arXiv subjects

Qiang Zhou

Publications and source records attributed to Qiang Zhou.

At least 127 records · Page 7Linked to original sources

arXiv2020

Effect of dispersion on indistinguishability between single-photon wave-packets

With propagating through a dispersive medium, the temporal-spectral profile of laser pulses should be inevitably modified. Although such dispersion effect has been well studied in classical optics, its effect on a single-photon wave-packet, i.e., the matter wave of a single-photon, has not yet been entirely revealed. In this paper, we investigate the effect of dispersion on indistinguishability of single-photon wave-packets through the Hong-Ou-Mandel (HOM) interference. By dispersively manipulating two indistinguishable single-photon wave-packets before interfering with each other, we observe that the difference of the second-order dispersion between two optical paths of the HOM interferometer can be mapped to the interference curve, indicating that (1) with the same amount of dispersion effect in both paths, the HOM interference curve must be only determined by the intrinsic indistinguishability between the wave-packets, i.e., dispersion cancellation due to the indistinguishability between Feynman paths; (2) unbalanced dispersion effect in two paths cannot be cancelled and will broaden the interference curve thus providing a way to measure the second-order dispersion coefficient. Our results suggest a more comprehensive understanding of the single-photon wave-packet and pave ways to explore further applications of the HOM interference.

quant-ph↗

arXiv2020

A Tree-structure Convolutional Neural Network for Temporal Features Exaction on Sensor-based Multi-resident Activity Recognition

With the propagation of sensor devices applied in smart home, activity recognition has ignited huge interest and most existing works assume that there is only one habitant. While in reality, there are generally multiple residents at home, which brings greater challenge to recognize activities. In addition, many conventional approaches rely on manual time series data segmentation ignoring the inherent characteristics of events and their heuristic hand-crafted feature generation algorithms are difficult to exploit distinctive features to accurately classify different activities. To address these issues, we propose an end-to-end Tree-Structure Convolutional neural network based framework for Multi-Resident Activity Recognition (TSC-MRAR). First, we treat each sample as an event and obtain the current event embedding through the previous sensor readings in the sliding window without splitting the time series data. Then, in order to automatically generate the temporal features, a tree-structure network is designed to derive the temporal dependence of nearby readings. The extracted features are fed into the fully connected layer, which can jointly learn the residents labels and the activity labels simultaneously. Finally, experiments on CASAS datasets demonstrate the high performance in multi-resident activity recognition of our model compared to state-of-the-art techniques.

cs.CV↗

arXiv2020

Bright Optical Eigenmode with about 1 nm $^3$ Volume

Concentrating optical field in an eigenmode with a tiny volume is vitally important for light-matter interactions at the fundamental level and underpins new technologies. In the past decades, researchers have investigated various approaches to shrink light and so far managed to reduce the volume of optical eigenmodes, under the quantum-optical definition, down to several ten nm3. Here we report on the discovery, characterization and engineering of a class of extremely localized eigenmodes that are resonances of atomistic protrusions on a metallic host nanoparticle and feature quantum-optical mode volumes of below 1 nm3. We theoretically demonstrate that these extremely localized modes can be made bright with radiation efficiencies reaching 30% and provide up to 4x10^7 times intensity enhancement. The existence of bright eigenmodes with the volume comparable to a photon emitter foresees exciting new optical physics, such as ultrastrong coupling with single optical emitters, angstrom-resolution optical imaging, and atomic-scale single-molecule photochemistry.

physics.optics↗

arXiv2020

Exploiting Interpretable Patterns for Flow Prediction in Dockless Bike Sharing Systems

Unlike the traditional dock-based systems, dockless bike-sharing systems are more convenient for users in terms of flexibility. However, the flexibility of these dockless systems comes at the cost of management and operation complexity. Indeed, the imbalanced and dynamic use of bikes leads to mandatory rebalancing operations, which impose a critical need for effective bike traffic flow prediction. While efforts have been made in developing traffic flow prediction models, existing approaches lack interpretability, and thus have limited value in practical deployment. To this end, we propose an Interpretable Bike Flow Prediction (IBFP) framework, which can provide effective bike flow prediction with interpretable traffic patterns. Specifically, by dividing the urban area into regions according to flow density, we first model the spatio-temporal bike flows between regions with graph regularized sparse representation, where graph Laplacian is used as a smooth operator to preserve the commonalities of the periodic data structure. Then, we extract traffic patterns from bike flows using subspace clustering with sparse representation to construct interpretable base matrices. Moreover, the bike flows can be predicted with the interpretable base matrices and learned parameters. Finally, experimental results on real-world data show the advantages of the IBFP method for flow prediction in dockless bike sharing systems. In addition, the interpretability of our flow pattern exploitation is further illustrated through a case study where IBFP provides valuable insights into bike flow analysis.

