Heterogeneous sapphire-supported low-loss photonic platform.

Sapphire is a promising wideband substrate material for visible photonics. It is a common growth substrate for III-nitride light-emitting diodes and laser structures. Doped sapphires are important gain media foundational to the development of titanium-sapphire and ruby lasers. For lasers operating at visible and near-infrared wavelengths, a photonic platform that minimizes loss while maximizing gain material overlap is crucial. Here, we introduce a novel low-loss waveguiding strategy that establishes high-performance integrated photonics on sapphire substrates. This platform achieves a high intrinsic quality factor of 5.6 million near 780 nm and features direct compatibility with a range of solid-state laser gain media.

Conjugation with glucagon like peptide-1 enables targeted protein degradation.

Lysosome-targeting chimeras (LYTACs) have emerged as a promising technique to extend the scope of targeted protein degradation to extracellular proteins, e.g., secreted proteins and membrane-anchored proteins. However, up to now, only a small number of lysosomal targeting receptors (LTRs), such as cation-independent mannose 6-phosphate receptor (CI-M6PR) and asialoglycoprotein receptor (ASGPR), were reported to build LYTACs for degradation of extracellular proteins. Therefore, it is important to explore more functionalized ligands for the relevant LTRs to expand the LYTAC framework. Herein, we demonstrate a new LTR ligand-glucagon like peptide 1 (GLP-1) based targeted degradation platform, termed GLP-1 receptor-targeting chimeras (GLP-1-LYTAC). GLP-1-LYTACs are formed by conjugating GLP-1 with targeted binder (such as antibody) through Click Chemistry, showing efficiently lysosomal degradation of both extracellular proteins (GFP and Neutravidin) as well as cell membrane proteins (EGFR and PD-L1). We believe that this novel GLP-1-LYTAC will open up a new dimension for targeted protein breakdown.

Adiabatic Frequency Conversion Using a Time-Varying Epsilon-Near-Zero Metasurface.

A time-dependent change in the refractive index of a material leads to a change in the frequency of an optical beam passing through that medium. Here, we experimentally demonstrate that this effect-known as adiabatic frequency conversion (AFC)-can be significantly enhanced by a nonlinear epsilon-near-zero-based (ENZ-based) plasmonic metasurface. Specifically, by using a 63-nm-thick metasurface, we demonstrate a large, tunable, and broadband frequency shift of up to ∼11.2 THz with a pump intensity of 4 GW/cm2. Our results represent a decrease of ∼10 times in device thickness and 120 times in pump peak intensity compared with the cases of bare, thicker ENZ materials for the similar amount of frequency shift. Our findings might potentially provide insights for designing efficient time-varying metasurfaces for the manipulation of ultrafast pulses.

Experimental demonstration of superresolution of partially coherent light sources using parity sorting: erratum.

The authors include references that appeared on arXiv during the preparation of their paper [Opt. Express29, 22034 (2021)10.1364/OE.427734].

Confocal super-resolution microscopy based on a spatial mode sorter.

Spatial resolution is one of the most important specifications of an imaging system. Recent results in the quantum parameter estimation theory reveal that an arbitrarily small distance between two incoherent point sources can always be efficiently determined through the use of a spatial mode sorter. However, extending this procedure to a general object consisting of many incoherent point sources remains challenging, due to the intrinsic complexity of multi-parameter estimation problems. Here, we generalize the Richardson-Lucy (RL) deconvolution algorithm to address this challenge. We simulate its application to an incoherent confocal microscope, with a Zernike spatial mode sorter replacing the pinhole used in a conventional confocal microscope. We test different spatially incoherent objects of arbitrary geometry, and we find that the resolution enhancement of sorter-based microscopy is on average over 30% higher than that of a conventional confocal microscope using the standard RL deconvolution algorithm. Our method could potentially be used in diverse applications such as fluorescence microscopy and astronomical imaging.

Experimental demonstration of superresolution of partially coherent light sources using parity sorting.

Analyses based on quantum metrology have shown that the ability to localize the positions of two incoherent point sources can be significantly enhanced over direct imaging through the use of mode sorting. Here we theoretically and experimentally investigate the effect of partial coherence on the sub-diffraction limit localization of two sources based on parity sorting. With the prior information of a negative and real-valued degree of coherence, higher Fisher information is obtained than that for the incoherent case. Our results pave the way to clarifying the role of coherence in quantum-limited metrology.

Tunable Doppler shift using a time-varying epsilon-near-zero thin film near 1550 nm.

