procedure termed learn-and-adapt. The novel resource allocation protocol permeates benefits of stochastic approximation and statistical learning to obtain low-complexity online updates with learning errors close to the statistical accuracy limits, while still preserving adaptation performance, which in the stochastic network optimization context guarantees queue stability. Analysis and simulated tests demonstrate that the proposed data-driven approach improves the delay and convergence performance of existing resource allocation schemes.

math.OC↗

arXiv2017

Nanotwinned diamond synthesized from multi-core onion carbon

Nano-polycrystalline diamond (NPD) and nanotwinned diamond (NtD) were successfully synthesized in multi-anvil high pressure apparatus at high pressure and high temperature (HPHT) conditions using precursors of onion carbons. We found that the choices of distinct onion carbons with hollow or multi-cored microstructures lead to the synthesis of different diamond products of NPD or NtD ones. High quality NtD with an average twin size of 6.8 nm has been synthesized whose Vickers hardness reaches as high as 180 GPa as measured by indentation hardness experiment. The existence of stacking faults other than various defects in the onion carbon is found to be crucial to form twin boundary in the product. The origin of the extraordinarily high Vickers hardness in the NtD sample is attributable to the high concentration of twin boundary. Our work gave a direct support on the argument that pursuit of nanotwinned microstructure is an effective strategy to harden materials, in good coincidence with the well-known Hall-Petch effect.

cond-mat.mtrl-sci↗

arXiv2017

The Grism lens-amplified survey from space (GLASS). VIII. The influence of the cluster properties on Halpha emitter galaxies at 0.3<z<0.7

Exploiting the data of the Grism Lens-Amplified Survey from Space (GLASS), we characterize the spatial distribution of star formation in 76 high star forming galaxies in 10 clusters at 0.3< z <0.7. All these galaxies are likely restricted to first infall. In a companion paper we contrast the properties of field and cluster galaxies, whereas here we correlate the properties of Hα emitters to a number of tracers of the cluster environment to investigate its role in driving galaxy transformations. Hα emitters are found in the clusters out to 0.5 virial radii, the maximum radius covered by GLASS. The peak of the Hα emission is offset with respect to the peak of the UV-continuum. We decompose this offsets into a radial and tangential component. The radial compo- nent points away from the cluster center in 60% of the cases, with 95% confidence. The decompositions agree with cosmological simulations, i.e. the Hα emission offset correlates with galaxy velocity and ram-pressure stripping signatures. Trends between Hα emitter properties and surface mass density distributions and X-ray emissions emerge only for unrelaxed clusters. The lack of strong correlations with the global environment does not allow us to identify a unique environmental effect originating from the cluster center. In contrast, correla- tions between Hα morphology and local number density emerge. We conclude that local effects, uncorrelated to the cluster-centric radius, play a more important role in shaping galaxy properties.

astro-ph.GA↗

arXiv2017

REEL-BF Design: Achieving the SDP Bound for Downlink Beamforming with Arbitrary Shaping Constraints

This paper considers the beamforming design for a multiuser multiple-input single-output (MISO) downlink with an arbitrary number of (context-specific) shaping constraints. In this setup, the state-of-the-art beamforming schemes cannot attain the well-known performance bound promised by the semidefinite program (SDP) relaxation technique. To close the gap, we propose a redundant-signal embedded linear beamforming (REEL-BF) scheme, where each user is assigned with one information beamformer and several shaping beamformers. It is shown that the proposed REEL-BF scheme can perform general rank-$K$ beamforming for user symbols in a low-complexity and structured manner. In addition, sufficient conditions are derived to guarantee that the REEL-BF scheme always achieves the SDP bound for linear beamforming schemes. Based on such conditions, an efficient algorithm is then developed to obtain the optimal REEL-BF solution in polynomial time. Numerical results demonstrate that the proposed scheme enjoys substantial performance gains over the existing alternatives.

cs.IT↗

arXiv2017

Classification of Neurological Gait Disorders Using Multi-task Feature Learning

As our population ages, neurological impairments and degeneration of the musculoskeletal system yield gait abnormalities, which can significantly reduce quality of life. Gait rehabilitative therapy has been widely adopted to help patients maximize community participation and living independence. To further improve the precision and efficiency of rehabilitative therapy, more objective methods need to be developed based on sensory data. In this paper, an algorithmic framework is proposed to provide classification of gait disorders caused by two common neurological diseases, stroke and Parkinson's Disease (PD), from ground contact force (GCF) data. An advanced machine learning method, multi-task feature learning (MTFL), is used to jointly train classification models of a subject's gait in three classes, post-stroke, PD and healthy gait. Gait parameters related to mobility, balance, strength and rhythm are used as features for the classification. Out of all the features used, the MTFL models capture the more important ones per disease, which will help provide better objective assessment and therapy progress tracking. To evaluate the proposed methodology we use data from a human participant study, which includes five PD patients, three post-stroke patients, and three healthy subjects. Despite the diversity of abnormalities, the evaluation shows that the proposed approach can successfully distinguish post-stroke and PD gait from healthy gait, as well as post-stroke from PD gait, with Area Under the Curve (AUC) score of at least 0.96. Moreover, the methodology helps select important gait features to better understand the key characteristics that distinguish abnormal gaits and design personalized treatment.

cs.CV↗

arXiv2017

Gravitational rotation of polarization: Clarifying the gauge dependence and prediction for double pulsar

From the basic concepts of general relativity, we investigate the rotation of the polarization angle by a moving gravitational lens. Particularly, we clarify the existing confusion in the literature by showing and explaining why such rotation must explicitly depend on the relative motion between the observer and the lens. We update the prediction of such effect on the double pulsar PSR J0737-3039 and estimate a rotation angle of $\sim 10^{-7}rad$. Despite its tiny signal, this is $10$ orders of magnitude larger than the previous prediction by Ruggiero and Tartaglia, which apparently was misguided by the confusion in the literature.

gr-qc↗

arXiv2017

Exact Quantization Conditions, Toric Calabi-Yau and Nonperturbative Topological String

We establish the precise relation between the Nekrasov-Shatashvili (NS) quantization scheme and Grassi-Hatsuda-Marino conjecture for the mirror curve of arbitrary toric Calabi-Yau threefold. For a mirror curve of genus $g$, the NS quantization scheme leads to $g$ quantization conditions for the corresponding integrable system. The exact NS quantization conditions enjoy a self S-duality with respect to Planck constant $\hbar$ and can be derived from the Lockhart-Vafa partition function of nonperturbative topological string. Based on a recent observation on the correspondence between spectral theory and topological string, another quantization scheme was proposed by Grassi-Hatsuda-Marino, in which there is a single quantization condition and the spectra are encoded in the vanishing of a quantum Riemann theta function. We demonstrate that there actually exist at least $g$ nonequivalent quantum Riemann theta functions and the intersections of their theta divisors coincide with the spectra determined by the exact NS quantization conditions. This highly nontrivial coincidence between the two quantization schemes requires infinite constraints among the refined Gopakumar-Vafa invariants. The equivalence for mirror curves of genus one has been verified for some local del Pezzo surfaces. In this paper, we generalize the correspondence to higher genus, and analyze in detail the resolved $\mathbb{C}^3/\mathbb{Z}_5$ orbifold and several $SU(N)$ geometries. We also give a proof for some models at $\hbar=2π/k$.

hep-th↗