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This study offers a theoretical solution for the neutral surface position of a space lightweight mirror employing two-axis bipod flexible mounts (TABFM) evenly distributed at three locations along the circumference. To maximize the surface shape accuracy of the mirror (SSAM) under the influence of radial gravity, it is typically necessary that the center of rotation of the TABFM coincides with the position of the neutral surface of the mirror (PNSM). Departing from the PNSM, the SSAM will be substantially deteriorated. In this paper, the compliance matrix of the TABFM utilized for space lightweight mirrors is initially solved. Subsequently, based on the compliance matrix, the analytical formulas and solution approaches for the PNSM under the action of 1g gravity are derived when the support structure of the mirror is symmetrically arranged horizontally and vertically. Additionally, a sensitivity analysis of the PNSM is also conducted. Finally, it is verified through the finite element simulation method. The results indicate that when the support structure of the mirror is uniformly distributed along the circumference and symmetrically arranged horizontally, the PNSM is solely related to the flexibility of the support structure, and the error between the theoretical calculation results and the finite element simulation results is merely 3.2‰; when the mirror support structure is uniformly distributed along the circumference and symmetrically arranged vertically, the PNSM is determined by the flexibility of the support structure and the mass characteristics of the mirror, and the error between the theoretical calculation results and the finite element simulation results is 2.1%. The proposed solution method of PNSM has been implemented in practical engineering projects. The method proposed in this paper can rapidly solve the PNSM and significantly enhance the efficiency and accuracy of integrated simulation optimization. Additionally, the method applies not only to the TABFM investigated in this paper but also to tripod mounts or other symmetric side support structures.

Efficient piston estimation is a critical factor in preserving the image quality in synthetic aperture telescopes. When the light source or observation scene is an extended object, the spatial properties of the target and the point spread function (PSF) will undergo convolution effects on the scientific image plane, posing a significant challenge to numerous developed point-source piston sensing methods. In this paper, we investigate a model-driven-based piston sensing strategy capable of high-accuracy piston measurement for extended scenes. Firstly, a mathematical model of the feature vector is constructed to respond to the piston accurately and subsequently we characterize its nonlinear relationship with the piston, termed the frequency secondary-peak piston extraction (FSPE) algorithm. Furthermore, an optimization framework is designed to automatically generate the non-redundant configuration, avoiding the potential baseline crosstalk that can cause the misalignment of feature vector extraction in FSPE. Since the decoupled feature vector contains the analytic properties, through sequentially placing the non-redundant mask and performing the FSPE algorithm, the pistons can be directly retrieved without iterations and any additional instruments. Both numerical simulation and experimental results demonstrate the effectiveness of the proposed method.Given the efficiency and superiority, we believe that the proposed method might find wide applications in future extremely large synthetic aperture telescopes.

In this paper, we proposed and numerically verified a perfect absorber composed of unstructured nature hyperbolic material α-MoO 3 layers on top of photonic crystal (PhC) layers and reflecting mirrors, which can attain nearly perfect absorption of 99.94% at 24.7 terahertz (THz) in Transverse Magnetic (TM) mode. We demonstrate that the absorption efficacy can be regulated by adjusting structural parameters, meeting the requirements of the absorption spectrum spanning from the microwave to the infrared (IR) region. This study presents an exemplary application of natural hyperbolic materials in the realm of perfect absorption, offering significant potential for use in sensing and detection.

The achievement of distinct wavefront reconstruction for orthogonally polarized electromagnetic (EM) waves in a broadband frequency range is extremely important in modern wireless communications. However, the development of circularly polarized wavefront modulation devices is hindered by conjugate symmetric phase responses introduced by the rotation-induced geometric phase. Herein, a spin-decoupled meta-atom with a novel structure is designed to independently tailor left-hand and right-hand circularly polarized incident waves over a broadband range of 12-28 GHz with a fractional bandwidth of 80%. By incorporating diagonal curvature-induced and conventional geometric phases, spin-dependent phase modulation covering the entire 2π range can be obtained. As a proof of concept, three prototypes are designed and manufactured. In addition, a four-channel imaging method is proposed to enhance the information capacity of the meta-hologram. Furthermore, the applications of the proposed spin-decoupled method are also investigated in metalens and orbital angular momentum. Both the calculation and experimentation demonstrate the feasibility of the proposed spin-decoupled phase modulation strategy, which has potential applications in information metasurfaces, metalens, wireless communications, and other fields.