We experimentally investigate the tunable Doppler shift in an 80 nm thick indium-tin-oxide (ITO) film at its epsilon-near-zero (ENZ) region. Under strong and pulsed excitation, ITO exhibits a time-varying change in the refractive index. A maximum frequency redshift of 1.8 THz is observed in the reflected light when the pump light has a peak intensity of ∼140GW/cm2 and a pulse duration of ∼580fs, at an incident angle of 40°. The frequency shift increases with the increase in pump intensity and saturates at the intensity of ∼140GW/cm2. When the pump pulse duration increases from ∼580fs to ∼1380fs, the maximum attainable frequency shift decreases from 1.8 THz to 0.7 THz. In addition, the pump energy required to saturate the frequency shift decreases with the increase in pump pulse duration for ∼x<1ps and remains unchanged for ∼x>1ps durations. Tunability exists among the pump pulse energy, duration, and incident angle for the Doppler shift of the ITO-ENZ material, which can be employed to design efficient frequency shifters for telecom applications.

Direct Tomography of High-Dimensional Density Matrices for General Quantum States of Photons.

Quantum-state tomography is the conventional method used to characterize density matrices for general quantum states. However, the data acquisition time generally scales linearly with the dimension of the Hilbert space, hindering the possibility of dynamic monitoring of a high-dimensional quantum system. Here, we demonstrate a direct tomography protocol to measure density matrices of photons in the position basis through the use of a polarization-resolving camera, where the dimension of density matrices can be as large as 580×580 in our experiment. The use of the polarization-resolving camera enables parallel measurements in the position and polarization basis and as a result, the data acquisition time of our protocol does not increase with the dimension of the Hilbert space and is solely determined by the camera exposure time (on the order of 10 ms). Our method is potentially useful for the real-time monitoring of the dynamics of quantum states and paves the way for the development of high-dimensional, time-efficient quantum metrology techniques.

Performance of real-time adaptive optics compensation in a turbulent channel with high-dimensional spatial-mode encoding.

The orbital angular momentum (OAM) of photons is a promising degree of freedom for high-dimensional quantum key distribution (QKD). However, effectively mitigating the adverse effects of atmospheric turbulence is a persistent challenge in OAM QKD systems operating over free-space communication channels. In contrast to previous works focusing on correcting static simulated turbulence, we investigate the performance of OAM QKD in real atmospheric turbulence with real-time adaptive optics (AO) correction. We show that even though our AO system provides a limited correction, it is possible to mitigate the errors induced by weak turbulence and establish a secure channel. The crosstalk induced by turbulence and the performance of AO systems is investigated in two configurations: a lab-scale link with controllable turbulence, and a 340 m long cross-campus link with dynamic atmospheric turbulence. Our experimental results suggest that an advanced AO system with fine beam tracking, reliable beam stabilization, precise wavefront sensing, and accurate wavefront correction is necessary to adequately correct turbulence-induced error. We also propose and demonstrate different solutions to improve the performance of OAM QKD with turbulence, which could enable the possibility of OAM encoding in strong turbulence.

Simultaneous turbulence mitigation and channel demultiplexing for two 100 Gbit/s orbital-angular-momentum multiplexed beams by adaptive wavefront shaping and diffusing.

We experimentally demonstrate simultaneous turbulence mitigation and channel demultiplexing in a 200 Gbit/s orbital-angular-momentum (OAM) multiplexed link by adaptive wavefront shaping and diffusing (WSD) the light beams. Different realizations of two emulated turbulence strengths (the Fried parameter ${r_0} = 0.4,\,1.0\;{\rm mm}$r0=0.4,1.0mm) are mitigated. The experimental results show the following. (1) Crosstalk between OAM $l = + 1$l=+1 and $l = - 1$l=-1 modes can be reduced by $ {\gt} {10.0}$>10.0 and $ {\gt} {5.8}\;{\rm dB}$>5.8dB, respectively, under the weaker turbulence (${r_0} = 1.0\;{\rm mm}$r0=1.0mm); crosstalk is further improved by $ {\gt} {17.7}$>17.7 and $ {\gt} {19.4}\;{\rm dB}$>19.4dB, respectively, under most realizations in the stronger turbulence (${r_0} = 0.4\;{\rm mm}$r0=0.4mm). (2) The optical signal-to-noise ratio penalties for the bit error rate performance are measured to be ${\sim}{0.7}$∼0.7 and ${\sim}{1.6}\;{\rm dB}$∼1.6dB under weaker turbulence, while measured to be ${\sim}{3.2}$∼3.2 and ${\sim}{1.8}\;{\rm dB}$∼1.8dB under stronger turbulence for OAM $l = + 1$l=+1 and $l = - 1$l=-1 mode, respectively.

Using all transverse degrees of freedom in quantum communications based on a generic mode sorter.

