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We theoretically investigate the problem of position detection of an optically levitated Mie particle. The information radiation field (IRF) is proposed and defined to characterize the scattered light carrying complete information about the center-of-mass (c.m.) motion of the particle. Based on the IRF, we suggest an optimal detection scheme for the position of arbitrary particles. We calculate both the information losses of objective collection and mode-matching in levitated optomechanical experiments. Our results conclude that the backward detection scheme, using an incident Gaussian beam focused by a high numerical aperture lens, provides sufficient information to achieve the quantum ground state through cooling of the three-dimensional c.m. motion of the Mie particle.

Simultaneous wireless information and power transfer (SWIPT) leverages lightwave as the wireless transmission medium, emerging as a promising technology in the future Internet of Things (IoT) scenarios. The use of retro-reflectors in constructing spatially separated laser resonators (SSLR) enables a self-aligning wireless transmission system with the self-reproducing resonant beam, i.e. resonant beam system (RBS). However, it's effective Field of View (FoV) is physically limited by the size of retroreflectors and still requires significant improvement. This restricts the transmitter from providing seamless wireless connectivity and power supply to receivers within a large dynamic movement range. In this paper, we propose an FoV-enlarged resonant beam system operating at a meter distance by incorporating a telescope. The telescope plays a crucial role in minimizing the extra loss inflicted on the gain medium, which typically arises from the deviation of the resonant beam within the cavity. Further, we construct the proposed telescope-based RBS and experimentally demonstrate that the design could expand the FoV to 28$^\circ$ over 1 m transmission distance is about triple that of the ordinary RBS design.

The rapid advancement of the next generation of communications and internet of things (IoT) technologies has made the provision of location-based services for diverse devices an increasingly pressing necessity. Localizing devices with/without intelligent computing abilities, including both active and passive devices is essential, especially in indoor scenarios. For traditional RF positioning systems, aligning transmission signals and dealing with signal interference in complex environments are inevitable challenges. Therefore, this paper proposed a new passive positioning system, the RF-band resonant beam positioning system (RF-RBPS), which achieves energy concentration and beam alignment by amplifying echoes between the base station (BS) and the passive target (PT), without the need for complex channel estimation and time-consuming beamforming and provides high-precision direction of arrival (DoA) estimation for battery-free targets using the resonant mechanism. The direction information of the PT is estimated using the multiple signal classification (MUSIC) algorithm at the end of BS. The feasibility of the proposed system is validated through theoretical analysis and simulations. Results indicate that the proposed RF-RBPS surpasses RF-band active positioning system (RF-APS) in precision, achieving millimeter-level precision at 2m within an elevation angle of 35$^\circ$, and an error of less than 3cm at 2.5m within an elevation angle of 35$^\circ$.

To meet the growing demand for data traffic, spectrum-rich optical wireless communication (OWC) has emerged as a key technological driver for the development of 6G. The resonant beam communication (RBC) system, which employs spatially separated laser cavities as the transmitter and receiver, is a high-speed OWC technology capable of self-alignment without tracking. However, its transmission through the air is susceptible to losses caused by obstructions. In this paper, we propose an intelligent reflecting surface (IRS) assisted RBC system with the optical frequency doubling method, where the resonant beam in frequency-fundamental and frequency-doubled is transmitted through both direct line-of-sight (LoS) and IRS-assisted channels to maintain steady-state oscillation and enable communication without echo-interference, respectively. Then, we establish the channel model based on Fresnel diffraction theory under the near-field optical propagation to analyze the transmission loss and frequency-doubled power analytically. Furthermore, communication power can be maximized by dynamically controlling the beam-splitting ratio between the two channels according to the loss levels encountered over air. Numerical results validate that the IRS-assisted channel can compensate for the losses in the obstructed LoS channel and misaligned receivers, ensuring that communication performance reaches an optimal value with dynamic ratio adjustments.

Optical frequency combs (OFCs), composed of equally spaced frequency tones, have spurred advancements in communications, spectroscopy, precision measurement and fundamental physics research. A prevalent method for generating OFCs involves the electro-optic (EO) effect, i.e., EO comb, renowned for its rapid tunability via precise microwave field control. Recent advances in integrated lithium niobate (LN) photonics have greatly enhanced the efficiency of EO effect, enabling the generation of broadband combs with reduced microwave power. However, parasitic nonlinear effects, such as Raman scattering and four-wave mixing, often emerge in high quality nonlinear devices, impeding the expansion of comb bandwidth and the minimization of frequency noise. Here, we tame these nonlinear effects and present a novel type of OFC, i.e., the self-locked Raman-electro-optic (REO) microcomb by leveraging the collaboration of EO, Kerr and Raman scattering processes. The spectral width of the REO microcomb benefits from the Raman gain and Kerr effect, encompassing nearly 1400 comb lines spanning over 300 nm with a fine repetition rate of 26.03 GHz, much larger than the pure EO combs. Remarkably, the system can maintain a self-locked low-noise state in the presence of multiple nonlinearities without the need for external active feedback. Our approach points to a direction for improving the performance of microcombs and paves the way for exploring new nonlinear physics, such as new laser locking techniques, through the collaboration of inevitable multiple nonlinear effects in integrated photonics.