cs.LG↗

arXiv2020

Continuous-variable pairwise entanglement based on optoelectromechanical system

Inspired by the discrete-variable pairwise entanglement, in this work, we in theory analyze the continuous-variable pairwise entanglement between microwave modes based on a hybrid optoelectromechanical system, where the multi-pair microwave superconducting circuits simutaneously interact with each other via a mechanical resonator, which forms a Fabry-Pérot cavity along with a standing mirror. With experimentally reachable parameter settings, wanted entanglement can be acheived when the pair number up to 10, and more is also available, which has the potential to be useful in quantum technologies where the demand for scalability and intergration is continuously increasing.

quant-ph↗

arXiv2020

TransMoMo: Invariance-Driven Unsupervised Video Motion Retargeting

We present a lightweight video motion retargeting approach TransMoMo that is capable of transferring motion of a person in a source video realistically to another video of a target person. Without using any paired data for supervision, the proposed method can be trained in an unsupervised manner by exploiting invariance properties of three orthogonal factors of variation including motion, structure, and view-angle. Specifically, with loss functions carefully derived based on invariance, we train an auto-encoder to disentangle the latent representations of such factors given the source and target video clips. This allows us to selectively transfer motion extracted from the source video seamlessly to the target video in spite of structural and view-angle disparities between the source and the target. The relaxed assumption of paired data allows our method to be trained on a vast amount of videos needless of manual annotation of source-target pairing, leading to improved robustness against large structural variations and extreme motion in videos. We demonstrate the effectiveness of our method over the state-of-the-art methods. Code, model and data are publicly available on our project page (https://yzhq97.github.io/transmomo).

cs.CV↗

arXiv2020

Quantum random number generator based on room-temperature single-photon emitter in gallium nitride

We experimentally demonstrate a real-time quantum random number generator by using a room-temperature single-photon emitter from the defect in a commercial gallium nitride wafer. Thanks to the brightness of our single photon emitter, the raw bit generation rate is ~1.8 MHz, and the unbiased bit generation rate is ~420 kHz after von Neumann's randomness extraction procedure. Our results show that commercial gallium nitride wafer has great potential for the development of integrated high-speed quantum random number generator devices.

quant-ph↗

arXiv2020

Visual Data Analysis and Simulation Prediction for COVID-19

The COVID-19 (formerly, 2019-nCoV) epidemic has become a global health emergency, as such, WHO declared PHEIC. China has taken the most hit since the outbreak of the virus, which could be dated as far back as late November by some experts. It was not until January 23rd that the Wuhan government finally recognized the severity of the epidemic and took a drastic measure to curtain the virus spread by closing down all transportation connecting the outside world. In this study, we seek to answer a few questions: How did the virus get spread from the epicenter Wuhan city to the rest of the country? To what extent did the measures, such as, city closure and community quarantine, help controlling the situation? More importantly, can we forecast any significant future development of the event had some of the conditions changed? By collecting and visualizing publicly available data, we first show patterns and characteristics of the epidemic development; we then employ a mathematical model of disease transmission dynamics to evaluate the effectiveness of some epidemic control measures, and more importantly, to offer a few tips on preventive measures.

physics.med-ph↗

arXiv2019

Spectrally uncorrelated biphotons generated from `the family of BBO crystal'