The dimension of the state space for information encoding offered by the transverse structure of light is usually limited by the finite size of apertures. The widely used orbital angular momentum (OAM) number of Laguerre-Gaussian (LG) modes in free-space communications cannot achieve the theoretical maximum transmission capacity unless the radial degree of freedom is multiplexed into the protocol. While the methodology to sort the radial quantum number has been developed, the application of radial modes in quantum communications requires an additional ability to efficiently measure the superposition of LG modes in the mutually unbiased basis. Here we develop and implement a generic mode sorter that is capable of sorting the superposition of LG modes through the use of a mode converter. As a consequence, we demonstrate an 8-dimensional quantum key distribution experiment involving all three transverse degrees of freedom: spin, azimuthal, and radial quantum numbers of photons. Our protocol presents an important step towards the goal of reaching the capacity limit of a free-space link and can be useful to other applications that involve spatial modes of photons.

Flow Measurement of Oil-Water Two-Phase Flow at Low Flow Rate Using the Plug-in Conductance Sensor Array.

In order to improve the flow measurement accuracy of oil-water two-phase flow at low flow rate, this paper presents a plug-in conductance sensor array (PICSA) for the measurement of water holdup and cross-correlation velocity. Due to the existence of the insert body in PICSA, the effect of slippage and the non-uniform distribution of dispersed phase on the measurement of oil-water two-phase flow at low flow rate can be reduced. The finite element method is used to analyze the electric field distribution characteristics of the plug-in conductance sensor, and the sensor geometry is optimized. The dynamic experiment of oil-water two-phase flow is carried out where water cut Kw and mixture velocity Um are set in the range of 10-98% and 0.0184-0.2580 m/s respectively. Experimental results show that the PICSA has good resolution in water holdup measurement for dispersed oil-in-water slug flow (D OS/W), transition flow (TF), dispersed oil-in-water bubble flow (D O/W) and very fine dispersed oil-in-water bubble flow (VFD O/W). In addition, the cross-correlation velocity of the oil-water two-phase flow is obtained by using the plug-in upstream and downstream conductance sensor arrays. The relationship between the cross-correlation velocity and mixture velocity is found to be sensitive to the change of flow pattern, but it has a good linear relationship under the same flow pattern. Based on the flow pattern identification, a good prediction result of the mixture velocity is obtained using kinematic wave theory. Finally, a high precision prediction of the individual phase volume fraction of oil-water two-phase flow at low flow rate is achieved by using the drift flux model.

Realization of a scalable Laguerre-Gaussian mode sorter based on a robust radial mode sorter.

The transverse structure of light is recognized as a resource that can be used to encode information onto photons and has been shown to be useful to enhance communication capacity as well as resolve point sources in superresolution imaging. The Laguerre-Gaussian (LG) modes form a complete and orthonormal basis set and are described by a radial index p and an orbital angular momentum (OAM) index ℓ. Earlier works have shown how to build a sorter for the radial index p or/and the OAM index ℓ of LG modes, but a scalable and dedicated LG mode sorter which simultaneous determinate p and ℓ is immature. Here we propose and experimentally demonstrate a scheme to accomplish complete LG mode sorting, which consists of a novel, robust radial mode sorter that can be used to couple radial modes to polarizations, an ℓ-dependent phase shifter and an OAM mode sorter. Our scheme is in principle efficient, scalable, and crosstalk-free, and therefore has potential for applications in optical communications, quantum information technology, superresolution imaging, and fiber optics.

Hermite-Gaussian mode sorter.

The Hermite-Gaussian (HG) modes, sometimes referred to as transverse electromagnetic modes in free space, form a complete and orthonormal basis that have been extensively used to describe optical fields. In addition, these modes have been shown to be helpful in enhancing information capacity of optical communications as well as achieving super-resolution imaging in microscopy. Here we propose and present the realization of an efficient, robust mode sorter that can sort a large number of HG modes based on the relation between HG modes and Laguerre-Gaussian (LG) modes. We experimentally demonstrate the sorting of 16 HG modes, and our method can be readily extended to a higher-dimensional state space in a straightforward manner. We expect that our demonstration will have direct applications in a variety of fields including fiber optics, classical and quantum communications, as well as super-resolution imaging.

Sorting Photons by Radial Quantum Number.

The Laguerre-Gaussian (LG) modes constitute a complete basis set for representing the transverse structure of a paraxial photon field in free space. Earlier workers have shown how to construct a device for sorting a photon according to its azimuthal LG mode index, which describes the orbital angular momentum (OAM) carried by the field. In this paper we propose and demonstrate a mode sorter based on the fractional Fourier transform to efficiently decompose the optical field according to its radial profile. We experimentally characterize the performance of our implementation by separating individual radial modes as well as superposition states. The reported scheme can, in principle, achieve unit efficiency and thus can be suitable for applications that involve quantum states of light. This approach can be readily combined with existing OAM mode sorters to provide a complete characterization of the transverse profile of the optical field.

