High-peak-power long-wave infrared BaGa4Se7 optical parametric oscillator with 6.7-13.9†µm widely tunable range.

A high-peak-power, widely tunable range long-wave infrared optical parametric oscillator (OPO) based on the BaGa4Se7 (BGSe) crystal is demonstrated in this Letter. Pumped by a 1064 nm Nd:YAG laser, a high-peak-power of 0.15 MW was achieved at 9.8 µm with a pulse width of 5.0 ns. At 11.0 µm, a high beam quality of M2x = 4.1 and M2y = 3.3 was achieved. By rotating the BGSe crystal, a broad tuning range of 6.7-13.9 µm was realized. Furthermore, a theoretical analysis was conducted to elucidate the reasons behind the improvement in beam quality in the x-direction as the wavelength of the idler wave increases.

Speckle visual cryptography for credential authentication.

Based on the high random distribution characteristic of the natural speckle image, a new method of speckle visual cryptography, to the best of our knowledge, is designed by combining the natural speckle image with the secret key in visual cryptography. Specifically, we designed an authentication system for user credentials by combining speckle visual cryptography and the QR code. By using the speckle visual cryptography method, the image of the QR code carrying user authentication information is hidden in the speckle image, and the speckle image is printed on the paper credentials. Through a simulation and analog experiments, we verify the possibility of applying speckle visual cryptography to a user credentials authentication system, compare the improved grayscale reordering algorithm and grayscale reordering algorithm, and prove that the improved grayscale reordering algorithm has more advantages in this system by comparing the PSNR and SSIM. Finally, the y-interference ability and the uniqueness of the virtual secret key in the system are analyzed to prove that the secret key has high anti-interference ability and security.

Optical information hiding for different surface images.

Optical hiding often requires the selection of specific artificial optical components as carriers, which results in poor versatility of the carriers and high costs for the hiding system. To conceal secret information on different surfaces such as metal, wood, and paper, we propose an optical information hiding method. In this method, we use images of surfaces, whose grayscale histograms have the characteristic of symmetric distribution. Based on this characteristic, we first scramble the surface image, and then adjust part of the gray value of the surface image to the complementary value to embed the secret information into a scrambled surface image to generate a key image. In the extraction process, a projector is used to reproduce the scrambled surface image and the key image, which are then incoherently superimposed to extract the secret information using the human visual system. The extraction process does not require complex optical knowledge and is simple and feasible. Simulation experiments and optical experiments indicate that this method is applicable in practice and possesses good security and imperceptibility. Furthermore, we prove the reliability of this method by embedding secret information in different surface images, demonstrating the potential application of more surface images in the field of optical information hiding. Finally, we discuss the applicability of surface information images and analyze the imperceptibility of key images.

Highly efficient and aberration-free off-plane grating spectrometer and monochromator for EUV-soft X-ray applications.

We demonstrate a novel flat-field, dual-optic imaging EUV-soft X-ray spectrometer and monochromator that attains an unprecedented throughput efficiency exceeding 60% by design, along with a superb spectral resolution of λ/Δλ > 200 accomplished without employing variable line spacing gratings. Exploiting the benefits of the conical diffraction geometry, the optical system is globally optimized in multidimensional parameter space to guarantee optimal imaging performance over a broad spectral range while maintaining circular and elliptical polarization states at the first, second, and third diffraction orders. Moreover, our analysis indicates minimal temporal dispersion, with pulse broadening confined within 80 fs tail-to-tail and an FWHM value of 29 fs, which enables ultrafast spectroscopic and pump-probe studies with femtosecond accuracy. Furthermore, the spectrometer can be effortlessly transformed into a monochromator spanning the EUV-soft X-ray spectral region using a single grating with an aberration-free spatial profile. Such capability allows coherent diffractive imaging applications to be conducted with highly monochromatic light in a broad spectral range and extended to the soft X-ray region with minimal photon loss, thus facilitating state-of-the-art imaging of intricate nano- and bio-systems, with a significantly enhanced spatiotemporal resolution, down to the nanometer-femtosecond level.

Simulation-driven machine learning approach for high-speed correction of slope-dependent error in coherence scanning interferometry.

Slope-dependent error often occurs in the coherence scanning interferometry (CSI) measurement of functional engineering surfaces with complex geometries. Previous studies have shown that these errors can be corrected through the characterization and phase inversion of the instrument's three-dimensional (3D) surface transfer function. However, since CSI instrument is usually not completely shift-invariant, the 3D surface transfer function characterization and correction must be repeated for different regions of the full field of view, resulting in a long computational process and a reduction of measurement efficiency. In this work, we introduce a machine learning approach based on a deep neural network that is trainable for slope-dependent error correction in CSI. Our method leverages a deep neural network to directly learn errors characteristics from simulated surface measurements provided by a previously validated physics-based virtual CSI method. The experimental results demonstrate that the trained network is capable of correcting the surface height map with 1024 × 1024 sampling points within 0.1 seconds, covering a 178 µm field of view. The accuracy is comparable to the previous phase inversion approach while the new method is two orders of magnitude faster under the same computational condition.

Surpassing the limitation of a coherence length in lidar by digital coherence.

