Solar adaptive optics systems for the New Vacuum Solar Telescope at the Fuxian Lake Solar Observatory

Adaptive optics(AO)is essential for high-quality ground-based observations with large telescopes because it counters the impact of wavefront aberrations caused by atmospheric turbulence.The new vacuum solar telescope(NVST)is one of the most important high-resolution solar observation instruments in the world.Three sets of solar adaptive optics systems have been developed and installed on this telescope:conventional adaptive optics,ground layer adaptive optics,and multi-conjugate adaptive optics.These have been in operation from 2018 to 2023.This paper details the development and application of solar adaptive optics on the NVST and discusses the newest instrumentation.

Adaptive optics based on machine learning: a review

Adaptive optics techniques have been developed over the past half century and routinely used in large ground-based telescopes for more than 30 years.Although this technique has already been used in various applications,the basic setup and methods have not changed over the past 40 years.In recent years,with the rapid development of artificial in-telligence,adaptive optics will be boosted dramatically.In this paper,the recent advances on almost all aspects of adapt-ive optics based on machine learning are summarized.The state-of-the-art performance of intelligent adaptive optics are reviewed.The potential advantages and deficiencies of intelligent adaptive optics are also discussed.

EAST-Educational Adaptive-optics Solar Telescope

For the public having a better understanding of solar activities,the Educational Adaptive-optics Solar Telescope(EAST)was built in July 2021 and is located at the Shanghai Astronomy Museum.The EAST consists of a 65 cm aperture solar telescope with a 177-element adaptive optics system and two-channel high resolution imaging system at the Hαand TiO bands,in addition to three full disk solar telescopes at CaK,Hαand TiO bands equipped on the tube of the main telescope.In this paper,the configuration of the EAST is described.Its performance and on-sky observational results are presented.The EAST,to our knowledge,is the most advanced solar telescope for the popularization of science in the world.Due to its excellent performance,the data acquired by the EAST can also be used for research on solar physics and space weather prediction.

High-resolution visible imaging with piezoelectric deformable secondary mirror: experimental results at the 1.8-m adaptive telescope

Integrating deformable mirrors within the optical train of an adaptive telescope was one of the major innovations in astronomical observation technology,distinguished by its high optical throughput,reduced optical surfaces,and the incorporation of the deformable mirror.Typically,voice-coil actuators are used,which require additional position sensors,internal control electronics,and cooling systems,leading to a very complex structure.Piezoelectric deformable secondary mirror technologies were proposed to overcome these problems.Recently,a high-order piezoelectric deformable secondary mirror has been developed and installed on the 1.8-m telescope at Lijiang Observatory in China to make it an adaptive telescope.The system consists of a 241-actuator piezoelectric deformable secondary mirror,a 192-sub-aperture Shack-Hartmann wavefront sensor,and a multi-core-based real-time controller.The actuator spacing of the PDSM measures 19.3 mm,equivalent to approximately 12.6 cm when mapped onto the primary mirror,significantly less than the voicecoil-based adaptive telescopes such as LBT,Magellan and VLT.As a result,stellar images with Strehl ratios above 0.49 in the R band have been obtained.To our knowledge,these are the highest R band images captured by an adaptive telescope with deformable secondary mirrors.Here,we report the system description and on-sky performance of this adaptive telescope.

Visualization for Explanation of Deep Learning-Based Fault Diagnosis Model Using Class Activation Map

