Real-time ghost imaging of Bell-nonlocal entanglement between a photon and a quantum memory

Certification of nonlocality of quantum mechanics is an important fundamental test that typically requires prolonged data collection and is only revealed in an in-depth analysis. These features are often particularly exposed in hybrid systems, such as interfaces between light and atomic ensembles. Certification of entanglement from images acquired with single-photon camera can mitigate this issue by exploiting multiplexed photon generation. Here we demonstrate this feature in a quantum memory (QM) operating in a real-time feedback mode. Through spatially-multimode spin-wave storage the QM enables operation of the real-time ghost imaging (GI) protocol. By properly preparing the spatial phase of light emitted by the atoms we enable observation of Bell-type nonlocality from a single image acquired in the far field as witnessed by the Bell parameter of S=2.227±0.007>2. Our results are an important step towards fast and efficient utilization of multimode quantum memories both in protocols and in fundamental tests.

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DECOHERENCE-FREE QUANTUM MEMORY FOR PHOTONIC STATE USING ATOMIC ENSEMBLES

International Journal of Quantum Information ◽

10.1142/s021974990900547x ◽

2009 ◽

Vol 07 (04) ◽

pp. 811-820 ◽

Cited By ~ 2

Author(s):

FENG MEI ◽

YA-FEI YU ◽

ZHI-MING ZHANG

Keyword(s):

Information Processing ◽

Quantum Information ◽

Large Scale ◽

Quantum Information Processing ◽

Single Photon ◽

Quantum Memory ◽

Single Photon Detection ◽

Atomic Ensembles ◽

Optical Elements ◽

Photonic State

Large scale quantum information processing requires stable and long-lived quantum memories. Here, using atom-photon entanglement, we propose an experimentally feasible scheme to realize decoherence-free quantum memory with atomic ensembles, and show one of its applications, remote transfer of unknown quantum state, based on laser manipulation of atomic ensembles, photonic state operation through optical elements, and single-photon detection with moderate efficiency. The scheme, with inherent fault-tolerance to the practical noise and imperfections, allows one to retrieve the information in the memory for further quantum information processing within the reach of current technology.

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Purcell-Enhanced and Indistinguishable Single-Photon Generation from Quantum Dots Coupled to On-Chip Integrated Ring Resonators

Nano Letters ◽

10.1021/acs.nanolett.0c01771 ◽

2020 ◽

Vol 20 (9) ◽

pp. 6357-6363 ◽

Cited By ~ 2

Author(s):

Łukasz Dusanowski ◽

Dominik Köck ◽

Eunso Shin ◽

Soon-Hong Kwon ◽

Christian Schneider ◽

...

Keyword(s):

Quantum Dots ◽

Single Photon ◽

Ring Resonators ◽

On Chip ◽

Photon Generation

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Tailoring the Geometry of Bottom-Up Nanowires: Application to High Efficiency Single Photon Sources

Nanomaterials ◽

10.3390/nano11051201 ◽

2021 ◽

Vol 11 (5) ◽

pp. 1201

Author(s):

Dan Dalacu ◽

Philip J. Poole ◽

Robin L. Williams

Keyword(s):

Quantum Dot ◽

High Efficiency ◽

Emission Rate ◽

Single Photon ◽

Collection Efficiency ◽

Photon Emission ◽

Device Performance ◽

Bottom Up ◽

Selective Area ◽

Photon Generation

For nanowire-based sources of non-classical light, the rate at which photons are generated and the ability to efficiently collect them are determined by the nanowire geometry. Using selective-area vapour-liquid-solid epitaxy, we show how it is possible to control the nanowire geometry and tailor it to optimise device performance. High efficiency single photon generation with negligible multi-photon emission is demonstrated using a quantum dot embedded in a nanowire having a geometry tailored to optimise both collection efficiency and emission rate.

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Real-Time Environment Monitoring Using a Lightweight Image Super-Resolution Network

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18115890 ◽

2021 ◽

Vol 18 (11) ◽

pp. 5890

Author(s):

Qiang Yu ◽

Feiqiang Liu ◽

Long Xiao ◽

Zitao Liu ◽

Xiaomin Yang

Keyword(s):

Deep Learning ◽

Real Time ◽

Super Resolution ◽

Model Complexity ◽

Practical Application ◽

Single Image ◽

Feature Maps ◽

Benchmark Datasets ◽

Image Super Resolution ◽

Single Image Super Resolution

Deep-learning (DL)-based methods are of growing importance in the field of single image super-resolution (SISR). The practical application of these DL-based models is a remaining problem due to the requirement of heavy computation and huge storage resources. The powerful feature maps of hidden layers in convolutional neural networks (CNN) help the model learn useful information. However, there exists redundancy among feature maps, which can be further exploited. To address these issues, this paper proposes a lightweight efficient feature generating network (EFGN) for SISR by constructing the efficient feature generating block (EFGB). Specifically, the EFGB can conduct plain operations on the original features to produce more feature maps with parameters slightly increasing. With the help of these extra feature maps, the network can extract more useful information from low resolution (LR) images to reconstruct the desired high resolution (HR) images. Experiments conducted on the benchmark datasets demonstrate that the proposed EFGN can outperform other deep-learning based methods in most cases and possess relatively lower model complexity. Additionally, the running time measurement indicates the feasibility of real-time monitoring.

