We review astronomical results in the visible (lambda<1 mu m) with adaptive optics. Other than a brief period in the early 1990s, there has been little (<1 paper/yr) night-time astronomical science published with AO in the visible from 2000-2013 (outside of the solar or Space Surveillance Astronomy communities where visible AO is the norm, but not the topic of this invited review). However, since mid-2013 there has been a rapid increase visible AO with over 50 refereed science papers published in just similar to 2.5 years (visible AO is experiencing a rapid growth rate very similar to that of NIR AO science from 1997-2000; Close 2000). Currently the most productive small (D < 2 m) visible light AO telescope is the UV-LGS Robo-AO system (Baranec, et al. 2016) on the robotic Palomar D=1.5 m telescope (currently relocated to the Kitt Peak 1.8m; Salama et al. 2016). Robo-AO uniquely offers the ability to target >15 objects/hr, which has enabled large (>3000 discrete targets) companion star surveys and has resulted in 23 refereed science publications. The most productive large telescope visible AO system is the D=6.5m Magellan telescope AO system (MagAO). MagAO is an advanced Adaptive Secondary Mirror (ASM) AO system at the Magellan 6.5m in Chile (Morzinski et al. 2016). This ASM secondary has 585 actuators with < 1 msec response times (0.7 ms typically). MagAO utilizes a 1 kHz pyramid wavefront sensor. The relatively small actuator pitch (similar to 22 cm/subap) allows moderate Strehls to be obtained in the visible (0.63-1.05 microns). Long exposures (60s) achieve <30mas resolutions, 30% Strehls at 0.62 microns (r') with the VisAO camera in 0.5" seeing with bright R <= 9 mag stars. These capabilities have led to over 22 MagAO refereed science publications in the visible. The largest (D=8m) telescope to achieve regular visible AO science is SPHERE/ZIMPOL. ZIMPOL is a polarimeter fed by the similar to 1.2 kHz SPHERE ExAO system (Fusco et al. 2016). ZIMPOL's ability to differentiate scattered polarized light from starlight allows the sensitive detection of circumstellar disks, stellar surfaces, and envelopes of evolved AGB stars. Here we review the key steps to having good performance in the visible and review the exciting new AO visible science opportunities and science results in the fields of: exoplanet detection; circumstellar and protoplanetary disks; young stars; AGB stars; emission line jets; and stellar surfaces. The recent rapid increase in the scientific publications and power of visible AO is due to the maturity of the next-generation of AO systems and our new ability probe circumstellar regions with very high (10-30 mas) spatial resolutions that would otherwise require much larger (> 10m) diameter telescopes in the infrared.

AutoCAD, Zemax Optic Studio 15, and Interactive Data Language (IDL) with the Proper Library are used to computationally model and test a diffractive mask (DiM) suitable for use in the Gemini Multi-Conjugate Adaptive Optics System (GeMS) on the Gemini South Telescope. Systematic errors in telescope imagery are produced when the light travels through the adaptive optics system of the telescope. DiM is a transparent, flat optic with a pattern of miniscule dots lithographically applied to it. It is added ahead of the adaptive optics system in the telescope in order to produce diffraction spots that will encode systematic errors in the optics after it. Once these errors are encoded, they can be corrected for. DiM will allow for more accurate measurements in astrometry and thus improve exoplanet detection. The mechanics and physical attributes of the DiM are modeled in AutoCAD. Zemax models the ray propagation of point sources of light through the telescope. IDL and Proper simulate the wavefront and image results of the telescope. Aberrations are added to the Zemax and IDL models to test how the diffraction spots from the DiM change in the final images. Based on the Zemax and IDL results, the diffraction spots are able to encode the systematic aberrations.