Improved time-of-flight range acquisition technique in underwater lidar experiments.

This paper presents an underwater lidar time-of-flight ranging system that combines the variable forgivable factor recursive least-squares (VFF-RLS) adaptive filter algorithm and the constant fraction discriminator (CFD) timing technology. The effectiveness of suppressing the backscattering and increasing timing accuracy is experimentally verified in the water basin under the different target distances, especially near the detection limit. The classical RLS is creatively transformed by introducing the VFF, which is highly correlated to the target echo at any distance. The improvement of the signal-to-backscatter ratio always exceeds 18.9 dB. The Monte Carlo simulation proves the applicability of the proposed method in the media of different turbidity. The influences of the selective timing methods on the walk error and time jitter are compared, and the optimum zero point of CFD is achieved by the slope analysis of leading (falling) edge in experimental target pulses.

Labeled RFS-Based Track-Before-Detect for Multiple Maneuvering Targets in the Infrared Focal Plane Array.

The problem of jointly detecting and tracking multiple targets from the raw observations of an infrared focal plane array is a challenging task, especially for the case with uncertain target dynamics. In this paper a multi-model labeled multi-Bernoulli (MM-LMB) track-before-detect method is proposed within the labeled random finite sets (RFS) framework. The proposed track-before-detect method consists of two parts-MM-LMB filter and MM-LMB smoother. For the MM-LMB filter, original LMB filter is applied to track-before-detect based on target and measurement models, and is integrated with the interacting multiple models (IMM) approach to accommodate the uncertainty of target dynamics. For the MM-LMB smoother, taking advantage of the track labels and posterior model transition probability, the single-model single-target smoother is extended to a multi-model multi-target smoother. A Sequential Monte Carlo approach is also presented to implement the proposed method. Simulation results show the proposed method can effectively achieve tracking continuity for multiple maneuvering targets. In addition, compared with the forward filtering alone, our method is more robust due to its combination of forward filtering and backward smoothing.

Covariance-based direction-of-arrival estimation of wideband coherent chirp signals via sparse representation.

This paper addresses the problem of direction-of-arrival (DOA) estimation of multiple wideband coherent chirp signals, and a new method is proposed. The new method is based on signal component analysis of the array output covariance, instead of the complicated time-frequency analysis used in previous literatures, and thus is more compact and effectively avoids possible signal energy loss during the hyper-processes. Moreover, the a priori information of signal number is no longer a necessity for DOA estimation in the new method. Simulation results demonstrate the performance superiority of the new method over previous ones.

Semi-blind signal extraction for communication signals by combining independent component analysis and spatial constraints.

Signal of interest (SOI) extraction is a vital issue in communication signal processing. In this paper, we propose two novel iterative algorithms for extracting SOIs from instantaneous mixtures, which explores the spatial constraint corresponding to the Directions of Arrival (DOAs) of the SOIs as a priori information into the constrained Independent Component Analysis (cICA) framework. The first algorithm utilizes the spatial constraint to form a new constrained optimization problem under the previous cICA framework which requires various user parameters, i.e., Lagrange parameter and threshold measuring the accuracy degree of the spatial constraint, while the second algorithm incorporates the spatial constraints to select specific initialization of extracting vectors. The major difference between the two novel algorithms is that the former incorporates the prior information into the learning process of the iterative algorithm and the latter utilizes the prior information to select the specific initialization vector. Therefore, no extra parameters are necessary in the learning process, which makes the algorithm simpler and more reliable and helps to improve the speed of extraction. Meanwhile, the convergence condition for the spatial constraints is analyzed. Compared with the conventional techniques, i.e., MVDR, numerical simulation results demonstrate the effectiveness, robustness and higher performance of the proposed algorithms.

Direction-of-arrival estimation based on joint sparsity.

We present a DOA estimation algorithm, called Joint-Sparse DOA to address the problem of direction-of-arrival (DOA) estimation using sensor arrays. Firstly, DOA estimation is cast as the joint-sparse recovery problem. Then, norm is approximated by an arctan function to represent joint sparsity and DOA estimation can be obtained by minimizing the approximate norm. Finally, the minimization problem is solved by a quasi-Newton method to estimate DOA. Simulation results show that our algorithm has some advantages over most existing methods: it needs a small number of snapshots to estimate DOA, while the number of sources need not be known a priori. Besides, it improves the resolution, and it can also handle the coherent sources well.