Pulsed light detecting and ranging (Lidar) is capable of acquiring comprehensive target information within a single pulse, including distance and intensity data. Intensity data reflects the target's backscattered intensity and is commonly regarded as a crucial observational parameter associated with target reflectivity information. Multiple studies have indicated the potential of intensity data in various applications within pulsed Lidar contexts. However, the intensity data is influenced by the incident angle and distance; hence it cannot directly manifest target characteristics. Consequently, a prerequisite for its usage is the implementation of intensity calibration. This paper presents a target intensity correction method based on an improved tail model, designed for preprocessing intensity data. First, the pulse echo signal equation is derived by incorporating the improved tail model with the detected target. On this foundation, a target echo intensity correction model is established to correct the intensities at various incident angles to those at the normal direction. Lastly, the derived approach is validated through simulation analysis, and practical experiments are conducted on a constructed pulsed Lidar system. These experiments meticulously investigate the influences of incident angle and distance, two prominent factors, on echo intensity. In the context of incident angle correction experiments, the mean absolute errors (MAEs) in calibrated values for diverse targets all remain within 0.04 V. Prior to correction, the maximum MAE for the cystosepiment is 0.505 V; after the correction it is reduced to merely 0.02 V, indicating a 96% reduction in error. Furthermore, all discrepancies exhibit an error standard deviation (ESD) of 0.03 V or less, showcasing favorable stability. For distance correction, under normal incidence conditions, a diverse set of targets is measured at different distances to achieve corrected MAE and ESD within 0.05 V. Consequently, the proposed method effectively achieves intensity correction concerning incident angles and distances. To achieve this, a reflectivity lookup table for the relevant targets was established. Combining this with the corrected intensity information enabled target identification in the three-dimensional imaging of pulsed Lidar.

The quantum digital signature protocol offers a replacement for most aspects of public-key digital signatures ubiquitous in today's digital world. A major advantage of a quantum-digital-signatures protocol is that it can have information-theoretic security, whereas public-key cryptography cannot. Here we demonstrate and characterize hardware to implement entanglement-based quantum digital signatures over our campus network. Over 25 hours, we collect measurements on our campus network, where we measure sufficiently low quantum bit error rates (<5% in most cases) which in principle enable quantum digital signatures at over 50 km as shown through rigorous simulation accompanied by a noise model developed specifically for our implementation. These results show quantum digital signatures can be successfully employed over deployed fiber. Moreover, our reported method provides great flexibility in the number of users, but with reduced entanglement rate per user. Finally, while the current implementation of our entanglement-based approach has a low signature rate, feasible upgrades would significantly increase the signature rate.

We correct typographical errors in Eq. (15) in [Opt. Express30, 15184 (2022)10.1364/OE.456597] [1]. These errors were not present in the actual formulas used to calculate the results of the paper, so all results remain unaffected.

In-line X-ray phase-contrast computed tomography typically contains two independent procedures: phase retrieval and computed tomography reconstruction, in which multi-material and streak artifacts are two important problems. To address these problems simultaneously, an accelerated 3D iterative image reconstruction algorithm is proposed. It merges the above-mentioned two procedures into one step, and establishes the data fidelity term in raw projection domain while introducing 3D total variation regularization term in image domain. Specifically, a transport-of-intensity equation (TIE)-based phase retrieval method is updated alternately for different areas of the multi-material sample. Simulation and experimental results validate the effectiveness and efficiency of the proposed algorithm.

Continuous-variable (CV) photonic states are of increasing interest in quantum information science, bolstered by features such as deterministic resource state generation and error correction via bosonic codes. Data-efficient characterization methods will prove critical in the fine-tuning and maturation of such CV quantum technology. Although Bayesian inference offers appealing properties-including uncertainty quantification and optimality in mean-squared error-Bayesian methods have yet to be demonstrated for the tomography of arbitrary CV states. Here we introduce a complete Bayesian quantum state tomography workflow capable of inferring generic CV states measured by homodyne or heterodyne detection, with no assumption of Gaussianity. As examples, we demonstrate our approach on experimental coherent, thermal, and cat state data, obtaining excellent agreement between our Bayesian estimates and theoretical predictions. Our approach lays the groundwork for Bayesian estimation of highly complex CV quantum states in emerging quantum photonic platforms, such as quantum communications networks and sensors.

An all-fiber Mach-Zehnder interferometer (MZI) using ring core few-mode fiber (RC-FMF) for curvature sensing is proposed and experimentally demonstrated. The MZI was fabricated by splicing a segment of RC-FMF between two pieces of single-mode fiber (SMF). With the benefit of a RC of the central axis of the RC-FMF, the sensor is more sensitive to curvature compared to other fiber sensors based on ordinary SMF or FMF. Curvature measurement can be achieved by monitoring the wavelength shift of interference dips. Experimental results have shown that the sensitivity of curvature sensing can reach up to -4.370 n m / m -1 , within the range of 1.199-1.549 m -1 . Also, the temperature sensing characteristics of the sensor are measured, and the maximum temperature sensitivity is 57.6 pm/°C, ranging from 25°C to 45°C. The proposed MZI sensor has excellent potential for curvature measurement of building structural health monitoring, bridge engineering, and more.

Modern imaging optics ensures high-quality photography at the cost of a complex optical form factor that deviates from the portability. The drastic development of image processing algorithms, especially advanced neural networks, shows great promise to use thin optics but still faces the challenges of residual artifacts and chromatic aberration. In this work, we investigate photorealistic thin-lens imaging that paves the way to actual applications by exploring several fine-tunes. Notably, to meet all-day photography demands, we develop a scene-specific generative-adversarial-network-based learning strategy and develop an integral automatic acquisition and processing pipeline. Color fringe artifacts are reduced by implementing a chromatic aberration pre-correction trick. Our method outperforms existing thin-lens imaging work with better visual perception and excels in both normal-light and low-light scenarios.