Spectrally intrinsically uncorrelated biphoton states generated from nonlinear crystals are very important but rare resources for quantum photonics and quantum information applications. Previously, such biphoton states were generated from several kinds of crystals, however, their wavelength ranges and nonlinear efficiencies were still limited for various applications. In order to explore new crystal for wider wavelength range and higher nonlinear efficiency, here we theoretically study the generation of spectrally uncorrelated biphoton states from 14 crystals in the `BBO family', including BBO, CLBO, KABO, KBBF, RBBF, CBBF, BABF, BiBO, LBO, CBO, LRB4, LCB, YCOB, and GdCOB. They satisfy three kinds of group-velocity matching condition from near-infrared to telecom wavelengths. Furthermore, heralded single photons can be generated with a purity as high as 0.98, which is achieved without any narrow filtering. The indistinguishability of photons from independent sources is examined by the Hong-Ou-Mandel interference, which results in a visibility of 98% also without any further filtering, i.e., photons from different heralded single-photon sources are highly indistinguishable. Our study may provide single-photon sources with good performance for quantum information processing at near-infrared and telecom wavelengths.

quant-ph↗

arXiv2019

Entangling two microwave modes via optomechanics

We in theory proposed a hybrid system consisting of a mechanical resonator, an optical Fabry-Pérot cavity, and two superconducting microwave circuits to generate stationary continuous-variable quantum entanglement between two microwave modes. We show that the hybrid system can also achieve quantum entanglement of other bipartite subsystems in experimentally accessible parameter regimes, which has the potential to be useful in quantum information processing and quantum illumination radar.

quant-ph↗

arXiv2019

Dispersion independent long-haul photon counting OTDR

Photon counting optical time-domain reflectometry (PC-OTDR) based on the single photon detection is an effective scheme to attain the high spatial resolution for optical fiber fault monitoring. Currently, due to the spatial resolution of PC-OTDR is proportional to the pulse width of a laser beam, short laser pulses are essential for the high spatial resolution. However, short laser pulses have a large bandwidth, which would be widened by the dispersion of fiber, thereby causing inevitable deterioration in spatial resolution, especially for long-haul fiber links. In this letter, we propose a scheme of dispersion independent PC-OTDR based on an infinite backscatter technique. Our experimental results -with more than 50 km long fiber - show that the spatial resolution of the PC-OTDR system is independent with the total dispersion of the fiber under test. Our method provides an avenue for developing the long-haul PC-OTDR with high performance.

quant-ph↗

arXiv2019

FAB: A Robust Facial Landmark Detection Framework for Motion-Blurred Videos

Recently, facial landmark detection algorithms have achieved remarkable performance on static images. However, these algorithms are neither accurate nor stable in motion-blurred videos. The missing of structure information makes it difficult for state-of-the-art facial landmark detection algorithms to yield good results. In this paper, we propose a framework named FAB that takes advantage of structure consistency in the temporal dimension for facial landmark detection in motion-blurred videos. A structure predictor is proposed to predict the missing face structural information temporally, which serves as a geometry prior. This allows our framework to work as a virtuous circle. On one hand, the geometry prior helps our structure-aware deblurring network generates high quality deblurred images which lead to better landmark detection results. On the other hand, better landmark detection results help structure predictor generate better geometry prior for the next frame. Moreover, it is a flexible video-based framework that can incorporate any static image-based methods to provide a performance boost on video datasets. Extensive experiments on Blurred-300VW, the proposed Real-world Motion Blur (RWMB) datasets and 300VW demonstrate the superior performance to the state-of-the-art methods. Datasets and models will be publicly available at https://keqiangsun.github.io/projects/FAB/FAB.html.

cs.CV↗

arXiv2019

Entanglement between light and microwave via electro-optic effect

We theoretically proposed one of the approaches achieving the quantum entanglement between light and microwave by means of electro-optic effect. Based on the established full quantum model of electro-optic interaction, the entanglement characteristics between light and microwave are studied by using the logarithmic negativity as a measure of the steady-state equilibrium operating point of the system. The investigation shows that the entanglement between light and microwave is a complicated function of multiple physical parameters, the parameters such as ambient temperature, optical detuning, microwave detuning and coupling coefficient have an important influence on the entanglement. When the system operates at narrow pulse widths and/or low repetition frequencies, it has obvious entanglement about 20 K, which is robust to the thermal environment.

quant-ph↗

arXiv2019

High Dynamic Range Externally Time-gated Photon Counting Optical Time-domain Reflectometry