We present measurements of the evolutionary timescales of speckles around adaptive optics-corrected PSFs. We placed a SELEX SAPHIRA HgCdTe detector behind the SCExA0 instrument at Subaru Telescope. We analyzed the behavior of speckles at radial distances of 2-8 A/D away from the diffraction-limited PSF in H-band (-1.6 m) images collected at 1 kHz framerates. Speckles evolve with a variety of timescales, and these have not previously been studied at near-infrared wavelengths. Ultimately we would like to image reflected-light exoplanets, which necessitates a fast speckle control loop. Based on our measurements, we calculate the parameters of an optimized control loop that would enable such observations.

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第17826号 / 医博第3824号 / 新制||医||999(附属図書館) / 30641 / 京都大学大学院医学研究科医学専攻 / (主査)教授 渡邉 大, 教授 村井 俊哉, 教授 柳田 素子 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

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This thesis addresses the exponential growth of experimental data and the resulting computational complexity seen in two major scientific applications, which account for significant cycles consumed on today’s supercomputers. The first application concerns computation of the adaptive optics system in next-generation ground-based telescopes, which will expand our knowledge of the universe but confronts the astronomy community with daunting real-time computation requirements. The second application deals with emerging frequency-domain redatuming methods, e.g., Marchenko redatuming, which are game-changers in exploration geophysics. They are valuable to oil and gas applications and will soon be to geothermal exploration and carbon capture storage. However, they are impractical at industrial scale due to prohibitive computational complexity and memory footprint. We tackle the aforementioned challenges by designing high-performance algebraic and stochastic algorithms, which exploit the data sparsity structure of the matrix operator. We show that popular randomized algorithms from machine learning can also solve large covariance matrix problems that capture the correlations of wavefront sensors detecting the atmospheric turbulence for ground-based telescopes. Algebraic compression based on low-rank approximations that retains the most significant portion of the spectrum of the operator provides numerical solutions at the accuracy level required by the application. In addition, selective use of lower precisions can further reduce the data volume by trading off application accuracy for memory footprint. Reducing memory footprint has ancillary implications for reduced energy expenditure and reduced execution time because moving a word is more expensive than computing with it on today’s architectures. We exploit the data sparsity of matrices representative of these two scientific applications and propose four algorithms to accelerate the corresponding computational workload. In soft real-time control of an adaptive optics system, we design a stochastic Levenberg-Marquardt method and high-performance solver for Discrete-time Algebraic Riccati Equations. We create a tile low-rank matrix-vector multiplication algorithm used in both hard real-time control of ground-based telescopes and seismic redatuming. Finally, we leverage multiple precisions to further improve the performance of seismic redatuming applications We implement our algorithms on essentially all families of currently relevant HPC architectures and customized AI accelerators and demonstrate significant performance improvement and validated numerical solutions.

<p>  </p> <p>        Analyzing single molecule emission patterns plays a critical role in retrieving the structural and physiological information of their tagged targets, and further, understanding their interactions and cellular context. These emission patterns of tiny light sources (i.e. point spread functions, PSFs) simultaneously encode information such as the molecule’s location, orientation, the environment within the specimen, and the paths the emitted photons took before being captured by the camera. However, retrieving multiple classes of information beyond the 3D position from complex or high-dimensional single molecule data remains challenging, due to the difficulties in perceiving and summarizing a comprehensive yet succinct model. We developed smNet, a deep neural network that can extract multiplexed information near the theoretical limit from both complex and high-dimensional point spread functions. Through simulated and experimental data, we demonstrated that smNet can be trained to efficiently extract both molecular and specimen information, such as molecule location, dipole orientation, and wavefront distortions from complex and subtle features of the PSFs, which otherwise are considered too complex for established algorithms. </p> <p>        Single molecule localization microscopy (SMLM) forms super-resolution images with a resolution of several to tens of nanometers, relying on accurate localization of molecules’ 3D positions from isolated single molecule emission patterns. However, the inhomogeneous refractive indices distort and blur single molecule emission patterns, reduce the information content carried by each detected photon, increase localization uncertainty, and thus cause significant resolution loss, which is irreversible by post-processing. To compensate tissue induced aberrations, conventional sensorless adaptive optics methods rely on iterative mirror-changes and image-quality metrics to compensate aberrations. But these metrics result in inconsistent, and sometimes opposite, metric responses which fundamentally limited the efficacy of these approaches for aberration correction in tissues. Bypassing the previous iterative trial-then-evaluate processes, we developed deep learning driven adaptive optics (DL-AO), for single molecule localization microscopy (SMLM) to directly infer wavefront distortion and compensate distortion near real-time during data acquisition. our trained deep neural network monitors the individual emission patterns from single molecule experiments, infers their shared wavefront distortion, feeds the estimates through a dynamic filter (Kalman), and drives a deformable mirror to compensate sample induced aberrations. We demonstrated that DL-AO restores single molecule emission patterns approaching the conditions untouched by specimen and improves the resolution and fidelity of 3D SMLM through brain tissues over 130 µm, with as few as 3-20 mirror changes.</p>