Propagation-based X-ray phase-contrast computed tomography (PB-PCCT) can serve as an effective tool for studying organ function and pathologies. However, it usually suffers from a high radiation dose due to the long scan time. To alleviate this problem, we propose a deep learning reconstruction framework for PB-PCCT with sparse-view projections. The framework consists of dual-path deep neural networks, where the edge detection, edge guidance, and artifact removal models are incorporated into two subnetworks. It is worth noting that the framework has the ability to achieve excellent performance by exploiting the data-based knowledge of the sample material characteristics and the model-based knowledge of PB-PCCT. To evaluate the effectiveness and capability of the proposed framework, simulations and real experiments were performed. The results demonstrated that the proposed framework could significantly suppress streaking artifacts and produce high-contrast and high-resolution computed tomography images.

The surface figure precision, weight, and dynamic performance of spaceborne primary mirrors depend on mirror structure parameters, which are usually optimized to improve the overall performance. To realize rapid multi-objective design optimization of a primary mirror with multiple apertures, a fully parameterized primary mirror structure is established. A surrogate model based on a hybrid of improved particle swarm optimization (IPSO), adaptive genetic algorithm (IAGA), and optimized back propagation neural network (IPSO-IAGA-BPNN) is developed to replace optomechanical simulation with its high computational cost. In this model, a self-adaptive inertia weight and a modified genetic operator are introduced into the particle swarm optimization (PSO) and adaptive genetic algorithm (AGA), respectively. The connection parameters of BPNN are optimized by the IPSO-IAGA algorithm for global searching capability. Further, the proposed IPSO-IAGA-BPNN, based on a rapid multi-objective optimization framework for a fully parameterized primary mirror structure, is established. Moreover, in addition to the proposed IPSO-IAGA-BPNN model, the Kriging, RSM, BPNN, GA-BPNN, PSO-BPNN, and PSO-GA-BPNN models are also analyzed as contrast models. The comparison results indicate that the predicted value obtained by IPSO-IAGA-BPNN is superior to the six other surrogate models since its mean absolute percentage error is less than 3% and its R 2 is more than 0.99. Finally, we present a Pareto-optimal primary mirror design and implement it through three optimization methods. The verification results show that the proposed method predicts mirror structural performance more accurately than existing surrogate-based methods, and promotes significantly superior computational efficiency compared to the conventional integration-based method.

Pulsed Lidar can obtain rich target information in one pulse, but the echo pulse signal is extremely susceptible to low laser transmitting power and complex target environments, resulting in an amplitude that is too low, which affects detection efficiency and ranging accuracy. In this paper, a variational modal decomposition based on gray wolf optimizer (VMD-GWO) and an empirical mode decomposition (EMD) parallel for denoising and signal enhancement in pulse Lidar is proposed and demonstrated completely. First, the adaptive strategy EMD is used for denoising the signal to obtain effective information. The combination of optimal VMD parameters of quadratic penalty α v and decomposition mode k was obtained by using the GWO to select the modal component with the smallest center frequency as effective information. Second, EMD and VMD-GWO parallel optimization algorithms are used to reconstruct the signal to obtain denoising and enhanced signals. Finally, a real experiment was carried out with the pulse Lidar ranging equipment. Our method compared with EMD-soft, EMD-VMD,WL-db4//EMD-DT and WL-db4//VMD has achieved greater improvement. When the target distance and the reflectivity of the reflectivity plate are 30 m and 10%, respectively, the peak signal-to-noise ratio (PSNR) of the weak echo signal calculated by our method can reach 11.5284 dB. And when in the dead zone of the system ranging, it is effectively denoising and enhancing the signal.

The next generation of optical telescopes will provide high-resolution imaging of celestial objects by using the aperture synthesis technique. To preserve the quality of the image, fast corrections of the pistons among subapertures have to be applied, namely, the co-phasing of the array. The image-based co-phasing method via an optimization procedure has been newly developed. Despite simplicity and strong commonality, when dealing with large piston errors, this correction method is also faced with a problem in which the metric function easily falls into the local convergence, especially in the case of broadband imaging with many subapertures. In this study, an improved stochastic parallel gradient descent (SPGD) algorithm based on heuristic search is proposed for co-phasing, termed the metaheuristic SPGD algorithm. The heuristic research scheme assists the original SPGD algorithm in getting rid of local extrema. By iterations of this algorithm, the synthetic system can be co-phased without any additional instruments and operations. The effectiveness of the proposed algorithm is verified by means of simulation. Given the efficiency and superiority, it is expected that the method proposed in this study may find wide applications in multi-aperture imaging.

