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Register a new userMICADO PSF-Reconstruction work package description
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The point spread function reconstruction (PSF-R) capability is a deliverable of the MICADO@ESO-ELT project. The PSF-R team works on the implementation of the instrument software devoted to reconstruct the point spread function (PSF), independently of the science data, using adaptive optics (AO) telemetry data, both for Single Conjugate (SCAO) and Multi-Conjugate Adaptive Optics (MCAO) mode of the MICADO camera and spectrograph. The PSF-R application will provide reconstructed PSFs through an archive querying system to restore the telemetry data synchronous to each science frame that MICADO will generate. Eventually, the PSF-R software will produce the output according to user specifications. The PSF-R service will support the state-of-the-art scientific analysis of the MICADO imaging and spectroscopic data.
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In this work, we present a novel centroiding method based on Fourier space Phase Fitting(FPF) for Point Spread Function(PSF) reconstruction. We generate two sets of simulations to test our method. The first set is generated by GalSim with elliptical Moffat profile and strong anisotropy which shifts the center of the PSF. The second set of simulation is drawn from CFHT i band stellar imaging data. We find non-negligible anisotropy from CFHT stellar images, which leads to $sim$0.08 scatter in unit of pixels using polynomial fitting method Vakili and Hogg (2016). And we apply FPF method to estimate the centroid in real space, this scatter reduces to $sim$0.04 in SNR=200 CFHT like sample. In low SNR (50 and 100) CFHT like samples, the background noise dominates the shifting of the centroid, therefore the scatter estimated from different methods are similar. We compare polynomial fitting and FPF using GalSim simulation with optical anisotropy. We find that in all SNR$sim$50, 100 and 200) samples, FPF performs better than polynomial fitting by a factor of $sim$3. In general, we suggest that in real observations there are anisotropy which shift the centroid, and FPF method is a better way to accurately locate it.
Adaptive optics (AO) allows one to derive the point spread function (PSF) simultaneously to the science image, which is a major advantage in post-processing tasks such as astrometry/photometry or deconvolution. Based on the algorithm of citet{veran97}, PSF reconstruction has been developed for four different AO systems so far: PUEO, ALFA, Lick-AO and Altair. A similar effort is undertaken for NAOS/VLT in a collaboration between the group PHASE (Onera and Observatoire de Paris/LESIA) and ESO. In this paper, we first introduce two new algorithms that prevent the use of the so-called $U_{ij}$ functions to: (1) avoid the storage of a large amount of data (for both new algorithms), (2) shorten the PSF reconstruction computation time (for one of the two) and (3) provide an estimation of the PSF variability (for the other one). We then identify and explain issues in the exploitation of real-time Shack-Hartmann (SH) data for PSF reconstruction, emphasising the large impact of thresholding in the accuracy of the phase residual estimation. Finally, we present the data provided by the NAOS real-time computer (RTC) to reconstruct PSF ({em (1)} the data presently available, {em (2)} two NAOS software modifications that would provide new data to increase the accuracy of the PSF reconstruction and {em (3)} the tests of these modifications) and the PSF reconstruction algorithms we are developing for NAOS on that basis.
In order to enhance accuracy of astrophysical estimates obtained on Adaptive-optics (AO) images, such as photometry and astrometry, we investigate a new concept to constrain the Point Spread Function (PSF) model called PSF Reconstruction and Identification for Multi-sources characterization Enhancement (PRIME), that handles jointly the science image and the AO control loop data. We present in this paper the concept of PRIME and validate it on Keck II telescope NIRC2 images. We show that by calibrating the PSF model over the scientific image, PSF reconstruction achieves 1% and 3 mas of accuracy on respectively the Strehl-ratio and the PSF full width at half maximum. We show on NIRC2 binary images that PRIME is sufficiently robust to noise to retain photometry and astrometry precision below 0.005 mag and 100$mu$as on a $m_H=$ 14 mag object. Finally, we also validate that PRIME performs a PSF calibration on the triple system Gl569BAB which provides a separation of 66.73$pm 1.02$ and a differential photometry of 0.538$pm 0.048$, compared to the reference values obtained with the extracted PSF which are 66.76 mas $pm$ 0.94 and 0.532 mag $pm$ 0.041.
MICADO will equip the E-ELT with a first light capability for diffraction limited imaging at near-infrared wavelengths. The instruments observing modes focus on various flavours of imaging, including astrometric, high contrast, and time resolved. There is also a single object spectroscopic mode optimised for wavelength coverage at moderately high resolution. This contribution provides an overview of the key functionality of the instrument, outlining the scientific rationale for its observing modes. The interface between MICADO and the adaptive optics system MAORY that feeds it is summarised. The design of the instrument is discussed, focussing on the optics and mechanisms inside the cryostat, together with a brief overview of the other key sub-systems.
MICADO is a near-IR camera for the Europea ELT, featuring an extended field (75 diameter) for imaging, and also spectrographic and high contrast imaging capabilities. It has been chosen by ESO as one of the two first-light instruments. Although it is ultimately aimed at being fed by the MCAO module called MAORY, MICADO will come with an internal SCAO system that will be complementary to it and will deliver a high performance on axis correction, suitable for coronagraphic and pupil masking applications. The basis of the pupil masking approach is to ensure the stability of the optical transfer function, even in the case of residual errors after AO correction (due to non common path errors and quasi-static aberrations). Preliminary designs of pupil masks are presented. Trade-offs and technical choices, especially regarding redundancy and pupil tracking, are explained.
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