Permanent magnet synchronous motor(PMSM)is widely used in various production processes because of its high efficiency,fast reaction time,and high power density.With the continuous promotion of new energy vehicles,timely detection of PMSM faults can significantly reduce the accident rate of new energy vehicles,further enhance consumers’trust in their safety,and thus promote their popularity.Existing fault diagnosis methods based on deep learning can only distinguish different PMSM faults and cannot interpret and analyze them.Convolutional neural networks(CNN)show remarkable accuracy in image data analysis.However,due to the“black box”problem in deep learning models,the diagnostic results regarding providing accurate information to the user are uncertain.This paper proposes a motor fault diagnosis method based on improved deep residual network(ResNet)and gradient-weighted class activation mapping(Grad-CAM)to analyze demagnetization and eccentricity faults of permanent magnet synchronous motors,and the uncertainty limitation of fault diagnosis based on the convolutional neural network is overcome by the visual interpretation method.The improved ResNet is formed by using ResNet9 as the backbone network,replacing the last convolution layer with a atrous spatial pyramid pooling(ASPP),and adding a multi-scale feature fusion module and attention channel mechanism(CAM).The proposed model not only retains the effective extraction of image features by ResNet9 but also enhances the sensitivity field of the network through the hollow convolution pyramid and realizes the feature fusion of the web on different scales through the multi-scale feature fusion module(MSFFM),further improving the diagnostic accuracy of the network on different types of fault features.The diagnostic effect of the network is verified on the selfmade data set,which mainly includes five states:normal(He),25%demagnetization(De25),50%demagnetization(De50),10%static eccentricity(Se10),and 20%static eccentricity(Se20).The number of pictures in the training set is 6000,and the number in the test set is 1500.The average diagnostic accuracy of the improved ResNet on this dataset is 99.00%,which is 1.04%,8.89%,4.58%,and 7.22%higher than that of the multi-column convolutional neural network(MCNN),Bi-directional long short-term memory(Bi-LSTM),deep belief network(DBN),and recurrent neural network(RNN)models,respectively.Finally,gradient activation heat maps were used to globally average pool the final output feature map of the network to obtain feature weights.They were superimposed with the original image to get gradient activation heat maps of different grayscale images.The warmer the tone of the heat map,the greater the impact on the network diagnosis results,and then the demagnetization and eccentricity fault characteristics of the permanent magnet synchronous motor were determined-visual characterization of quantitative analysis.

First light of the 1.8-m solar telescope–CLST

Large-aperture solar telescopes play an important role in solar observations and research,and require high temporal and spatial resolution[1].To solve some fundamental problems such as the solar dynamo,coronal heating,and the triggering of major solar eruptions,the spatial resolution for solar-atmosphere observation should reach at least 0.1 arcsec[2].

First light of solar multi-conjugate adaptive optics at the 1-m new vacuum solar telescope

Observations play a leading role in any branches of astronomy, including solar physics. In order to solve fundamental problems, such as solar dynamo [1], coronal heating [2] and the triggering of major solar eruptions [3], solar observations with spatial resolution better than 0.1 arcsec are required. Such a goal cannot be achieved without the help of adaptive optics （AO）, which eliminates the wavefront distortion caused by atmosphere turbulence [4,5]. However, solar observations are performed over an extended field of view （FoV）. Flare trigger mechanisms operate rapidly and on the smallest spatial scales and their location within the FoV is difficult to predict.

Ground-layer adaptive optics for the New Vacuum Solar Telescope:Instrument description and first results

Ground-layer adaptive optics(GLAO)has shown its potential for use in solar observation owing to its wide field-of-view(FOV)correction.A high-order GLAO system that consists of a multiple direction Shack-Hartmann wavefront sensor(WFS),a realtime controller with a multi-CPU processor,and a 151-element deformable mirror was developed for the 1-m New Vacuum Solar Telescope at Yunnan Observatories,Chinese Academy of Sciences.A hexagonal microlens with 9×8 subapertures is employed in the WFS.The detection FOV is 42′′×37′′,in which 9(3×3)guide regions are extracted for multiple direction wavefront sensing with a frame rate of up to 2200 Hz.To our knowledge,this is the first professional solar GLAO system used as a regularly operating instrument for scientific observations.Its installation and adjustment were performed in the summer of 2021.In this article,a detailed account of the GLAO system and its first light results and a comprehensive analysis of the performance of the GLAO system are provided.The results show that this system can effectively improve the imaging quality after compensating for the wavefront aberration due to ground-layer turbulence.