For adaptive optic systems, the use of aperture filter functions calculated using various Zernike modes can be useful in removing lower-order aberrations caused by atmospheric turbulence. Traditionally, these filter functions are calculated using the step function depicting a hard aperture that introduces integrals that are sometimes difficult to integrate and must be done numerically. The Gaussian method can be used in place of the conventional method for calculating the aperture filter functions. Evaluation of the Gaussian approximation for modeling a finite receiver aperture can be made by comparison of reduction in phase variance with results achieved using the conventional method. The validity of Gaussian approximation in this application is demonstrated by the consistency of results between the two methodologies. Comparison of reduction in scintillation by the two methodologies reveals several benefits derived from utilization of Gaussian approximation. The Gaussian approximation produces data that can be interpreted analytically. It further produces greater scintillation reduction. This paper will first examine the use of statistical models for predicting atmospheric turbulence and then the use of Zernike polynomials in adaptive optics. Next, this paper compares the reduction of phase variance and scintillation using the conventional method with the Gaussian approximation to evaluate the effectiveness of the new filter functions. The results of these comparisons are presented both as mathematical expressions and graphically.

The relationship between accommodation and myopia has been under investigation for many years, and the effort to understand it is ongoing. In this thesis, an introduction to the state of myopia research is given first, with particular reference to studies of accommodation and higher-order ocular aberrations, which feature in the subsequent chapters. Following a brief introduction to the general technique of aberrometry and visual stimulus control using adaptive optics, the development of a monocular adaptive optics instrument for this purpose is described. The instrument is used to vary a dioptric stimulus and record the accommodation response in pilot studies and a detailed experiment, which has also been published elsewhere. It is found, among other things, that accommodation can respond to more than one different input level during its latency period, and that such inputs can be stored until components of the accommodation control system are free to process them. Indications of a minimum halting time for accommodation, of around 0.6 s, are presented. In later chapters, the development and testing of a new, binocular adaptive optics apparatus will be found. As well as binocular aberrometry and adaptive optics control of stimulus aberrations, this instrument displaces images to allow for and stimulate ocular convergence in binocular accommodation experiments. It is the first instrument in the world with its combined functionalities. Finally, the contribution of this thesis is summarised, and further instrumentation development and experiments are put forward for the continuation of this branch of accommodation and myopia research.

The continued growth of the communications industry has caused interest in mode-division multiplexing (MDM) techniques to flourish in recent years. These techniques allow individual waveguide modes to be used as distinct channels. However, as with any versatile technique, it should be also useful and beneficial to extend its application to other areas. This work concerns itself with an initial conceptual design of a mode-division multiplexing (MDM) enabled optical sensor network that can use modes to interrogate either specific sensors or sensor subsystems, and specifically with quanitizing and optimizing the injection and detection of the signal of interest. A hypothetical test setup is demonstrated, and the major issue of back reflection burying the intended signal is addressed, analyzed, and improved. Improvements in the signal-to-background contrast ratio (SBCR) of approximately 10dB were achieved depending on fibre type and proximal face. Suggestions for extensions to further improve the SBCR as well as for applications of this system are discussed. / Master of Science