Accurate measurement of pressure with a wide dynamic range holds significant importance for various applications. This issue can be realized with a mechanical nano-oscillator, where the pressure-related collisions with surrounding molecules induce its energy dissipation. However, this energy dissipation of the nano-oscillator may be overshadowed by other processes. Here, we apply the second-order coherence analysis to accurately characterize those distinct dissipation processes. Based on an optically levitated nano-oscillator, we successfully obtain precise measurements of the air pressure surrounding the particles from atmosphere to 7E-6 mbar, over 8 orders of magnitude. It proves that the mechanical nano-oscillator is an extremely promising candidate for precision pressure sensing applications. Moreover, the second-order coherence analysis method on a classical system can pave the way to characterize the dynamic properties of an oscillator, which will benefit microscopic thermodynamics, precision measurement, and macroscopic quantum research., Comment: 6 pages. 4 figures

Reconfigurable intelligent surface (RIS)-assisted index modulation system schemes are considered a promising technology for sixth-generation (6G) wireless communication systems, which can enhance various system capabilities such as coverage and reliability. However, obtaining perfect channel state information (CSI) is challenging due to the lack of a radio frequency chain in RIS. In this paper, we investigate the RIS-assisted full-duplex (FD) two-way space shift keying (SSK) system under imperfect CSI, where the signal emissions are augmented by deploying RISs in the vicinity of two FD users. The maximum likelihood detector is utilized to recover the transmit antenna index. With this in mind, we derive closed-form average bit error probability (ABEP) expression based on the Gaussian-Chebyshev quadrature (GCQ) method and provide the upper bound and asymptotic ABEP expressions in the presence of channel estimation errors. To gain more insights, we also derive the outage probability and provide the throughput of the proposed scheme with imperfect CSI. The correctness of the analytical derivation results is confirmed via Monte Carlo simulations. It is demonstrated that increasing the number of elements of RIS can significantly improve the ABEP performance of the FD system over the half-duplex (HD) system. Furthermore, in the high SNR region, the ABEP performance of the FD system is better than that of the HD system.

Symmetric informationally complete measurements are both important building blocks in many quantum information protocols and the seminal example of a generalised, non-orthogonal, quantum measurement. In higher-dimensional systems, these measurements become both increasingly interesting and increasingly complex to implement. Here, we demonstrate an integrated quantum photonic platform to realize such a measurement on three-level quantum systems. The device operates at the high fidelities necessary for verifying a genuine many-outcome quantum measurement, performing near-optimal quantum state discrimination, and beating the projective limit in quantum random number generation. Moreover, it is programmable and can readily implement other quantum measurements at similarly high quality. Our work paves the way for the implementation of sophisticated higher-dimensional quantum measurements that go beyond the traditional orthogonal projections., Comment: 21 pages,13 figures

The use of nanophotonics for optical manipulation has continuously attracted interest in both fundamental research and practical applications, due to its significantly enhanced capabilities at the nanoscale. In this work, we showed that plasmonic particles can be trapped at off-axis location in Gaussian beams assisted by surface plasmon resonance. The off-axis displacement can be tuned at the sub-wavelength scale by the incident light beams. Based on these, we propose that a superfast orbital rotation of particles in continuous-wave laser beam can be realized in tightly focused circularly polarized Gaussian beams. The rotation has a tunable orbital radius at the sub-wavelength scale and a superfast rotation speed (more than 10^4 r/s in water under common laboratory conditions). Our work will aid in the development of optically driven nanomachines, and find applications in micro/nano-rheology, micro-fluid mechanics, and biological research at the nanoscale., Comment: 5 pages, 5 figures

Free space optical (FSO) transmission has emerged as a key candidate technology for 6G to expand new spectrum and improve network capacity due to its advantages of large bandwidth, low electromagnetic interference, and high energy efficiency. Resonant beam operating in the infrared band utilizes spatially separated laser cavities to enable safe and mobile high-power energy and high-rate information transmission but is limited by line-of-sight (LOS) channel. In this paper, we propose a reconfigurable intelligent surface (RIS) assisted resonant beam simultaneous wireless information and power transfer (SWIPT) system and establish an optical field propagation model to analyze the channel state information (CSI), in which LOS obstruction can be detected sensitively and non-line-of-sight (NLOS) transmission can be realized by changing the phased of resonant beam in RIS. Numerical results demonstrate that, apart from the transmission distance, the NLOS performance depends on both the horizontal and vertical positions of RIS. The maximum NLOS energy efficiency can achieve 55% within a transfer distance of 10m, a translation distance of $\pm$4mm, and rotation angle of $\pm$50{\deg}.

Hyperspectral imaging provides optical information with high-dimensional spatial-temporal-spectral data cubes revealing intrinsic matter characteristics. It has been widely applied in various intelligent inspection applications. The existing hyperspectral imaging systems employ individual optical prism or grating to separate different spectra, which require complicated optical design that takes a heavy load for integration. The emerging multispectral imaging sensor integrates narrow-band filters on each pixel element, wasting most light throughput and trapped in the rigorous tradeoff between spatial and spectral resolution. In this work, we report an on-chip computational hyperspectral imaging framework with full spatial and temporal resolution. By integrating different broadband filtering materials on the imaging sensor, the target spectral information is non-uniformly and intrinsically coupled on each pixel with high light throughput. Using intelligent reconstruction algorithms, multi-channel images can be recovered from each frame, realizing real-time hyperspectral imaging. Following such a framework, we for the first time fabricated a broadband (400-1700 nm) hyperspectral imaging sensor with an average light throughput of 71.8$\%$ (enabling 32.5 dB peak signal-to-noise ratio of spectral reconstruction on ColorChecker Classic chart) and 89 wavelength channels (10 nm interval within 400-1000 nm and 25 nm interval within 1000-1700 nm). The average spectral resolution achieves 2.65 nm at 400-1000 nm and 8.59 nm at 1000-1700 nm. The demonstrated spatial resolution is 2048x2048 pixels at 47 fps, with $\sim$3.43 arc minute resolving ability at a 39-degree field of view. We employed the prototype sensor to collect a large-scale hyperspectral image dataset (210 scenes over 8 categories), and demonstrated the sensor's wide application potentials on a series of experiments ...