The broad bandwidth and spectral efficiency of photonics has facilitated unparalleled speeds in long-distance lightwave communication. Yet efficient routing and control of photonic information without optical-to-electrical conversion remains an ongoing research challenge. Here, we demonstrate a practical approach for dynamically transforming the carrier frequencies of dense wavelength-division-multiplexed data. Combining phase modulators and pulse shapers into an all-optical frequency processor, we realize both cyclic channel hopping and 1-to-N broadcasting of input data streams for systems with N = 2 and N = 3 users. Our method involves no optical-to-electrical conversion and enables low-noise, reconfigurable routing of fiber-optic signals with in principle arbitrary wavelength operations in a single platform, offering new potential for low-latency all-optical networking.

In this Letter, we report a segmented large-scaled lightweight diffractive telescope testbed newly built in our laboratory. The telescope, consisting of one 710-mm-diameter element in the center surrounded by eight 352-mm-diameter elements and a smaller eyepiece of achromatic lenses, can realize wide-band high-resolution imaging of 0.55-0.65 µm. The stitching errors are coarsely corrected by adjusting the motion stage mounted on each element. In particular, an optical synthesis system inserted behind the eyepiece is designed to compensate the residual tip-tilt-piston errors. We present the experimental imaging result of two stitched elements, which is the first successful experimental verification obtained by a practical segmented diffractive telescope to enhance the resolution. Moreover, spatial modulation diversity technology is used to restore the synthetic image so as to improve its quality and contrast.

Existing photonic couplers are limited by either large footprint or long interaction length. Here a highly efficient and ultracompact three-port trench-based coupler (TBC) is proposed on an InP platform in terms of the frustrated total internal reflection principle. A single slash-shaped narrow trench located at the "T" intersection of two InP/InGaAsP multiquantum well ridge waveguides forms the coupler. The finite-difference time-domain numerical method is utilized to optimize the parameterization of the couplers, such as splitting ratios and efficiency versus trench widths, lengths, locations, and angles. A single-mode 2 µm wide ridge waveguide coupler having a high aspect ratio trench filled with A l 2 O 3 was fabricated and characterized at 1.55 µm wavelength. The "trench-first" fabrication process is optimized to reduce its inherent insertion loss (IL), showing the IL within a range of 0.3-0.5 dB. The devices can outperform the state-of-the-art trench couplers by ≥∼24 times the figure of merit. These TBCs are thus promising candidates for applications in the next generation of photonic integrated circuits.

We study the problem of determining the photon number statistics of an unknown quantum state using conjugate optical homodyne detection. We quantify the information gain in a single-shot measurement and show that the photon number statistics can be recovered in repeated measurements on an ensemble of identical input states without scanning the phase of the input state or randomizing the phase of the local oscillator used in homodyne detection. We demonstrate how the expectation maximization algorithm and Bayesian inference can be utilized to facilitate the reconstruction and illustrate our approach by conducting experiments to study the photon number distributions of a weak coherent state and a thermal state source.

We demonstrate a quadrature phase-shifted optical demodulation scheme for low-coherence fiber-optic Fabry-Perot interferometric sensors. The main part of the demodulator is a fiber-optic Mach-Zehnder interferometer (MZI) constructed with a 1 × 2 fiber coupler, a 3 × 3 fiber coupler, and fiber delay lines. This configuration allows us to generate quadrature phase-shifted interference signals simultaneously, thus eliminating the problem of ambiguous phase discrimination. The path length difference of the MZI is adjustable to adapt to sensors with arbitrary gaps. A great phase stability of the MZI has been obtained by using identical optical components in its two optical paths. The demodulator has been applied to a fiber-optic vibrometer. Measurement of vibrations with amplitudes from 0.67 nm to 12.3 µm has been demonstrated.

In this paper, an aberration correction method for an extended target is proposed to solve the problem of the lenslet-based plenoptic camera not imaging clearly under the influence of aberrations. We propose a light field manipulation method to improve performance of the light field imaging system. The principle of this method is that the sub-aperture images extracted from the raw light field image are offset when the light field imaging system is affected by aberrations, and the symmetrical arrangement of the sub-aperture image array is destroyed. By repairing the symmetrical arrangement of the sub-aperture image array, the influence of phase aberrations on the imaging system can be eliminated, and the resolution of the plenoptic camera can be improved. We use an image correlation algorithm to process the sub-aperture images of the plenoptic camera, calculate and compensate each sub-aperture image's displacement caused by aberrations, and restore the symmetrical arrangement of the sub-aperture image array; then, a corrected high-resolution refocused image can be generated. In particular, this method uses only the raw light field information obtained by the plenoptic camera in a single exposure, without adding other hardware devices. Furthermore, it takes the extended target itself as the reference image, so the ideal position need not be calibrated in advance. Also, the parallax information of the sub-aperture images is retained, and the method is simple and easy to use. Numerical simulation and experimental results show that the technology proposed in this paper can work well for high-resolution imaging of a plenoptic camera with phase aberrations. This method can be potentially applied to analyze lens aberration, media-induced image distortion such as water turbulence in underwater imaging, and atmospheric turbulence in remote imaging. It may have important application prospects in the fields of astronomical object detection, remote sensing, etc.

