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Added by
Visweshwar Ram Marthi Mr.
Publication date
2013
fields
Physics
and research's language is
English
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For radio interferometric arrays with a sufficient number of redundant spacings the multiplicity of measurements of the same sky visibility can be used to determine both the antenna gains as well as the true visibilities. Many of the earlier approaches to this problem focused on lineariz
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EFOSC2 (the European Southern Observatory Faint Object Spectrograph and Camera v2) is one of the workhorse instruments on ESOs New Technology Telescope (NTT), and is one of the most popular instruments at La Silla observatory. It is mounted at a Nasmyth focus, and therefore exhibits strong, wavelength and pointing-direction dependent instrumental polarisation. In this document we describe our efforts to calibrate the broadband imaging polarimetry mode, and provide a calibration for broadband B, V, R filters to a level that satisfies most use cases (i.e. polarimetric calibration uncertainty ~0.1%). We make our calibration codes public. This calibration effort can be used to enhance the yield of future polarimetric programmes with EFOSC2, by allowing good calibration with a greatly reduced number of standard star observations. Similarly, our calibration model can be combined with archival calibration observations to post-process data taken in past years, to form a EFOSC2 legacy archive with substantial scientific potential.
Self-supervised learning is an empirically successful approach to unsupervised learning based on creating artificial supervised learning problems. A popular self-supervised approach to representation learning is contrastive learning, which leverages naturally occurring pairs of similar and dissimilar data points, or multiple views of the same data. This work provides a theoretical analysis of contrastive learning in the multi-view setting, where two views of each datum are available. The main result is that linear functions of the learned representations are nearly optimal on downstream prediction tasks whenever the two views provide redundant information about the label.
Increasing interest in astronomical applications of non-linear curvature wavefront sensors for turbulence detection and correction makes it important to understand how best to handle the data they produce, particularly at low light levels. Algorithms for wavefront phase-retrieval from a four-plane curvature wavefront sensor are developed and compared, with a view to their use for low order phase compensation in instruments combining adaptive optics and Lucky Imaging. The convergence speed and quality of iterative algorithms is compared to their step-size and techniques for phase retrieval at low photon counts are explored. Computer simulations show that at low light levels, preprocessing by convolution of the measured signal with a gaussian function can reduce by an order of magnitude the photon flux required for accurate phase retrieval of low-order errors. This facilitates wavefront correction on large telescopes with very faint reference stars.
The Gemini Planet Imager (GPI) entered on-sky commissioning phase, and had its First Light at the Gemini South telescope in November 2013. Meanwhile, the fast loops for atmospheric correction of the Extreme Adaptive Optics (XAO) system have been closed on many dozen stars at different magnitudes (I=4-8), elevation angles and a variety of seeing conditions, and a stable loop performance was achieved from the beginning. Ultimate contrast performance requires a very low residual wavefront error (design goal 60 nm RMS), and optimization of the planet finding instrument on different ends has just begun to deepen and widen its dark hole region. Laboratory raw contrast benchmarks are in the order of 10^-6 or smaller. In the telescope environment and in standard operations new challenges are faced (changing gravity, temperature, vibrations) that are tackled by a variety of techniques such as Kalman filtering, open-loop models to keep alignment to within 5 mas, speckle nulling, and a calibration unit (CAL). The CAL unit was especially designed by the Jet Propulsion Laboratory to control slowly varying wavefront errors at the focal plane of the apodized Lyot coronagraph by the means of two wavefront sensors: 1) a 7x7 low order Shack-Hartmann SH wavefront sensor (LOWFS), and 2) a special Mach-Zehnder interferometer for mid-order spatial frequencies (HOWFS) - atypical in that the beam is split in the focal plane via a pinhole but recombined in the pupil plane with a beamsplitter. The original design goal aimed for sensing and correcting on a level of a few nm which is extremely challenging in a telescope environment. This paper focuses on non-common path low order wavefront correction as achieved through the CAL unit on sky. We will present the obtained results as well as explain challenges that we are facing.
The Marshall Grazing Incidence X-ray Spectrometer (MaGIXS) is a sounding rocket experiment that observes the soft X-ray spectrum of the Sun from 6.0 - 24 Angstrom (0.5 - 2.0 keV), successfully launched on 30 July 2021. End-to-end alignment of the flight instrument and calibration experiments are carried out using the X-ray and Cryogenic Facility (XRCF) at NASA Marshall Space Flight Center. In this paper, we present the calibration experiments of MaGIXS, which include wavelength calibration, measurement of line spread function, and determination of effective area. Finally, we use the measured instrument response function to predict the expected count rates for MaGIXS flight observation looking at a typical solar active region
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