Optical microscopy image plays an important role in scientific research through the direct visualization of the nanoworld, where the imaging mechanism is described as the convolution of the point spread function (PSF) and emitters. Based on a priori knowledge of the PSF or equivalent PSF, it is possible to achieve more precise exploration of the nanoworld. However, it is an outstanding challenge to directly extract the PSF from microscopy images. Here, with the help of self-supervised learning, we propose a physics-informed masked autoencoder (PiMAE) that enables a learnable estimation of the PSF and emitters directly from the raw microscopy images. We demonstrate our method in synthetic data and real-world experiments with significant accuracy and noise robustness. PiMAE outperforms DeepSTORM and the Richardson-Lucy algorithm in synthetic data tasks with an average improvement of 19.6\% and 50.7\% (35 tasks), respectively, as measured by the normalized root mean square error (NRMSE) metric. This is achieved without prior knowledge of the PSF, in contrast to the supervised approach used by DeepSTORM and the known PSF assumption in the Richardson-Lucy algorithm. Our method, PiMAE, provides a feasible scheme for achieving the hidden imaging mechanism in optical microscopy and has the potential to learn hidden mechanisms in many more systems.

Non-equilibrium thermodynamics provides a general framework for understanding non-equilibrium processes, particularly in small systems that are typically far from equilibrium and dominated by fluctuations. However, the experimental investigation of non-equilibrium thermodynamics remains challenging due to the lack of approaches to precisely manipulate non-equilibrium states and dynamics. Here, by shaping the effective potential of energy, we propose a general method to construct a non-equilibrium steady state (NESS) with arbitrary energy distribution. Using a well-designed energy-dependent feedback damping, the dynamics of an optically levitated nanoparticle in vacuum is manipulated and driven into a NESS with the desired energy distribution. Based on this approach, a phonon laser state is constructed with an ultra-narrow linewidth of 6.40 uHz. Such an arbitrary NESS construction method provides a new approach to manipulating the dynamics processes of micromechanical systems and paves the way for the systematic study of non-equilibrium dynamics in interdisciplinary research fields.

The accurate radio frequency (RF) ranging and localizing of objects has benefited the researches including autonomous driving, the Internet of Things, and manufacturing. Quantum receivers have been proposed to detect the radio signal with ability that can outperform conventional measurement. As one of the most promising candidates, solid spin shows superior robustness, high spatial resolution and miniaturization. However, challenges arise from the moderate response to a high frequency RF signal. Here, by exploiting the coherent interaction between quantum sensor and RF field, we demonstrate quantum enhanced radio detection and ranging. The RF magnetic sensitivity is improved by three orders to 21 $pT/\sqrt{Hz}$, based on nanoscale quantum sensing and RF focusing. Further enhancing the response of spins to the target's position through multi-photon excitation, a ranging accuracy of 16 $\mu m$ is realized with a GHz RF signal. The results pave the way for exploring quantum enhanced radar and communications with solid spins.

Locating mobile devices precisely in indoor scenarios is a challenging task because of the signal diffraction and reflection in complicated environments. One vital cause deteriorating the localization performance is the inevitable power dissipation along the propagation path of localization signals. In this paper, we propose a high-accuracy localization scheme based on the resonant beam system (RBS) and the binocular vision, i.e., binocular based resonant beam localization (BRBL). The BRBL system utilizes the energy-concentrated and self-aligned transmission of RBS to realize high-efficiency signal propagation and self-positioning for the target. The binocular method is combined with RBS to obtain the three-dimensional (3-D) coordinates of the target for the first time. To exhibit the localization mechanism, we first elaborate on the binocular localization model, including the resonant beam transmission analysis and the geometric derivation of the binocular method with RBS. Then, we establish the power model of RBS, and the signal and noise models of beam spot imaging, respectively, to analyse the performance of the BRBL system. Finally, the numerical results show an outstanding performance of centimeter level accuracy (i.e., $<5\mathrm{cm}$ in $0.4\mathrm{m}$ width and $0.4\mathrm{m}$ length effective range at $1\mathrm{m}$ vertical distance, $<13\mathrm{cm}$ in $0.6\mathrm{m}$ width and $0.6\mathrm{m}$ length effective range at $2\mathrm{m}$ vertical distance), which applies to indoor scenarios.

LHCb Collaboration studied the resonant structure of $B_s\to \overline{D}^0K^-\pi^+$ decays using the Dalitz plot analysis technique, based on a data sample corresponding to an integrated luminosity of $3.0{\rm fb}^{-1}$ of $pp$ collision. The $K^-\pi^+$ components have been analyzed in the amplitude model, where the decay amplitude is modeled to be the resonant contributions with respect to the intermediate resonances $K^*(892)$, $K_0^*(1430)$ and $K_2^*(1430)$. Motivated by the experimental results, we investigate the color-favored quasi-two-body $B \to \overline{D}^0K\pi$ decays in the framework of the perturbative QCD (PQCD) approach. We calculate the the branching fractions by introducing the appropriate wave functions of $K\pi$ pair. Our results are in agreement well the available data, and others can be tested in LHCb and Belle-II experiments. Using the narrow-width-approximation, we also extract the branching fractions of the corresponding two-body $B\to \overline D R$ decays, which agree to the previous theoretical calculations and the experimental data within the errors. There are no $CP$ asymmetries in these decays in the standard model, because these decays are all governed by only the tree operators., Comment: 18 pages, 1 figures

To satisfy the long-range and energy self-sustaining communication needs of electronic devices in the Internet of Things (IoT), we introduce a simultaneous wireless information and power transfer (SWIPT) system using the resonant beam that incorporates a telescope modulator inside a cavity for suppressing diffraction losses. We theoretically analyze power transfer in the resonant beam system with telescope internal modulator (TIM-RBS) considering the electromagnetic field propagation, the end-to-end (E2E) power transfer, and power and information reception. The numerical evaluation demonstrates that the TIM can effectively compress the beam spot, which allows the TIM-RBS to transmit energy twice as far as the RBS without TIM at higher power. Additionally, the largest transmission distance and maximum output power are proportional to the input power, and about 34m transmission distance, 4W electric power, and 12bps/Hz spectral efficiency can be achieved in the TIM-RBS with 200W input power. Hence, TIM-RBS can be considered as a promising option for realizing long-range, high-power, and high-rate SWIPT.