We demonstrate a method based on an ICL with tunable wavelength covering ethanol absorption peak, water absorption peak and a reference point around 3.345um to make a stand-off detection of ethanol vapor in the space. The detection model is established using the ratios of reference signal and detection signal at three target wavelengths, which help to eliminate the influence of laser power and the cross interference from water vapor in the space. The intrinsic error caused by detectors and optical elements have been corrected, and availability of this approach has been proved both in theory and in experiment.

The existing photonic switch matrices usually show the drawbacks of either a large footprint or high cross talk. Here, we propose a compact InGaAsP/InP rearrangeable nonblocking 4×4 photonic switch fabric based on 2×2 Mach-Zehnder interferometer (MZI) switch elements in a Benes architecture. Each switch element consists of two frustrated total internal reflection (TIR) couplers and TIR mirrors serving as 90° waveguide bends, forming the square layout configuration of the 2×2 MZI switches. We investigate the design parameters of the switch element and 4×4 photonic switch matrix by using FDTD and transfer matrix methods, respectively. Our analysis results show that the proposed device exhibits an ultracompact chip size of ∼340  μm×120  μm, the minimum cross talk of -23  dB in the 1.5∼1.6  μm wavelength range, the total insertion loss of ∼3.9  dB, the low electrical energy of ∼0.4  pJ/bit, and an operation speed up to 50 GHz. Experimentally, we can demonstrate the feasibility of fabricating 2×2 MZI switches and an operational low-loss trench-coupler. The enabling component of the 2×2 MZI switch can scale its pattern in the 2D directions. This as-formed compact 4×4 switch fabric can be potentially applied in large-scale InP-based photonic integrated circuits.

A phased sparse aperture system provides an economic solution to get high resolution images with less volume and weight. The crucial point of such systems is adaptive correction of piston, that is, a close-loop control aiming at stabilizing the optical path differences within a fraction of the wavelength. In this paper, we present an autonomous phasing approach using stochastic parallel gradient descent algorithm through optimization of image quality. The synthetic system can be phased by iteratively commanding piston actuators without any additional optics. Simulations are first performed to test the validity. Then experimental results based on a binocular telescope testbed are presented, showing that our proposed close-loop control of piston correction doesn't only work with both laser and white-light point sources, but also with an extended object.

A detailed assessment is carried out in relation to the influence of the uncertainties associated with the input auxiliary atmospheric state parameters on retrieving aerosol optical properties from high-spectral-resolution lidar (HSRL) observations. The study starts from a review of the main spectral structure of the Rayleigh backscattering followed by evaluating the temperature effects on a backscattering cross section of atmospheric molecules based on numerical simulation. It shows that the transmittance of the background interference filter should be taken into account, depending on the full width at half maximum, although overall temperature dependence is negligible. Based on the Taylor expansion of the Tenti S6 model, the systematic errors arising from input temperature and pressure profiles are analyzed. It is demonstrated that the atmospheric pressure profiles have limited effects on the inversion results of aerosol optical parameters, as the atmospheric pressure is usually quite stable. The relative errors of the aerosol backscatter coefficient mainly stem from temperature profile errors and highly depend on the aerosol concentration. Quantitatively, the aerosol backscatter coefficient error could be larger than 5% with a 3 K deviation of temperature when the backscatter ratio is larger than 1.1. The accuracy of aerosol extinction coefficient retrieval is affected not only by the error in temperature, but also by the error in temperature lapse rate; the retrieval accuracy is more sensitive to the latter than the former. Further analysis based on the sounding temperature data shows that the variation of the temperature inversion layer during the night could induce a bias larger than 0.04   km -1 on the aerosol extinction coefficient retrieval. Therefore, the time resolution of temperature measurement from sounding balloons twice per day is too low to obtain an accurate retrieval of the aerosol optical properties from the HSRL.

To establish optical links between an optical ground station (OGS) and a quantum experiment satellite, a method of acquisition for the Micius satellite is proposed in this paper and the acquisition technological specification of the OGS system is analyzed. An acquisition strategy for the OGS is designed to meet the requirements of the quantum experiments. A method is designed to point accurately at the quantum satellite and improve the absolute pointing precision. The results show that the correction accuracy is better than 5 μrad, the acquisition time is less than 5 s, and the acquisition probability is 100% so far.

Misalignment induced third-order coma with respect to misaligned parameters in TMA optical systems is derived by using Nodal Aberration Theory, which yields the compensation factors that can be used to accomplish coma compensation in both coaxial and off-axis misaligned TMA telescopes. By using the compensation factors, coma free point for the tertiary mirror in TMA telescopes is derived and proved to be the negative form of the one for the secondary mirror in the Cassegrain telescope. The compensation factors can also be used to design the off-axis TMAs due to their capability of eliminating the coma over the field of view.

