Co-phasing of the James Webb Space Telescope-like space segmented telescope by neural network wavefront reconstruction.

High-precision piston detection over a large range is the key to the phasing of segmented optical systems. In this paper, a large-range piston error detection method based on an artificial neural network is proposed. By establishing a compound attention mechanism and introducing a multilayer perceptron convolution layer, the network can quickly and accurately learn the key features of high-throughput light-intensity images of dispersed fringe patterns and narrowband far-field spot patterns during training, thereby accurately mapping grayscale images to multi-piston error values.

Large sparse aperture telescope wavefront sensing and control via pretrained neural network with attention module.

The ability to detect pistons with high accuracy over a wide range is paramount to the co-phasing of sparse aperture optical systems. This paper proposes a global piston error modulation method for sparse aperture mirrors based on convolutional neural networks. The efficacy of this approach is demonstrated by the introduction of a convolutional block attention module (CBAM) with a data generalization mechanism, which facilitates the rapid and accurate learning of key features from actual co-phasing sensor images.

Improved all photonics diffraction neural network based on multi-channel integrated optical fibers.

AI's exponentially growing computational demands conflict with slow hardware advances. The high-power consumption and long training times of large-scale models call for alternative solutions. Optical computing-based traditional optical networks and diffractive deep neural network (DNN) still face deployment challenges and reliance on electronic networks.

Semi-Kinematic Coupling Design and Analysis for Giant Steerable Science Mirror Prototype of Thirty Meter Telescope.

The Giant Steerable Science Mirror prototype is being developed to assess the tertiary mirror system of the Thirty Meter Telescope. In this study, a new semi-kinematic coupling design is proposed for the prototype based on three pairs of V-grooves and canoe-like components to allow for high repeatability accuracy under heavy loads. A mathematical model was constructed to estimate the repeatability accuracy using the corresponding measurement results and machining errors.

Opto-Electronic Hybrid Network Based on Scattering Layers.

Owing to the disparity between the computing power and hardware development in electronic neural networks, optical diffraction networks have emerged as crucial technologies for various applications, including target recognition, because of their high speed, low power consumption, and large bandwidth. However, traditional optical diffraction networks and electronic neural networks are limited by long training durations and hardware requirements for complex applications. To overcome these constraints, this paper proposes an innovative opto-electronic hybrid system that combines optical diffraction networks with electronic neural networks.

Photonics Scanning Pentaprism System for the Integrated Inspection of Large-Aperture Telescopes.

To improve their spatial resolution and detection capabilities, future ground-based optical telescopes will have a size of 30 m, and the aperture of space telescopes will be increased to 10 m. Such large optical systems necessitate the development of large integrated testing equipment. In this study, spectrum and system alignment measurements and wavefront quality checking were performed using the sub-aperture detection method and a fiber-connected Photonics Scanning Pentaprism (PSP).

Nonuniform Correction of Ground-Based Optical Telescope Image Based on Conditional Generative Adversarial Network.

Ground-based telescopes are often affected by vignetting, stray light and detector nonuniformity when acquiring space images. This paper presents a space image nonuniform correction method using the conditional generative adversarial network (). Firstly, we create a dataset for training by introducing the physical vignetting model and by designing the simulation polynomial to realize the nonuniform background.

Deep learning wavefront sensing for fine phasing of segmented mirrors.

Segmented primary mirror provides many crucial important advantages for the construction of extra-large space telescopes. The imaging quality of this class of telescope is susceptible to phasing error between primary mirror segments. Deep learning has been widely applied in the field of optical imaging and wavefront sensing, including phasing segmented mirrors.

Three dimensional band-filling control of complex oxides triggered by interfacial electron transfer.

The d-band-filling of transition metals in complex oxides plays an essential role in determining their structural, electronic and magnetic properties. Traditionally, at the oxide heterointerface, band-filling control has been achieved via electrostatic modification in the structure of field-effect transistors or electron transfer, which is limited to the quasi-two-dimension at the interface. Here we report a three-dimensional (3D) band-filling control by changing the local lattice coordination in a designed oxide heterostructure.

Large segmented sparse aperture collimation by curvature sensing.

Fine alignment of large, segmented telescopes is critical for achieving high angular resolution. Building an instrument with an equally large monolithic aperture is difficult because of the increasing mass and volume. Sparse aperture testing is a lower-cost solution to alignment and metrology, both in the optics shop and at the observatory.

Aberration retrieval by incorporating customized priors for estimating Zernike coefficients.

Zernike expansion is an important tool for aberration retrieval in the optical field. The Zernike coefficients in the expansion can be solved in a linear system from those focal region intensity images, which can be modeled by the extended Nijboer-Zernike approach. Here we point out that those coefficients usually follow from different prior distributions, and especially, their variances could be dramatically diverse.

Relay optical function and pre-construction results of a Giant Steerable Science Mirror for a thirty meter telescope.

The Giant Steerable Science Mirror (GSSM) is the tertiary mirror system of the Thirty Meter Telescope (TMT) that relays optical beams from the secondary mirror to active instruments on Nasmyth platforms. One of the key technologies involved in GSSM functions is the error budget allocation from the system engineering of TMT. A novel approach of error analysis and allocation with strong adaptability, which is based on normalized Point Source Sensitivity (PSSn), is proposed.

Ritchey-Common sparse-aperture testing of the Giant Steerable Science Mirror.

The Giant Steerable Science Mirror (GSSM) is the tertiary mirror of the future large telescope, the Thirty Meter Telescope. However, the mirror is too large to be tested using only one aperture, and using many apertures will increase the cost of testing. To accomplish testing at a low cost, the number of apertures should be reduced.

Realization of In-Plane p-n Junctions with Continuous Lattice of a Homogeneous Material.

Two-dimensional (2D) in-plane p-n junctions with a continuous interface have great potential in next-generation devices. To date, the general fabrication strategies rely on lateral epitaxial growth of p- and n-type 2D semiconductors. An in-plane p-n junction is fabricated with homogeneous monolayer Te at the step edge on graphene/6H-SiC(0001).

Analysis and correction for measurement error of edge sensors caused by deformation of guide flexure applied in the Thirty Meter Telescope SSA.

The Thirty Meter Telescope (TMT) project will design and build a 30-m-diameter telescope for research in astronomy in visible and infrared wavelengths. The primary mirror of TMT is made up of 492 hexagonal mirror segments under active control. The highly segmented primary mirror will utilize edge sensors to align and stabilize the relative piston, tip, and tilt degrees of segments.

Estimation of the GSSM calibration error.

The calibration of the tertiary mirror of the Thirty Meter Telescope, also known as the giant science steering mirror (GSSM), is a step of great significance during its testing process. Systematic, drift, and random errors constitute the major limitations to the accuracy of the calibration measurements. In this article, we estimated the errors in the calibration of the GSSM with a laser tracker.