We seek the best stroke sequences of a finite-size swimming predator chasing a non-motile point or finite--size prey at low Reynolds number. We use optimal control to seek the globally-optimal solutions for the former and RL for general situations. The predator is represented by a squirmer model that can translate forward and laterally, rotate and generate a stresslet flow. We identify the predator's best squirming sequences to achieve the time-optimal (TO) and efficiency-optimal (EO) predation. For a point prey, the TO squirmer executing translational motions favours a two-fold L-shaped trajectory that enables it to exploit the disturbance flow for accelerated predation; using a stresslet mode significantly expedites the EO predation, allowing the predator to catch the prey faster yet with lower energy consumption and higher predatory efficiency; the predator can harness its stresslet disturbance flow to suck the prey towards itself; compared to a translating predator, its compeer combining translation and rotation is less time--efficient, and the latter occasionally achieves the TO predation via retreating in order to advance. We also adopt RL to reproduce the globally-optimal predatory strategy of chasing a point prey, qualitatively capturing the crucial two--fold attribute of TO path. Using a numerically emulated RL environment, we explore the dependence of the optimal predatory path on the size of prey. Our results might provide useful information that help design synthetic microswimmers such as \textit{in vivo} medical micro-robots capable of capturing and approaching objects in viscous flows.

To prevent the spread of coronavirus disease 2019 (COVID-19), preliminary temperature measurement and mask detection in public areas are conducted. However, the existing temperature measurement methods face the problems of safety and deployment. In this paper, to realize safe and accurate temperature measurement even when a person's face is partially obscured, we propose a cloud-edge-terminal collaborative system with a lightweight infrared temperature measurement model. A binocular camera with an RGB lens and a thermal lens is utilized to simultaneously capture image pairs. Then, a mobile detection model based on a multi-task cascaded convolutional network (MTCNN) is proposed to realize face alignment and mask detection on the RGB images. For accurate temperature measurement, we transform the facial landmarks on the RGB images to the thermal images by an affine transformation and select a more accurate temperature measurement area on the forehead. The collected information is uploaded to the cloud in real time for COVID-19 prevention. Experiments show that the detection model is only 6.1M and the average detection speed is 257ms. At a distance of 1m, the error of indoor temperature measurement is about 3%. That is, the proposed system can realize real-time temperature measurement in public areas., Comment: 6 pages, 8 figures, INFOCOMW ICCN 2021

Integrating the wireless power transfer (WPT) technology into the wireless communication system has been important for operational cost saving and power-hungry problem solving of electronic devices. In this paper, we propose a resonant beam simultaneous wireless information and power transfer (RB-SWIPT) system, which utilizes a gain medium and two retro-reflecting surfaces to enhance and retro-reflect energy, and allows devices to recharge their batteries and exchange information from the resonant beam wirelessly. To reveal the SWIPT mechanism and evaluate the SWIPT performance, we establish an analytical end-to-end (E2E) transmission model based on a modular approach and the electromagnetic field propagation. Then, the intra-cavity power intensity distribution, transmission loss, output power, and E2E efficiency can be obtained. The numerical evaluation illustrates that the exemplary RB-SWIPT system can provide about 4.20W electric power and 12.41bps/Hz spectral efficiency, and shorter transmission distance or larger retro-reflecting surface size can lead to higher E2E efficiency. The RB-SWIPT presents a new way for high-power, long-range WPT, and high-rate communication.

Wireless charging for mobile Internet of Things (IoT) devices such as smartphones is extremely difficult. To reduce energy dissipation during wireless transmission in mobile scenarios, laser or narrow radio beams with sophisticated tracking control are typically required. However, reaching the necessary tracking accuracy and reliability is really difficult. In this paper, inspired by the features of optical resonators and retroreflectors, we develop an experiment on a self-aligned resonant beam charging system for long-distance mobile power transfer. It exploits light resonances inside a double-retroreflector-based spatially separated laser resonator (SSLR), which eliminates the requirement for any kind of tracking control. Focal telecentric cat's eye retroreflectors are employed here. The SSLR was investigated by both theoretical calculation and experiment. We also well assembled the transmitter and the receiver and demonstrated its application in mobile smartphone charging. The results show that above 5-W optical power (also obtained more than 0.6-W electrical power) transferring with negligible diffraction loss to a few-centimeter-size receiver is realized while the receiver moves arbitrarily within 2-m vertical distance and 6{\deg} field of view from the transmitter. The maximum horizontal moving range is up to 18cm. This wireless charging system empowers a smartphone in mobile operation with unlimited battery life without the need for a cable.

The newly established Heisenberg limit in arbitrary waveform estimation is quite different with parameter estimation and shows a unique characteristic of a future quantum version of oscilloscope. However, it is still a non-trivial challenge to generate a large number of exotic quantum entangled states to achieve this quantum limit. Here, by employing the time-domain quantum difference detection method, we demonstrate Heisenberg-limited waveform quantum estimation with diamond spins under ambient condition in the experiment. Periodic dynamical decoupling is applied to enhance both the dynamic range and sensitivity by one order of magnitude. Using this quantum-enhanced estimation scheme, the estimation error of an unknown waveform is reduced by more than $5$ dB below the standard quantum limit with $N\sim{\text{2}} \times {\text{1}}{{\text{0}}^3}$ resources, where more than ${1 \times {\text{1}}{{\text{0}}^5}}$ resources would be required to achieve a similar error level using classical detection. This work provides an essential step towards realizing quantum-enhanced structure recognition in a continuous space and time., Comment: 15 pages, 8 figures

Focusing electromagnetic field to enhance the interaction with matter has been promoting researches and applications of nano electronics and photonics. Usually, the evanescent-wave coupling is adopted in various nano structures and materials to confine the electromagnetic field into a subwavelength space. Here, based on the direct coupling with confined electron oscillations in a nanowire, we demonstrate an extreme localization of microwave field down to 10$^{-6}\lambda$. A hybrid nanowire-bowtie antenna is further designed to focus the free-space microwave to this deep-subwavelength space. Detected by the nitrogen vacancy center in diamond, the field intensity and microwave-spin interaction strength are enhanced by 2.0$\times$10$^{8}$ and 1.4$\times$10$^{4}$ times, respectively. Such an extreme concentration of microwave field will further promote integrated quantum information processing, sensing and microwave photonics in a nanoscale system., Comment: 16 pages, 10 figures