Optical sparse aperture imaging shows great promise for the next generation of high resolution systems. In this paper, we propose and demonstrate an active sparse aperture imaging approach using independent transmitter modulation to digitally overcome phasing errors, correct aberrations, and further improve resolution. The reported imaging scheme consists of a general sparse aperture system and an active illumination unit, specifically an independent pattern projector. A series of raw images are captured with the projector scanned to illuminate the object. Based on the acquired data set, the improved incoherent Fourier ptychographic algorithm is utilized to reconstruct sparse aperture images with distortions removed and contrast enhanced. Furthermore, thanks to illumination pattern modulation, higher resolution beyond the diffraction limit of the synthetic aperture system is gained as a benefit. Good-quality and higher-resolution sparse aperture imagery obtained by employing our proposed technique in both simulation and experiment demonstrates the effectiveness. The reported approach may provide new insights to address the phasing and image restoration problems of sparse aperture systems in the transmitting path rather than only in the receiving path.

A multiple spectra oriented similarity metric, referred to as n-dimensional solid spectral angle (NSSA), is addressed in this study. NSSA extends the traditional spectral angle metric (SAM)-calculating two spectra's angle-to the calculation of the high-dimensional solid angle jointly constituted by a set of spectra with any number of bands. Some significant inherent properties of NSSA are also discussed. Furthermore, as a merit of NSSA, an NSSA-based band add-on (BAO-NSSA) band selection method is derived, which displays an advantage in capturing spectra absorption features-particularly for similar classes-by operating a set of spectra instead of distinct band variables. Finally, an annular architecture in contrast with hierarchical architecture is presented by embedding the idea of BAO-NSSA into the issue of multiple class identification. Comprehensive analyses were conducted on three real hyperspectral data sets with similar and distinct classes. The proposed approach is shown to be effective for eliminating redundant bands and improving the accuracy of spectra identification.

We demonstrate that multiple-site sensing along an optical fiber can be done with incoherent continuous-wave light. Using a broadband low-coherence noise source, a slow detector, and an optical modulator, we construct a single-arm frequency-shifted interferometer (SA-FSI) capable of simultaneously sensing multiple weak-reflection sites distributed either in parallel or in series along fiber links. By scanning the driving frequency of an electro-optic amplitude modulator in the range of 2.7-3.2 GHz at steps of 41.7 KHz, we demonstrate a spatial resolution of 0.3 m and a measurement range of over 1 km.

In this paper, we propose and demonstrate the synthetic aperture imaging by using spatial modulation diversity technology with stochastic parallel gradient descent (SPGD) algorithm. Instead of creating diversity images by means of focus adjustments, the technology, proposed in this paper, creates diversity images by modulating the transmittance of individual sub-aperture of multi-aperture system, respectively. Specifically, spatial modulation is realized by switching off the transmittance of each sub-aperture with electrical shutters, alternately. Based on these multi diversity images, SPGD algorithm is used for adaptively optimizing the coefficients of Zernike polynomials to reconstruct the real phase distortions of multi-aperture system and to restore the near-diffraction-limited image of object. Numerical simulation and experimental results show that this technology can be used for joint estimation of both pupil aberrations and an high resolution image of the object, successfully. The technology proposed in this paper can have wide applications in segmented and multi-aperture imaging systems.

We present and demonstrate a novel protocol for distributing secret keys between two and only two parties based on N-party single-qubit Quantum Secret Sharing (QSS). We demonstrate our new protocol with N = 3 parties using phase-encoded photons. We show that any two out of N parties can build a secret key based on partial information from each other and with collaboration from the remaining N - 2 parties. Our implementation allows for an accessible transition between N-party QSS and arbitrary two party QKD without modification of hardware. In addition, our approach significantly reduces the number of resources such as single photon detectors, lasers and dark fiber connections needed to implement QKD.

Sparse representation-based classification (SRC) has attracted increasing attention in remote-sensed hyperspectral communities for its competitive performance with available classification algorithms. Kernel sparse representation-based classification (KSRC) is a nonlinear extension of SRC, which makes pixels from different classes linearly separable. However, KSRC only considers projecting data from original space into feature space with a predefined parameter, without integrating a priori domain knowledge, such as the contribution from different spectral features. In this study, customizing kernel sparse representation-based classification (CKSRC) is proposed by incorporating kth nearest neighbor density as a weighting scheme in traditional kernels. Analyses were conducted on two publicly available data sets. In comparison with other classification algorithms, the proposed CKSRC further increases the overall classification accuracy and presents robust classification results with different selections of training samples.

The support vector machine (SVM) is a widely used approach for high-dimensional data classification. Traditionally, SVMs use features from the spectral bands of hyperspectral images with each feature contributing equally to the classification. In practical applications, although affected by noise, slight contributions can also be obtained from deteriorated bands. Thus, compared with feature reduction or equal assignment of weights to all the features, feature weighting is a trade-off choice. In this study, we examined two approaches to assigning weights to SVM features to increase the overall classification accuracy: (1) "CSC-SVM" refers to a support vector machine with compactness and a separation coefficient feature weighting algorithm, and (2) "SE-SVM" refers to a support vector machine with a similarity entropy feature weighting algorithm. Analyses were conducted on a public data set with nine selected land-cover classes. In comparison with traditional SVMs and other classical feature weighting algorithms, the proposed weighting algorithms increase the overall classification accuracy, and even better results could be obtained with few training samples.