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Real-Time Single Image Depth Perception in the Wild with Handheld Devices

Sensors ◽

10.3390/s21010015 ◽

2020 ◽

Vol 21 (1) ◽

pp. 15

Author(s):

Filippo Aleotti ◽

Giulio Zaccaroni ◽

Luca Bartolomei ◽

Matteo Poggi ◽

Fabio Tosi ◽

...

Keyword(s):

Real Time ◽

Depth Perception ◽

Depth Estimation ◽

Autonomous Driving ◽

Estimation Methods ◽

Handheld Devices ◽

Single Image ◽

Handheld Device ◽

Time Performance ◽

In The Wild

Depth perception is paramount for tackling real-world problems, ranging from autonomous driving to consumer applications. For the latter, depth estimation from a single image would represent the most versatile solution since a standard camera is available on almost any handheld device. Nonetheless, two main issues limit the practical deployment of monocular depth estimation methods on such devices: (i) the low reliability when deployed in the wild and (ii) the resources needed to achieve real-time performance, often not compatible with low-power embedded systems. Therefore, in this paper, we deeply investigate all these issues, showing how they are both addressable by adopting appropriate network design and training strategies. Moreover, we also outline how to map the resulting networks on handheld devices to achieve real-time performance. Our thorough evaluation highlights the ability of such fast networks to generalize well to new environments, a crucial feature required to tackle the extremely varied contexts faced in real applications. Indeed, to further support this evidence, we report experimental results concerning real-time, depth-aware augmented reality and image blurring with smartphones in the wild.

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Design of a Real-Time Breakdown Voltage and On-Chip Temperature Monitoring System for Single Photon Avalanche Diodes

Electronics ◽

10.3390/electronics10010025 ◽

2020 ◽

Vol 10 (1) ◽

pp. 25

Author(s):

Shijie Deng ◽

Alan P. Morrison ◽

Yong Guo ◽

Chuanxin Teng ◽

Ming Chen ◽

...

Keyword(s):

Real Time ◽

Breakdown Voltage ◽

Count Rate ◽

Single Photon ◽

Photon Counting ◽

Temperature Monitoring ◽

Dark Count ◽

Chip Temperature ◽

Avalanche Diodes ◽

On Chip

The design and implementation of a real-time breakdown voltage and on-chip temperature monitoring system for single photon avalanche diodes (SPADs) is described in this work. In the system, an on-chip shaded (active area of the detector covered by a metal layer) SPAD is used to provide a dark count rate for the breakdown voltage and temperature calculation. A bias circuit was designed to provide a bias voltage scanning for the shaded SPAD. A microcontroller records the pulses from the anode of the shaded SPAD and calculates its real-time dark count rate. An algorithm was developed for the microcontroller to calculate the SPAD’s breakdown voltage and the on-chip temperature in real time. Experimental results show that the system is capable of measuring the SPAD’s breakdown voltage with a mismatch of less than 1.2%. Results also show that the system can provide real-time on-chip temperature monitoring for the range of −10 to 50 °C with errors of less than 1.7 °C. The system proposed can be used for the real-time SPAD’s breakdown voltage and temperature estimation for dual-SPADs or SPAD arrays chip where identical detectors are fabricated on the same chip and one or more dummy SPADs are shaded. With the breakdown voltage and the on-chip temperature monitoring, intelligent control logic can be developed to optimize the performance of the SPAD-based photon counting system by adjusting the parameters such as excess bias voltage and dead-time. This is particularly useful for SPAD photon counting systems used in complex working environments such as the applications in 3D LIDAR imaging for geodesy, geology, geomorphology, forestry, atmospheric physics and autonomous vehicles.

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On the Performance Comparisons of Native and Clientless Real-Time Screen-Sharing Technologies

ACM Transactions on Multimedia Computing Communications and Applications ◽

10.1145/3437881 ◽

2021 ◽

Vol 17 (2) ◽

pp. 1-26

Author(s):

Chun-ying Huang ◽

Yun-chen Cheng ◽

Guan-zhang Huang ◽

Ching-ling Fan ◽

Cheng-hsin Hsu

Keyword(s):

Real Time ◽

Computer Games ◽

Performance Metrics ◽

Video Quality ◽

Dynamic Network ◽

Web Browsers ◽

Depth Analysis ◽

Measurement Methodology ◽

Overall Performance ◽

Screen Sharing

Real-time screen-sharing provides users with ubiquitous access to remote applications, such as computer games, movie players, and desktop applications (apps), anywhere and anytime. In this article, we study the performance of different screen-sharing technologies, which can be classified into native and clientless ones. The native ones dictate that users install special-purpose software, while the clientless ones directly run in web browsers. In particular, we conduct extensive experiments in three steps. First, we identify a suite of the most representative native and clientless screen-sharing technologies. Second, we propose a systematic measurement methodology for comparing screen-sharing technologies under diverse and dynamic network conditions using different performance metrics. Last, we conduct extensive experiments and perform in-depth analysis to quantify the performance gap between clientless and native screen-sharing technologies. We found that our WebRTC-based implementation achieves the best overall performance. More precisely, it consumes a maximum of 3 Mbps bandwidth while reaching a high decoding ratio and delivering good video quality. Moreover, it leads to a steadily high decoding ratio and video quality under dynamic network conditions. By presenting the very first rigorous comparisons of the native and clientless screen-sharing technologies, this article will stimulate more exciting studies on the emerging clientless screen-sharing technologies.

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