We experimentally demonstrate fast and high-fidelity geometric control of a quantum system with the most brachistochrone method on hybrid spin registers in diamond. Based on the time-optimal universal geometric control, single geometric gates with the fidelities over 99.2% on the spin state of nitrogen-vacancy center are realized with average durations shortened by 74.9%, comparing with conventional geometric method. The fidelity of the fast geometric two-qubit gate exceeds 96.5% on the hybrid spin registers. With these fast high-fidelity gates available, we implement quantum entanglement-enhanced phase estimation algorithm and demonstrate the Heisenberg quantum limit at room-temperature. By comparing with the conventional geometric circuit, the measurement bandwidth and sensitivity is enhanced by 3.5 and 2.9 times. Hence, our results show that high-fidelity quantum control based on a fast geometric route will be a versatile tool for broad applications of quantum information processing in practice., Comment: 15 pages, 7 figures

In this study, we present a novel clustering-based collaborative filtering (CF) method for recommender systems. Clustering-based CF methods can effectively deal with data sparsity and scalability problems. However, most of them are applied to a single representation space, which might not characterize complex user-item interactions well. We argue that the user-item interactions should be observed from multiple views and characterized in an adaptive way. To address this issue, we leveraged the global and local properties to construct multiple representation spaces by learning various training datasets and loss functions. An attention network was built to generate a blended representation according to the relative importance of the representation spaces for each user-item pair, providing a flexible way to characterize diverse user-item interactions. Substantial experiments were evaluated on four popular benchmark datasets. The results show that the proposed method is superior to several CF methods where only one representation space is considered., Comment: This paper was accepted by IEEE Transactions on Computational Social Systems (TCSS) in November 2021

Nitrogen-vacancy quantum defects in diamond offer a promising platform for magnetometry because of their remarkable optical and spin properties. In this Letter, we present a high-sensitivity and wide-bandwidth fiber-based quantum magnetometer for practical applications. By coating the diamond surface with silver reflective film, both the fluorescence collection and excitation efficiency are enhanced. Additionally, tracking pulsed optically detected magnetic resonance spectrum allowed a magnetic field sensitivity of $35$ pT$/\sqrt{\rm{Hz}}$ and a bandwidth of $4.1$ KHz. Finally, this magnetometer was successfully applied to map the magnetic field induced by the current-carrying copper-wire mesh. Such a stable and compact magnetometry can provide a powerful tool in many areas of physical, chemical, and biological researches., Comment: 5 pages, 5 figures

The nonlinear fluorescence emission has been widely applied for the high spatial resolution optical imaging. Here, we studied the fluorescence anomalous saturating effect of the nitrogen vacancy defect in diamond. The fluorescence reduction was observed with high power laser excitation. It increased the nonlinearity of the fluorescence emission, and changed the spatial frequency distribution of the fluorescence image. We used a differential excitation protocol to extract the high spatial frequency information. By modulating the excitation laser's power, the spatial resolution of imaging was improved approximate 1.6 times in comparison with the confocal microscopy. Due to the simplicity of the experimental setup and data processing, we expect this method can be used for improving the spatial resolution of sensing and biological labeling with the defects in solids.

Experimental realization of a universal set of quantum logic gates with high-fidelity is critical to quantum information processing, which is always challenging by inevitable interaction between the quantum system and environment. Geometric quantum computation is noise immune, and thus offers a robust way to enhance the control fidelity. Here, we experimentally implement the recently proposed extensible nonadiabatic holonomic quantum computation with solid spins in diamond at room-temperature, which maintains both flexibility and resilience against decoherence and system control errors. Compared with previous geometric method, the fidelities of a universal set of holonomic single-qubit and two-qubit quantum logic gates are improved in experiment. Therefore, this work makes an important step towards fault-tolerant scalable geometric quantum computation in realistic systems., Comment: 9 pages, 6 figures

Resonant Beam Charging (RBC) is a promising multi-Watt and multi-meter wireless power transfer method with safety, mobility and simultaneously-charging capability. However, RBC system operation relies on information availability including power receiver location, class label and the receiver number. Since smartphone is the most widely-used mobile device, we propose a Mask R-CNN based smartphone detection model in the RBC system. Experiments illustrate that our model reduces the smartphone scanning time to one third. Thus, this machine learningdetectionapproachprovidesanintelligentwaytoimprove the user experience in wireless power transfer for mobile and Internet of Things (IoT) devices.

Resonant Beam Charging (RBC) is a wireless charging technology which supports multi-watt power transfer over meter-level distance. The features of safety, mobility and simultaneous charging capability enable RBC to charge multiple mobile devices safely at the same time. To detect the devices that need to be charged, a Mask R-CNN based dection model is proposed in previous work. However, considering the constraints of the RBC system, it's not easy to apply Mask R-CNN in lightweight hardware-embedded devices because of its heavy model and huge computation. Thus, we propose a machine learning detection approach which provides a lighter and faster model based on traditional Mask R-CNN. The proposed approach makes the object detection much easier to be transplanted on mobile devices and reduce the burden of hardware computation. By adjusting the structure of the backbone and the head part of Mask R-CNN, we reduce the average detection time from $1.02\mbox{s}$ per image to $0.6132\mbox{s}$, and reduce the model size from $245\mbox{MB}$ to $47.1\mbox{MB}$. The improved model is much more suitable for the application in the RBC system.