Frequency-shifted interferometry has shown great potential in optical fiber sensor multiplexing. In this letter, we propose and demonstrate a frequency-shifted interferometer (FSI) based on sideband interference. Comparing with previous implementation of FSI based on a Sagnac interferometer, this scheme is much simpler and compact. By scanning the driving frequency of a LiNbO3 phase modulator in the range of 4.5-5.5 GHz, we demonstrate a spatial resolution of 0.1 m, which is 50 times better than the previously reported results.

A quantum random number generator (QRNG) can generate true randomness by exploiting the fundamental indeterminism of quantum mechanics. Most approaches to QRNG employ single-photon detection technologies and are limited in speed. Here, we experimentally demonstrate an ultrafast QRNG at a rate over 6 Gbits/s based on the quantum phase fluctuations of a laser operating near threshold. Moreover, we consider a potential adversary who has partial knowledge on the raw data and discuss how one can rigorously remove such partial knowledge with postprocessing. We quantify the quantum randomness through min-entropy by modeling our system and employ two randomness extractors--Trevisan's extractor and Toeplitz-hashing--to distill the randomness, which is information-theoretically provable. The simplicity and high-speed of our experimental setup show the feasibility of a robust, low-cost, high-speed QRNG.

Support vector machine (SVM) is widely used in classification of hyperspectral reflectance data. In traditional SVM, features are generated from all or subsets of spectral bands with each feature contributing equally to the classification. In classification of small hyperspectral reflectance data sets, a common challenge is Hughes phenomenon, which is caused by many redundant features and resulting in subsequent poor classification accuracy. In this study, we examined two approaches to assigning weights to SVM features to increase classification accuracy and reduce adverse effects of Hughes phenomenon: 1) "RSVM" refers to support vector machine with relief feature weighting algorithm, and 2) "FRSVM" refers to support vector machine with fuzzy relief feature weighting algorithm. We used standardized weights to extract a subset of features with high classification contribution. Analyses were conducted on a reflectance data set of individual corn kernels from three inbred lines and a public data set with three selected land-cover classes. Both weighting methods and reduction of features increased classification accuracy of traditional SVM and therefore reduced adverse effects of Hughes phenomenon.

We present a spatial-domain fiber cavity ring-down (CRD) technique that does not require optical pulses for time-resolved detection. Instead of measuring the intensity decay rate of an optical pulse in the time domain as in conventional CRD experiments, we measure the decay rate of a CW signal in a ring-down cavity (RDC) using frequency-shifted interferometry in the spatial domain, as a function of distance traveled by the light. As a proof-of-concept demonstration, we measured fiber bend loss in a loop RDC using this technique, and a cavity loss change as low as 0.0135 dB induced by every fiber turn on a mandrel was unambiguously discerned., (© 2011 Optical Society of America)

Photonic crystal nanobeam microcavities based on slot and hollow-core waveguides were proposed and analyzed. Three-dimensional finite-difference time-domain simulations show that both an ultrasmall modal volume (V) and a high quality (Q) factor can be obtained simultaneously in hollow-core-nanobeam mirocavities (HCNMs) due to the strong confinement of fields in the two lateral directions. For a 6.5-μm-long HCNM, the Q factor and V are on the order of 10⁵ and 10⁻²(λ/2n)³, respectively. With compactness, lower fabrication requirements as well as ultrahigh Q/V, the proposed microcavities would be very promising in a variety of applications.

We present a liquid level sensing system for cryogenic fluids based on an array of aluminum-coated fiber Bragg gratings written in high-attenuation fibers (HAFs) interrogated by frequency-shifted interferometry (FSI). The sensors are heated up optically through the absorption of light at the core of the HAF sections. The distinct thermal response of sensors in the liquid from that in the gas provides an unambiguous means to detect the liquid level. FSI allows the sensors to have overlapped spectral response, and, therefore, has the potential of accommodating a larger number of sensors in the array. The measurement of liquid nitrogen level using this system was experimentally demonstrated. The successful combination of aluminum-coated HAF Bragg grating sensors and the FSI technique promises a viable solution for liquid level sensor networks at cryogenic temperatures.

We present a high-speed random number generation scheme based on measuring the quantum phase noise of a single-mode laser operating at a low intensity level near the lasing threshold. A delayed self-heterodyning system has been developed to measure the random phase fluctuation. By actively stabilizing the phase of the interferometer, a random number generation rate of 500 Mbit/s has been demonstrated and the generated random numbers have passed all the DIEHARD tests.

We reported on an all-solid-state double Nd:YAG slab laser. The laser was based on two diode end-pumped Nd:YAG slabs and a stable-unstable hybrid resonator. A cw output of 189 W and an average Q-switched output of 169 W at 10 kHz with an M(2) factor of 1.5 in the slow direction and 1.7 in the fast direction were obtained. We demonstrated efficient near-field frequency doubling by imaging the one-dimensional top-hat near-field to a lithium triborate frequency doubler. We obtained 93 W green light at 10 kHz with a pulse width of 10.7 ns. The efficiency of second-harmonic generation was up to 57%.

