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. The proposed design was verified by an experiment, and the results were consistent with the mathematical model. Furthermore, the results indicate that the repeatability of the semi-kinematic coupling is sufficient for the requirement.

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. Using scattering layers to replace the diffraction layers in traditional optical diffraction networks, this hybrid system circumvents the challenging training process associated with diffraction layers. Spectral outputs of the optical diffraction network were processed using a simple backpropagation neural network, forming an opto-electronic hybrid network exhibiting exceptional performance with minimal data. For three-class target recognition, this network attains a classification accuracy of 93.3% within a substantially short training time of 9.2 s using only 100 data samples (training: 70 and testing: 30). Furthermore, it demonstrates exceptional insensitivity to position errors in scattering elements, enhancing its robustness. Therefore, the proposed opto-electronic hybrid network presents substantial application prospects in the fields of machine vision, face recognition, and remote sensing.

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). First, the system was aligned using an optical truss, ensuring that the optical axis was properly positioned. Second, using a sub-aperture light beam though the entrance pupil, light spots were formed on the focal plane and transmitted to the spectrometer via fibers to obtain the corresponding spectral components. Then, by taking measurements at different system positions, a full-aperture spectrum response could be reached. Lastly, by photon-integrated interference on the focal plane, intensity interference fringes could be projected at the entrance pupil of the system. And the wavefront quality of the system could be verified by observing the fringe deformation. The measurement accuracy of the optical axis of the system is better than 2 mrad. The spectral measurement accuracy was better than 5%, and the wavefront measurement accuracy surpassed 0.1 wavelengths (1 wavelength = 633 nm). This study effectively enhanced the detection and in situ calibration capabilities of large telescope systems, ensuring that the performance requirements can be met in the design of future telescopes.

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 (CGAN). Firstly, we create a dataset for training by introducing the physical vignetting model and by designing the simulation polynomial to realize the nonuniform background. Secondly, we develop a robust conditional generative adversarial network (CGAN) for learning the nonuniform background, in which we improve the network structure of the generator. The experimental results include a simulated dataset and authentic space images. The proposed method can effectively remove the nonuniform background of space images, achieve the Mean Square Error (MSE) of 4.56 in the simulation dataset, and improve the target's signal-to-noise ratio (SNR) by 43.87% in the real image correction.

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. Compared to other image-based phasing techniques, such as phase retrieval and phase diversity, deep learning has the advantage of high efficiency and free of stagnation problem. However, at present deep learning methods are mainly applied to coarse phasing and used to estimate piston error between segments. In this paper, deep Bi-GRU neural work is introduced to fine phasing of segmented mirrors, which not only has a much simpler structure than CNN or LSTM network, but also can effectively solve the gradient vanishing problem in training due to long term dependencies. By incorporating phasing errors (piston and tip-tilt errors), some low-order aberrations as well as other practical considerations, Bi-GRU neural work can effectively be used for fine phasing of segmented mirrors. Simulations and real experiments are used to demonstrate the accuracy and effectiveness of the proposed methods.

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. At the LaCoO3/LaTiO3 heterointerface, due to the Fermi level mismatch, electrons transfer from LaTiO3 to LaCoO3. This triggers destabilisation of the CoO6 octahedrons, i.e. the formation of lattice configurations with a reduced Co valence. The associated oxygen migration results in the 3D topotactic phase transition of LaCoO3. Tuned by the thickness of LaTiO3, different crystalline phases and band-fillings of Co occur, leading to the emergence of different magnetic ground states.

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. We combined sparse aperture testing and curvature sensing to process the highly segmented system's final alignment. First, the stitching error, including tip/tilt/piston and shifting errors, is analyzed theoretically and numerically. These errors are then evaluated by normalized point source sensitivity (PSSn), and the change of PSSn during alignment, which specifies the residual alignment error, is calculated by the defocused donuts. Simulations and experiments demonstrate that the system performance improved by more than 35%. In this paper, we have described the incorporation of sparse aperture testing and curvature sensing algorithms, which can easily cover the tipping and shifting error affecting the traditional methodology.

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. To incorporate the prior information, we further introduce customized penalties to those Zernike coefficients and adopt a global adaptive generative adjustment algorithm for estimating coefficients. Based on both simulated and real data, numerical experiments show that our method outperforms other conventional methods, and provides an estimate of Zernike coefficients with a low mean square error.

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. The Ritchey-Common (R-C) testing method, commonly used for testing large flat surfaces, uses only a reference spherical mirror and avoids the use of large planar interferometers. Additionally, only the low-spatial-frequency mirror figure is relevant in the system assembly and alignment. Hence, the applicability of sparse-aperture testing is investigated in this paper. Sparse-aperture testing and the R-C method were combined to lower the cost. Using this method and the normalized point source sensitivity (PSSn), the mirror figure can be specified in a simple and accurate manner. Moreover, as fewer subapertures are under test, the efficiency can be improved. An error analysis is conducted, focusing on the shifting error, irregularity error, tipping error, tangential/sagittal error, and seeing. For the testing of the GSSM prototype, the error analysis showed the total error in PSSn is 0.9701.

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). Scanning tunneling spectroscopy reveals that Te on the terrace of trilayer graphene is p-type, and it is n-type on monolayer graphene. Atomic-resolution images demonstrate the continuous lattice of the junction, and mappings of the electronic states visualize the type-II band bending across the space-charge region of 6.2 nm with a build-in field of 4 × 105 V cm-1 . The reported strategy can be extended to other 2D semiconductors on patternable substrates for designed fabrication of in-plane junctions.

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. The support system assembly (SSA) of the segmented mirror utilizes a guide flexure to decouple the axial support and lateral support, while its deformation will cause measurement error of the edge sensor. We have analyzed the theoretical relationship between the segment movement and the measurement value of the edge sensor. Further, we have proposed an error correction method with a matrix. The correction process and the simulation results of the edge sensor will be described in this paper.

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. For the systematic error, a measurement strategy based on the standard bar method was successfully designed and applied. At the same time, we can distinguish between the drift and random errors by means of a correlation analysis. The systematic error, which depends strongly on the configuration of the system formed by the GSSM and the laser tracker, was estimated to be 20 µm for the GSSM prototype. The random error, averaging 15 min, was about 4 µm. The correlation coefficients among three different noise measurements are all lower than 0.1, which indicates that the noise is dominated by random errors. Finally, the error can be sufficiently suppressed by rearranging the position of the spherically mounted retroreflectors. The result shows that the accuracy of the measurement can be improved by 21.4% with the new arrangement method.