Resonant Beam Charging (RBC) is the Wireless Power Transfer (WPT) technology, which can provide high-power, long-distance, mobile, and safe wireless charging for Internet of Things (IoT) devices. Supporting multiple IoT devices charging simultaneously is a significant feature of the RBC system. To optimize the multi-user charging performance, the transmitting power should be scheduled for charging all IoT devices simultaneously. In order to keep all IoT devices working as long as possible for fairness, we propose the First Access First Charge (FAFC) scheduling algorithm. Then, we formulate the scheduling parameters quantitatively for algorithm implementation. Finally, we analyze the performance of FAFC scheduling algorithm considering the impacts of the receiver number, the transmitting power and the charging time. Based on the analysis, we summarize the methods of improving the WPT performance for multiple IoT devices, which include limiting the receiver number, increasing the transmitting power, prolonging the charging time and improving the single-user's charging efficiency. The FAFC scheduling algorithm design and analysis provide a fair WPT solution for the multi-user RBC system., Comment: 11 pages, 12 figures

The nitrogen-vacancy center in diamond has been broadly applied in quantum sensing since it is sensitive to different physical quantities. Meanwhile, it is difficult to isolate disturbances from unwanted physical quantities in practical applications. Here, we present a robust fiber-based quantum thermometer which can significantly isolate the magnetic field noise and microwave power shift. With a frequency modulation scheme, we realize the temperature measurement by detecting the variation of the sharp-dip in the zero-field optically detected magnetic resonance spectrum in a high-density nitrogen-vacancy ensemble. Thanks to its simplicity and compatibility in implementation and robustness in the isolation of magnetic and microwave noise, this quantum thermometer is then applied to the surface temperature imaging of an electronic chip with a sensitivity of $18$ $\rm{mK}/\sqrt{\rm{Hz}}$. It paves the way to high sensitive temperature measurement in ambiguous environments., Comment: 10 pages, 6 figures

The quality of a quantum operation determines the performance of quantum information processing, such as the sensitivity of quantum sensing. Different from the fidelity of quantum operation in quantum computation, we present an effective function to evaluate the performance and diagnose the imperfection of operations in multi-pulse based quantum sensing. The evaluation function directly links the realistic sensitivity with intrinsic sensitivity in a simple way. Moreover, guided by this evaluation function, we optimize a composite pulse sequence for high sensitivity nitrogen-vacancycenter based magnetometry against spectrum inhomogeneities and control errors to improve the signal-to-noise ratio of nanoscale nuclear magnetic resonance by 1 order of magnitude. It marks an important step towards quantitative quantum sensing with imperfect quantum control in practical applications., Comment: 10 pages, 9 figures

Light has shown up an incredibe capability in precision measurement based on opto-mechanic interaction in high vacuum by isolating environment noises. However, there are still obstructions, such as displacement and mass estimation error, highly hampering the improvement of absolute accuracy at the nanoscale. Here, we present a nonlinearity based metrology to precisely measure the position and mass of a nanoparticle with optical levitation under $10^{-5}$ mbar, 6-order of magnitude lower than the electrostatic-force and stochastic-force-based counterparts. By precisely controlling the amplitude of the levitated nanoparticle at the nonlinear regime, we realized a feasible sub-picometer-level position measurement with an uncertainty of $1.0\%$ without the prior information of mass, which can be further applied to weigh the femtogram-level mass with an uncertainty of $2.2\%$. It will also pave the way to construct a well-calibrated opto-mechanic platform in high vacuum for high sensitivity and accuracy measurement in force and acceleration at the nanoscale and the study in quantum superposition at the mesoscopic scale., Comment: 9 pages, 6 figures

We report the application of machine learning methods for predicting the effective diffusivity (De) of two-dimensional porous media from images of their structures. Pore structures are built using reconstruction methods and represented as images, and their effective diffusivity is computed by lattice Boltzmann (LBM) simulations. The datasets thus generated are used to train convolutional neural network (CNN) models and evaluate their performance. The trained model predicts the effective diffusivity of porous structures with computational cost orders of magnitude lower than LBM simulations. The optimized model performs well on porous media with realistic topology, large variation of porosity (0.28-0.98), and effective diffusivity spanning more than one order of magnitude (), e.g., >95% of predicted De have truncated relative error of <10% when the true De is larger than 0.2. The CNN model provides better prediction than the empirical Bruggeman equation, especially for porous structure with small diffusivity. The relative error of CNN predictions, however, is rather high for structures with De < 0.1. To address this issue, the porosity of porous structures is encoded directly into the neural network but the performance is enhanced marginally. Further improvement, i.e., 70% of the CNN predictions for structures with true De < 0.1 have relative error <30%, is achieved by removing trapped regions and dead-end pathways using a simple algorithm. These results suggest that deep learning augmented by field knowledge can be a powerful technique for predicting the transport properties of porous media. Directions for future research of machine learning in porous media are discussed based on detailed analysis of the performance of CNN models in the present work.

Nitrogen-vacancy centers in diamond are attractive as quantum sensors owing to their remarkable optical and spin properties under ambient conditions. Here we experimentally demonstrated a hybrid fiber-based thermometer coupled with nitrogen-vacancy center ensemble and a permanent magnet, where the temperature sensitivity was improved by converting the temperature variation to the magnetic field change based on the thermal-demagnetization of the permanent magnet. We have achieved both large temperature working range (room temperature to 373 K) and millikelvin sensitivity (1.6 mK/sqrt(Hz)), nearly 6-fold improvement compared with conventional technique. This stable and compact hybrid thermometer will enable a wide range of applications for large-area detection and imaging with high temperature sensitivity., Comment: 5 pages, 5 figures

The motion control of a levitated nanoparticle plays a central role in optical levitation for fundamental studies and practical applications. Here, we presented a digital parametric feedback cooling based on switching between two trapping laser intensity levels with square wave modulations. The effects of modulation depth and modulation signal phase on the cooling result were investigated in detail. With such a digital parametric feedback method, the centre-of-mass temperature of all three motional degrees of freedom can be cooled to dozens of milli-Kelvin, which paved the way to fully control the motion of the levitated nanoparticle with a programmable digital process for wild applications., Comment: 5 pages, 6 figures

Optical detection of spin state has been widely used for the solid state spin qubit in the application of quantum information processing. The signal contrast determines the accuracy of quantum state manipulation, sensitivity of quantum sensing and resolution of quantum imaging. Here, we demonstrated a time-gated fluorescence detection method for enhancing the spin state signal contrast of nitrogen vacancy (NV) center in diamond. By adjusting the delay between time gate and the excitation laser pulse, we improved both the signal contrast and signal-to-noise ratio for NV spin detection. An enhancement ratio of 1.86 times was reached for the signal contrast. Utilizing the time-gated fluorescence detection, we further demonstrated a high contrast quantum imaging of nanoparticle's stray magnetic field. Without any additional manipulation of the quantum state, we expect that this method can be used to improve the performance of various applications with NV center.