Single photon detector (SPD) has a maximum count rate due to its dead time, which results in that the dynamic range of photon counting optical time-domain reflectometry (PC-OTDR) de-creases with the length of monitored fiber. To further improve the dynamic range of PC-OTDR, we propose and demonstrate an externally time-gated scheme. The externally time-gated scheme is realized by using a high-speed optical switch, i.e. a Mach-Zehnder interferometer, to modulate the back-propagation optical signal, and to allow that only a certain segment of the fiber is monitored by the SPD. The feasibility of proposed scheme is first examined with theoretical analysis and simulation; then we experimentally demonstrate it with our experimental PC-OTDR testbed operating at 800 nm wavelength band. In our studies, a dynamic range of 30.0 dB is achieved in a 70 meters long PC-OTDR system with 50 ns external gates, corresponding to an improvement of 11.0 dB in dynamic range comparing with no gating operation. Furthermore, with the improved dynamic range, a successful identification of a 0.37 dB loss event is detected with 30-seconds accumulation, which could not be identified without gating operation. Our scheme paves an avenue for developing PC-OTDR systems with high dynamic range.

physics.ins-det↗

arXiv2019

Proposal, Tracking and Segmentation (PTS): A Cascaded Network for Video Object Segmentation

Video object segmentation (VOS) aims at pixel-level object tracking given only the annotations in the first frame. Due to the large visual variations of objects in video and the lack of training samples, it remains a difficult task despite the upsurging development of deep learning. Toward solving the VOS problem, we bring in several new insights by the proposed unified framework consisting of object proposal, tracking and segmentation components. The object proposal network transfers objectness information as generic knowledge into VOS; the tracking network identifies the target object from the proposals; and the segmentation network is performed based on the tracking results with a novel dynamic-reference based model adaptation scheme. Extensive experiments have been conducted on the DAVIS'17 dataset and the YouTube-VOS dataset, our method achieves the state-of-the-art performance on several video object segmentation benchmarks. We make the code publicly available at https://github.com/sydney0zq/PTSNet.

cs.CV↗

arXiv2019

Classical analogy of a cat state using vortex light

Cat states are systems in a superposition of macroscopically distinguishable states; this superposition can be of either classically or quantum distinct state, regardless of the number of particles or modes involved. Here, we constructed an experimental model that simulates an optical cat state by engineering the classical orbital angular momentum of light, referred to here as an analogous cat state (a-CS). In our scheme, the behaviors of the a-CS in position space show many similarities to the quantum version of the optical cat state in phase space, for example, movement, rotation, and interference. Experimentally, the a-CS, which has two spatially localized Gaussian intensity lobes, can be evolved from "kitten" to "cat" by engineering the acquired phase hologram. Additionally, we simulated the "decoherence" of the a-CS influenced by atmospheric turbulence. The a-CS provides a reliable tool for visualizing and studying the behaviors of quantum cat states in phase space.

quant-ph↗

arXiv2019

Multiplexing heralded single-photon in orbital angular momentum space

Heralded single-photon source (HSPS) with competitive single photon purity and indistinguishability has become an essential resource for photonic quantum information processing. Here, for the first time, we proposed a theoretical regime to enhance heralded single-photons generation by multiplexing the degree of the freedom of orbital angular momentum (OAM) of down-converted entangled photon pairs emitted from a nonlinear crystal. Experimentally, a proof-of-principle experiment has been performed through multiplexing three OAM modes. We achieve a 47$\%$ enhancement in single photon rate. A second-order autocorrelation function $g^{(2)}(0)<0.5$ ensures our multiplexed heralded single photons with good single photon purity. We further indicate that an OAM-multiplexed HSPS with high quality can be constructed by generating higher dimensional entangled state and sorting them with high efficiency in OAM space. Our avenue may approach a good HSPS with the deterministic property.

quant-ph↗

arXiv2019

STN-Homography: estimate homography parameters directly

In this paper, we introduce the STN-Homography model to directly estimate the homography matrix between image pair. Different most CNN-based homography estimation methods which use an alternative 4-point homography parameterization, we use prove that, after coordinate normalization, the variance of elements of coordinate normalized $3\times3$ homography matrix is very small and suitable to be regressed well with CNN. Based on proposed STN-Homography, we use a hierarchical architecture which stacks several STN-Homography models and successively reduce the estimation error. Effectiveness of the proposed method is shown through experiments on MSCOCO dataset, in which it significantly outperforms the state-of-the-art. The average processing time of our hierarchical STN-Homography with 1 stage is only 4.87 ms on the GPU, and the processing time for hierarchical STN-Homography with 3 stages is 17.85 ms. The code will soon be open sourced.

cs.CV↗