Near-infrared fundus imaging system with light illumination from an electronic contact lens

As for the diagnosis and treatment of eye diseases, an ideal fundus imaging system is expected to be portability, low cost, and high resolution. Here, we demonstrate a non-mydriatic near-infrared fundus imaging system with light illumination from an electronic contact lens (E-lens). The E-lens can illuminate the retinal and choroidal structures for capturing the fundus images when voltage is applied wirelessly to the lens. And we also reconstruct the images with a depth-dependent point-spread function to suppress the scattering effect that eventually visualizes the clear fundus images.

128383 (2004 JW52) is an Ordinary Jupiter Trojan Asteroid

The Jupiter Trojan asteroid 128383 (2004 JW52) was recently reported to have optical colors that are incongruous with its dynamical class. New and archival observations show that this is not the case. This is a reminder that we must always rule out the possibility that the Point-Spread Function of a minor planet is blended with that of a background sidereal source in survey images before its colors in the associated survey catalog can be considered reliable.

Accurate Photometry of Saturated Stars Using the Point-spread-function Wing Technique with Spitzer

We report Spitzer 3.6 and 4.5 μm photometry of 11 bright stars relative to Sirius, exploiting the unique optical stability of the Spitzer Space Telescope point-spread function (PSF). Spitzer's extremely stable beryllium optics in its isothermal environment enables precise comparisons in the wings of the PSF from heavily saturated stars. These bright stars stand as the primary sample to improve stellar models, and to transfer the absolute flux calibration of bright standard stars to a sample of fainter standards useful for missions like JWST and for large ground-based telescopes. We demonstrate that better than 1% relative photometry can be achieved using the PSF wing technique in the radial range of 20″–100″ for stars that are fainter than Sirius by 8 mag (from outside the saturated core to a large radius where a high signal-to-noise ratio profile can still be obtained). We test our results by (1) comparing the [3.6]−[4.5] color with that expected between the WISE W1 and W2 bands, (2) comparing with stars where there is accurate K S photometry, and (3) also comparing with relative fluxes obtained with the DIRBE instrument on COBE. These tests confirm that relative photometry is achieved to better than 1%.

Revisiting KELT-19Ab, WASP-156b, and WASP-121b in the TESS Era

We present a re-analysis of transit depths of KELT-19Ab, WASP-156b, and WASP-121b, including data from the Transiting Exoplanet Survey Satellite (TESS). The large ∼21″ TESS pixels and point-spread function result in significant contamination of the stellar flux by nearby objects. We use Gaia data to fit for and remove this contribution, providing general-purpose software for this correction. We find all three sources have a larger inclination, compared to earlier work. For WASP-121b, we find significantly smaller values (13.°5) of the inclination when using the 30 minute cadence data compared to the 2 minute cadence data. Using simulations, we demonstrate that the radius ratio of exoplanet to star (R p /R *) is biased small relative to data taken with a larger sampling interval although oversampling corrections mitigate the bias. This is particularly important for deriving subpercent transit differences between bands. We find the radius ratio of exoplanet to star (R p /R *) in the TESS band is 7.5σ smaller than previous work for KELT-19Ab, but consistent to within ∼2σ for WASP-156b and WASP-121b. The difference could be due to specific choices in the analysis, not necessarily due to the presence of atmospheric features. The result for KELT-19Ab possibly favors a haze-dominated atmosphere. We do not find evidence for the ∼0.95 μm water feature contaminating transit depths in the TESS band for these stars but show that with photometric precision of 500 ppm and with a sampling of about 200 observations across the entire transit, this feature could be detectable in a more narrow z-band.

Bayesian Fitting of Multi-Gaussian Expansion Models to Galaxy Images

Fitting parameterized models to images of galaxies has become the standard for measuring galaxy morphology. This forward-modeling technique allows one to account for the point-spread function to effectively study semi-resolved galaxies. However, using a specific parameterization for a galaxy’s surface brightness profile can bias measurements if it is not an accurate representation. Furthermore, it can be difficult to assess systematic errors in parameterized profiles. To overcome these issues we employ the Multi-Gaussian expansion (MGE) method of representing a galaxy’s profile together with a Bayesian framework for fitting images. MGE flexibly represents a galaxy’s profile using a series of Gaussians. We introduce a novel Bayesian inference approach that uses pre-rendered Gaussian components, which greatly speeds up computation time and makes it feasible to run the fitting code on large samples of galaxies. We demonstrate our method with a series of validation tests. By injecting galaxies, with properties similar to those observed at z ∼ 1.5, into deep Hubble Space Telescope observations we show that it can accurately recover total fluxes and effective radii of realistic galaxies. Additionally we use degraded images of local galaxies to show that our method can recover realistic galaxy surface brightness and color profiles. Our implementation is available in an open source python package imcascade, which contains all methods needed for the preparation of images, fitting, and analysis of results.

Neural networks application to determine the types and magnitude of aberrations from the pattern of the point spread function out of the focal plane

Recognition of the types of aberrations corresponding to individual Zernike functions were carried out from the pattern of the intensity of the point spread function (PSF) outside the focal plane using convolutional neural networks. The PSF intensity patterns outside the focal plane are more informative in comparison with the focal plane even for small values/magnitudes of aberrations. The mean prediction errors of the neural network for each type of aberration were obtained for a set of 8 Zernike functions from a dataset of 2 thousand pictures of out-of-focal PSFs. As a result of training, for the considered types of aberrations, the obtained averaged absolute errors do not exceed 0.0053, which corresponds to an almost threefold decrease in the error in comparison with the same result for focal PSFs.

Point-spread Function Deconvolution of the IFU Data and Restoration of Galaxy Stellar Kinematics

We present a performance test of the point-spread function (PSF) deconvolution algorithm applied to astronomical integral field unit (IFU) spectroscopy data for restoration of galaxy kinematics. We deconvolve the IFU data by applying the Lucy–Richardson algorithm to the 2D image slice at each wavelength. We demonstrate that the algorithm can effectively recover the true stellar kinematics of the galaxy, by using mock IFU data with a diverse combination of surface brightness profile, signal-to-noise ratio, line-of-sight geometry, and line-of-sight velocity distribution (LOSVD). In addition, we show that the proxy of the spin parameter λ R e can be accurately measured from the deconvolved IFU data. We apply the deconvolution algorithm to the actual SDSS-IV MaNGA IFU survey data. The 2D LOSVD, geometry, and λ R e measured from the deconvolved MaNGA IFU data exhibit noticeable differences compared to the ones measured from the original IFU data. The method can be applied to any other regular-grid IFU data to extract the PSF-deconvolved spatial information.