The sensitivity of a practical quantum magnetometer is challenged by both inhomogeneous coupling between sensors and environment and errors in quantum control. Based on the physical criteria of modern quantum sensing, we present a robust and effective composite-pulse for high fidelity operation against inhomogeneous broadening of sensor and control errors via optimized modulation of control field. Such a technique is verified on nitrogen-vacancy (NV) center in diamond to keep almost perfect operation up to a detuning as larger as $110\%$. The sensitivity of the magnetometer with NV center ensemble is experimentally improved by a factor of $4$, comparing to dynamical decoupling with normal rectangular pulse. Our work marks an important step towards high trustworthy ultra-sensitive quantum sensing with imperfect quantum control in realistic systems. The used principle however, is universal and not restricted to NV center ensemble magnetometer., Comment: 16 pages, 6 figures

Resonant Beam Charging (RBC) is a promising Wireless Power Transfer (WPT) technology to provide long-range, high-power, mobile and safe wireless power for the Internet of Things (IoT) devices. The Point-to-Multipoint (PtMP) RBC system can charge multiple receivers simultaneously similar to WiFi communications. To guarantee the Quality of Charging Service (QoCS) for each receiver and maximize the overall earning in the PtMP RBC service, we specify the Charging Pricing Strategy (CPS) and develop the High Priority Charge (HPC) scheduling algorithm to control the charging order and power allocation. Each receiver is assigned a priority, which is updated dynamically based on its State of Charging (SOC) and specified charging power. The receivers with high priorities are scheduled to be charged in each time slot. We present the pseudo code of the HPC algorithm based on quantifying the receiver's SOC, discharging energy and various relevant parameters. Relying on simulation analysis, we demonstrate that the HPC algorithm can achieve better QoCS and earning than the Round-Robin Charge (RRC) scheduling algorithm. Based on the performance evaluation, we illustrate that the methods to improve the PtMP RBC service are: 1) limiting the receiver number within a reasonable range and 2) prolonging the charging duration as long as possible. In summary, the HPC scheduling algorithm provides a practical strategy to maximize the earning of the PtMP RBC service with each receiver's QoCS guarantee.

Resonant Beam Charging (RBC) is the Wireless Power Transfer (WPT) technology, which can provide high-power, long-distance, mobile, and safe wireless charging for Internet of Things (IoT) devices. Supporting multiple IoT devices charging simultaneously is a significant feature of the RBC system. To optimize the multi-user charging performance, the transmitting power should be scheduled for charging all IoT devices simultaneously. In order to keep all IoT devices working as long as possible for fairness, we propose the First Access First Charge (FAFC) scheduling algorithm. Then, we formulate the scheduling parameters quantitatively for algorithm implementation. Finally, we analyze the performance of FAFC scheduling algorithm considering the impacts of the receiver number, the transmitting power and the charging time. Based on the analysis, we summarize the methods of improving the WPT performance for multiple IoT devices, which include limiting the receiver number, increasing the transmitting power, prolonging the charging time and improving the single-user's charging efficiency. The FAFC scheduling algorithm design and analysis provide a fair WPT solution for the multi-user RBC system.

As a long-range high-power wireless power transfer (WPT) technology, resonant beam charging (RBC) can transmit Watt-level power over long distance for the devices in the internet of things (IoT). Due to its open-loop architecture, RBC faces the challenge of providing dynamic current and voltage to optimize battery charging performance. In RBC, battery overcharge may cause energy waste, thermal effects, and even safety issues. On the other hand, battery undercharge may lead to charging time extension and significant battery capacity reduction. In this paper, we present an adaptive resonant beam charging (ARBC) system for battery charging optimization. Based on RBC, ARBC uses a feedback system to control the supplied power dynamically according to the battery preferred charging values. Moreover, in order to transform the received current and voltage to match the battery preferred charging values, ARBC adopts a direct current to direct current (DC-DC) conversion circuit. Relying on the analytical models for RBC power transmission, we obtain the end-to-end power transfer relationship in the approximate linear closed-form of ARBC. Thus, the battery preferred charging power at the receiver can be mapped to the supplied power at the transmitter for feedback control. Numerical evaluation demonstrates that ARBC can save 61% battery charging energy and 53%-60% supplied energy compared with RBC. Furthermore, ARBC has high energy-saving gain over RBC when the WPT is unefficient. ARBC in WPT is similar to link adaption in wireless communications. Both of them play the important roles in their respective areas., Comment: 12 pages, 24 figures, IEEE Internet of Things Journal

Optical communication systems are able to send the information from one user to another in light beams that travel through the free space or optical fibers, therefore how to send larger amounts of information in smaller periods of time is a long term concern, one promising way is to use multiplexing of photon's different degrees of freedoms to parallel handle the large amounts of information in multiple channels independently. In this work, by combining the wavelength and time division multiplexing technologies, we prepare a multifrequency mode time bin entangled photon pair source at different time slots by using four wave mixing in a silicon nanowire waveguide, and distribute entangled photons into 3 time by 14 wavelength channels independently, which can significantly increase the bit rate compared with the single channel systems in quantum communication. Our work paves a new and promising way to achieve a high capacity quantum communication and to generate a multiple photon nonclassical state., Comment: 11 pages, 6 figures, comments welcome