In this manuscript, we propose a digital coherent detection method to surpass the limitation of a coherent length on the detection range of a coherent lidar. This method rapidly reconstructs the laser phase noise utilizing the multi-channel delay self-homodyne and the generalized inverse of the system observation matrix. Subsequently, the reconstructed phase noise is utilized to expunge its perturbation onto the target information in the digital domain, thereby effectively surmounting the coherence length limitation. Through experimentation, the proposed method is verified to produce stable and high-quality interference even when the optical path difference between two beams exceeds 1000 times the coherence length. Additionally, the equivalent laser linewidth is compressed by 105 times.

Adaptive Global Power-of-Two Ternary Quantization Algorithm Based on Unfixed Boundary Thresholds.

In the field of edge computing, quantizing convolutional neural networks (CNNs) using extremely low bit widths can significantly alleviate the associated storage and computational burdens in embedded hardware, thereby improving computational efficiency. However, such quantization also presents a challenge related to substantial decreases in detection accuracy. This paper proposes an innovative method, called Adaptive Global Power-of-Two Ternary Quantization Based on Unfixed Boundary Thresholds (APTQ). APTQ achieves adaptive quantization by quantizing each filter into two binary subfilters represented as power-of-two values, thereby addressing the accuracy degradation caused by a lack of expression ability of low-bit-width weight values and the contradiction between fixed quantization boundaries and the uneven actual weight distribution. It effectively reduces the accuracy loss while at the same time presenting strong hardware-friendly characteristics because of the power-of-two quantization. This paper extends the APTQ algorithm to propose the APQ quantization algorithm, which can adapt to arbitrary quantization bit widths. Furthermore, this paper designs dedicated edge deployment convolutional computation modules for the obtained quantized models. Through quantization comparison experiments with multiple commonly used CNN models utilized on the CIFAR10, CIFAR100, and Mini-ImageNet data sets, it is verified that the APTQ and APQ algorithms possess better accuracy performance than most state-of-the-art quantization algorithms and can achieve results with very low accuracy loss in certain CNNs (e.g., the accuracy loss of the APTQ ternary ResNet-56 model on CIFAR10 is 0.13%). The dedicated convolutional computation modules enable the corresponding quantized models to occupy fewer on-chip hardware resources in edge chips, thereby effectively improving computational efficiency. This adaptive CNN quantization method, combined with the power-of-two quantization results, strikes a balance between the quantization accuracy performance and deployment efficiency in embedded hardware. As such, valuable insights for the industrial edge computing domain can be gained.

Flexible and efficient fabrication of a terahertz absorber by single-step laser direct writing.

Laser direct writing (LDW) is a promising candidate for the fabrication of all-dielectric THz absorbers for its high flexibility and material compatibility. However, multi-step processing or multi-layer materials are required to compensate for the nonideal features of LDW to realize good absorption performance. To further explore the potential of LDW in flexible and cost-effective THz absorber fabrication, in this work, we demonstrate a design method of THz absorbers fully considering and utilizing the characteristics of laser processing. Specifically, we first numerically analyze that by properly combining basic structures processed by single-step LDW, good and adjustable absorption performance can be achieved on a single-layer substrate. Then we experimentally fabricate THz absorbers by processing periodic composite structures, which are combined by grooves and circular holes, on single-layer doped silicon using LDW. Experimental results show that our method can fabricate THz absorbers at a speed of 3.3 mm2/min with an absorptivity above 90% over a broadband of 1.8-3 THz. Our method provides a promising solution for the flexible and efficient fabrication of all-dielectric broadband THz absorbers.

Spatiotemporal coherent modulation imaging for dynamic quantitative phase and amplitude microscopy.

The single-shot capability of coherent modulation imaging (CMI) makes it have great potential in the investigation of dynamic processes. Its main disadvantage is the relatively low signal-to-noise ratio (SNR) which affects the spatial resolution and reconstruction accuracy. Here, we propose the improvement of a general spatiotemporal CMI method for imaging of dynamic processes. By making use of the redundant information in time-series reconstructions, the spatiotemporal CMI can achieve robust and fast reconstruction with higher SNR and spatial resolution. The method is validated by numerical simulations and optical experiments. We combine the CMI module with an optical microscope to achieve quantitative phase and amplitude reconstruction of dynamic biological processes. With the reconstructed complex field, we also demonstrate the 3D digital refocusing ability of the CMI microscope. With further development, we expect the spatiotemporal CMI method can be applied to study a range of dynamic phenomena.

Squint-looking differential synthetic aperture ladar: signal processing and experimental demonstration.

Squint-looking differential synthetic aperture ladar (DSAL) is reported with detailed signal processing mathematics and high-resolution experimental demonstrations. Based on the DSAL principle and standard squint-looking synthetic aperture radar theory, the data processing procedures on squint-looking DSAL image formation are obtained. The experimental DSAL setup, operating in "step-stop" strip map mode, adopts a frequency chirped laser with a wavelength of 1550 nm as the illuminating source and a specially designed random phase generator to introduce large common mode random phase error (RPE) into the phase history data of both receiving sub-apertures. High-resolution DSAL images of a cooperative target at a distance of 1.85 m and squint-looking angle of $-{10}^\circ$-10∘ or $+{10}^\circ$+10∘ are demonstrated. The DSAL images, with or without large RPE, are all well focused by straightforwardly following the given data processing steps. The result illustrates that the DSAL technique is robust in removing common mode phase errors in squint-looking configuration.