We study the performance of a practical quantum cloning scheme consisting of a continuously pumped broadband optical amplifier followed by optimal spectral and temporal filters for spontaneous emission suppression. Our simulation results demonstrate that the fidelity of this system is no better than a random cloning machine when the average input photon number is below one, but asymptotically approaches the quantum limit of an optimal quantum cloning machine as the input photon number increases. We also show that this system has a better fidelity than cloning based on state estimation, though for a large number of clones both cloning methods asymptotically approach the quantum limit.

We propose a new quantum key distribution protocol in which information is encoded on continuous variables of a single photon. In this protocol, Alice randomly encodes her information on either the central frequency of a narrowband single-photon pulse or the time delay of a broadband single-photon pulse, while Bob randomly chooses to do either frequency measurement or time measurement. The security of this protocol rests on the energy-time uncertainty relation, which prevents Eve from simultaneously determining both frequency and time information with arbitrarily high resolution. Since no interferometer is employed in this scheme, it is more robust against various channel noises, such as polarization and phase fluctuations.

In this paper, we propose a polarization-insensitive phase modulation scheme based on frequency modulation of light waves using either one or a pair of acousto-optic modulators. A stable Sagnac quantum key distribution (QKD) system employing this technique is also proposed. The interference visibility for a 40km and a 10km fiber loop is 96% and 99% respectively, at single-photon level. We ran standard BB84 QKD protocol in a simplified Sagnac setup (40km fiber loop) continuously for one hour and the measured quantum bit error rate stayed within 2%-5% range.

We propose and experimentally demonstrate a single-mode fiber length and dispersion measurement system based on what we believe to be a novel frequency-shifted asymmetric Sagnac interferometer incorporating an acousto-optic modulator (AOM). By sweeping the driving frequency of the AOM, which is asymmetrically placed in the Sagnac loop, the optical length of the fiber can be determined by measuring the corresponding variation in the phase delay between the two counterpropagating light beams. Combined with a high-resolution data processing algorithm, this system yields a dynamic range from a few centimeters to 60 km (limited by our availability of long fibers) with a resolution of approximately 1 part per million for long fibers.

A self-compensating fiber optic flow sensor system based on the principle of broadband white-light interferometers and cantilever beam bending is described. The fiber optic sensor system uses two fiber ferrule sensors that are bonded on either side of a cantilever beam to measure the flow rate by monitoring the air-gap changes caused by the bending of the cantilever beam. Cross sensitivity of the temperature and pressure dependence of the sensor can be compensated for automatically. The prototype sensor system was constructed, laboratory characterized, and field tested. The results from the field testing have demonstrated high resolution, repeatability, and stability for on-line detection of the flow rates of fluids.

We previously described a fiber based Doppler optical coherence tomography system [1] capable of imaging embryo cardiac blood flow at 4~16 frames per second with wide velocity dynamic range [2]. Coupling this system to a linear scanning fiber optical catheter design that minimizes friction and vibrations, we report here the initial results of in vivo endoscopic Doppler optical coherence tomography (EDOCT) imaging in normal rat and human esophagus. Microvascular flow in blood vessels less than 100 microm diameter was detected using a combination of color-Doppler and velocity variance imaging modes, during clinical endoscopy using a mobile EDOCT system.

We previously reported a Doppler optical coherence tomography (DOCT) system design [1] for high-speed imaging with wide velocity dynamic range (up to 28.5 dB when acquiring 8 frames per second), operating at 1.3 m with a coherence length of 13.5 m. Using a developmental biology model (Xenopus laevis), here we test the DOCT system's ability to image cardiac dynamics in an embryo in vivo, with a simple hand-held scanner at 4 ~ 16 frames per second. In particular, we show that high fidelity DOCT movies can be obtained by increasing the reference arm scanning rate (~8 kHz). Utilizing a combination of four display modes (B-mode, color-Doppler, velocity variance, and Doppler spectrum), we show that DOCT can detect changes in velocity distribution during heart cycles, measure the velocity gradient in the embryo, and distinguish blood flow Doppler signal from heart wall motions.

Improvements in real-time Doppler optical coherence tomography (DOCT), acquiring up to 32 frames per second at 250 x 512 pixels per image, are reported using signal processing techniques commonly employed in Doppler ultrasound imaging. The ability to measure a wide range of flow velocities, ranging from less than 20 microm/s to more than 10 cm/s, is demonstrated using an 1.3 microm DOCT system with flow phantoms in steady and pulsatile flow conditions. Based on full implementation of a coherent demodulator, four different modes of flow visualization are demonstrated: color Doppler, velocity variance, Doppler spectrum, and power Doppler. The performance of the former two, which are computationally suitable for real-time imaging, are analyzed in detail under various signal-to-noise and frame-rate conditions. The results serve as a guideline for choosing appropriate imaging parameters for detecting in vivo blood flow.