Dense wavelength division multiplexing (DWDM) is one of the most successful methods for enhancing data transmission rates in both classical and quantum communication networks. Although signal multiplexing and demultiplexing are equally important, traditional multiplexing and demultiplexing methods are based on passive devices such as arrayed waveguides and fiber Bragg cascade filters, which, although widely used in commercial devices, lack any active tuning ability. In this work, we propose a signal demultiplexing method based on sum frequency generation (SFG) with two significant features: first, any signal from the common communication channel can be demultiplexed to a single user by switching the pump wavelength; second, a cheap high-performance detector can be used for signal detection. These two features were demonstrated by demultiplexing multi-channel energy-time entanglement generated by a micro-cavity silicon chip. High interference visibilities over three channels after demultiplexing showed that entanglement was preserved and verified the high performance of the demultiplexer, which will find wide application in high-capacity quantum communication networks., Comment: 7 pages, 4 figures, comments welcome

The memory effects in non-Markovian quantum dynamics can induce the revival of quantum coherence, which is believed to provide important physical resources for quantum information processing (QIP). However, no real quantum algorithms have been demonstrated with the help of such memory effects. Here, we experimentally implemented a non-Markovianity-assisted highfidelity refined Deutsch-Jozsa algorithm (RDJA) with a solid spin in diamond. The memory effects can induce pronounced nonmonotonic variations in the RDJA results, which were confirmed to follow a non-Markovian quantum process by measuring the non-Markovianity of the spin system. By applying the memory effects as physical resources with the assistance of dynamical decoupling, the probability of success of RDJA was elevated above 97% in the open quantum system. This study not only demonstrates that the non-Markovianity is an important physical resource but also presents a feasible way to employ this physical resource. It will stimulate the application of the memory effects in non-Markovian quantum dynamics to improve the performance of practical QIP., Comment: 11 pages, 8 figures

Wireless power transfer (WPT) is a promising solution to provide convenient and perpetual energy supplies to electronics. Traditional WPT technologies face the challenge of providing Watt-level power over meter-level distance for Internet of Things (IoT) and mobile devices, such as sensors, controllers, smart-phones, laptops, etc.. Distributed laser charging (DLC), a new WPT alternative, has the potential to solve these problems and enable WPT with the similar experience as WiFi communications. In this paper, we present a multi-module DLC system model, in order to illustrate its physical fundamentals and mathematical formula. This analytical modeling enables the evaluation of power conversion or transmission for each individual module, considering the impacts of laser wavelength, transmission attenuation and photovoltaic-cell (PV-cell) temperature. Based on the linear approximation of electricity-to-laser and laser-to-electricity power conversion validated by measurement and simulation, we derive the maximum power transmission efficiency in closed-form. Thus, we demonstrate the variation of the maximum power transmission efficiency depending on the supply power at the transmitter, laser wavelength, transmission distance, and PV-cell temperature. Similar to the maximization of information transmission capacity in wireless information transfer (WIT), the maximization of the power transmission efficiency is equally important in WPT. Therefore, this work not only provides the insight of DLC in theory, but also offers the guideline of DLC system design in practice., Comment: add table IV

The atom-light interaction in a three-level system has shown significant physical phenomena, such as electromagnetically induced transparency and Autler{Townes splitting (ATS), for broad applications in classical and quantum information techniques. Here, we optimally demonstrated the ATS with a quantum state manipulation method. The ATS in the dephasing-dominated diamond NV center system was successfully recovered by coherent microwave control, which cannot be observed with traditional method. The dynamical process of ATS was investigated in detail, revealing a nontrivial quantum interference with geometric phase modulations. Based on the quantum interference, the signal of the optimal ATS is twice as intense as those with traditional observation method., Comment: 10 pages and 9 figures

Non-reciprocal devices, which allow the non-reciprocal signal routing, serve as the fundamental elements in photonic and microwave circuits and are crucial in both classical and quantum information processing. The radiation-pressure-induced coupling between light and mechanical motion in traveling wave resonators has been exploited to break the Lorentz reciprocity, realizing non-reciprocal devices without magnetic materials. Here, we experimentally demonstrate a reconfigurable nonreciprocal device with alternative functions of either a circulator or a directional amplifier via the optomechanically induced coherent photon-phonon conversion or gain. The demonstrated device exhibits considerable flexibility and offers exciting opportunities for combining reconfigurability, non-reciprocity and active properties in single photonic structures, which can also be generalized to microwave as well as acoustic circuits., Comment: 13 pages, 4 Figures

The quantum statistics of particles is determined by both the spins and the indistinguishability of quantum states. Here we studied the quantum statistics of partially distinguishable photons by defining the multi-photon indistinguishability. The photon bunching co-efficient was formulated based on the properties of permutation symmetry, and a modified Bose--Einstein statistics was presented with an indistinguishability induced photon bunching effect. Moreover, the statistical transition of the photon state was studied for partially distinguishable photons, and the results shows the that indistinguishability exhibits the same role as that observed in the generation of laser. The results will fill the gap between Bose--Einstein and Poisson statistics for photons, and a formula is presented for the study of multi-photon quantum information processes., Comment: 6 pages, 3 figures

Photon statistics is one of the key properties of the photon state for the study of quantum coherence and quantum information techniques. Here, we discuss the photon indistinguishability induced bunching effect which can significantly change photon statistics. Through the measurement of the second-order degree of coherence of a mixed photon state composed of a single-photon state and a weak coherent state, the statistical transition from a classical behavior to a nonclassical behavior is experimentally demonstrated by modifying the indistinguishability of the two-photon states. The study will help us to understand and control the photon statistics with a method for quantum optical coherence and quantum information applications. It also indicates that the photon indistinguishability is a key parameter for multipartite quantum coherence., Comment: 5pages, 5 figures