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Register a new userPlanet detection down to a few $lambda$/D: an RSDI/TLOCI approach to PSF subtraction
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Most current high contrast imaging point spread function (PSF) subtraction algorithms use some form of a least-squares noise minimization to find exoplanets that are, before post-processing, often hidden below the instrumental speckle noise. In the current standard PSF subtraction algorithms, a set of reference images is derived from the target image sequence to subtract each target image, using Angular and/or Simultaneous Spectral Differential Imaging (ADI, SSDI, respectively). However, to avoid excessive exoplanet self-subtraction, ADI and SSDI (in the absence of a strong spectral feature) severely limit the available number of reference images at small separations. This limits the performance of the least-squares algorithm, resulting in lower sensitivity to exoplanets at small angular separations. Possible solutions are to use additional reference images by acquiring longer sequences, use SSDI if the exoplanet is expected to show strong spectral features, or use images acquired on other targets. The latter option, known as Reference Star Differential Imaging (RSDI), which relies on the use of reference images that are highly correlated to the target image, has been ineffective in previous ground-based high contrast imaging surveys. We present the results of work to optimize PSF subtraction with the GPIES reference library using a least-squares algorithm designed to minimize speckle noise and maximize planet throughput, thus maximizing the planet signal to noise ratio (SNR). Using December 2014 51 Eri GPI data in the inner 100 mas to 300 mas annulus, we find no apparent improvement in SNR when using RSDI and/or our optimization scheme. This result, while still being investigated, seems to show that current algorithms on ADI+SSDI data sets are optimized, and that limited gains can be achieved by using a PSF archive.
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We present the implementation and use of algorithms for matching point-spread functions (PSFs) within the Pan-STARRS Image Processing Pipeline (IPP). PSF-matching is an essential part of the IPP for the detection of supernovae and asteroids, but it is also used to homogenize the PSF of inputs to stacks, resulting in improved photometric precision compared to regular coaddition, especially in data with a high masked fraction. We report our experience in constructing and operating the image subtraction pipeline, and make recommendations about particular basis functions for constructing the PSF-matching convolution kernel, determining a suitable kernel, parallelisation and quality metrics. We introduce a method for reliably tracking the noise in an image throughout the pipeline, using the combination of a variance map and a `covariance pseudo-matrix. We demonstrate these algorithms with examples from both simulations and actual data from the Pan-STARRS1 telescope.
Angular differential imaging (ADI) and spectral differential imaging (SDI) are commonly used for direct detection and characterisation of young, Jovian exoplanets in datasets obtained with the SPHERE/IFS instrument. We compare the performance of ADI, SDI, and three combinations of ADI and SDI to find which technique achieves the highest signal-to-noise ratio (S/N), and we analyse their performance as functions of integration time, field rotation, and wavelength range. We analyse SPHERE/IFS observations of three known exoplanets, namely Beta Pictoris b, 51 Eridani b, and HR 8799 e, with five differential imaging techniques. We split the datasets into subsets to vary each parameter before the data are processed with each technique. The differential imaging techniques are applied using principal component analysis (PCA). The tests show that a combination of SDI and ADI consistently achieves better results than ADI alone, and using SDI and ADI simultaneously (combined differential imaging; CODI) achieved the best results. The integration time test shows that targets with a separation larger than 0.24 arcsec observed with an integration time of more than 10$^3$s were photon-noise limited. Field rotation shows a strong correlation with S/N for field rotations up to 1 full width at half maximum (FWHM), after which no significant increase in S/N with field rotation is observed. Wavelength range variation shows a general increase in S/N for broader wavelength ranges, but no clear correlation is seen. Spectral information is essential to boost S/N compared to regular ADI. Our results suggest that CODI should be the preferred processing technique to search for new exoplanets with SPHERE/IFS. To optimise direct-imaging observations, the field rotation should exceed 1 FWHM to detect exoplanets at small separations.
PHASECam is the Large Binocular Telescope Interferometers (LBTI) phase sensor, a near-infrared camera which is used to measure tip/tilt and phase variations between the two AO-corrected apertures of the Large Binocular Telescope (LBT). Tip/tilt and phase sensing are currently performed in the H (1.65 $mu$m) and K (2.2 $mu$m) bands at 1 kHz, and the K band phase telemetry is used to send tip/tilt and Optical Path Difference (OPD) corrections to the system. However, phase variations outside the range [-$pi$, $pi$] are not sensed, and thus are not fully corrected during closed-loop operation. PHASECams phase unwrapping algorithm, which attempts to mitigate this issue, still occasionally fails in the case of fast, large phase variations. This can cause a fringe jump, in which case the unwrapped phase will be incorrect by a wavelength or more. This can currently be manually corrected by the observer, but this is inefficient. A more reliable and automated solution is desired, especially as the LBTI begins to commission further modes which require robust, active phase control, including controlled multi-axial (Fizeau) interferometry and dual-aperture non-redundant aperture masking interferometry. We present a multi-wavelength method of fringe jump capture and correction which involves direct comparison between the K band and currently unused H band phase telemetry.
The Adaptive Optics (AO) performance significantly depends on the available Natural Guide Stars (NGSs) and a wide range of atmospheric conditions (seeing, Cn2, windspeed,...). In order to be able to easily predict the AO performance, we have developed a fast algorithm - called TIPTOP - producing the expected AO Point Spread Function (PSF) for any of the existing AO observing modes (SCAO, LTAO, MCAO, GLAO), and any atmospheric conditions. This TIPTOP tool takes its roots in an analytical approach, where the simulations are done in the Fourier domain. This allows to reach a very fast computation time (few seconds per PSF), and efficiently explore the wide parameter space. TIPTOP has been developed in Python, taking advantage of previous work developed in different languages, and unifying them in a single framework. The TIPTOP app is available on GitHub at: https://github.com/FabioRossiArcetri/TIPTOP, and will serve as one of the bricks for the ELT Exposure Time Calculator.
Protoplanetary disk surveys by the Atacama Large Millimeter/sub-millimeter Array (ALMA) are now probing a range of environmental conditions, from low-mass star-forming regions like Lupus to massive OB clusters like $sigma$ Orionis. Here we conduct an ALMA survey of protoplanetary disks in $lambda$ Orionis, a ~5 Myr old OB cluster in Orion, with dust mass sensitivities comparable to the surveys of nearby regions (~0.4 $M_oplus$). We assess how massive OB stars impact planet formation, in particular from the supernova that may have occurred ~1 Myr ago in the core of $lambda$ Orionis; studying these effects is important as most planetary systems, including our Solar System, are likely born in cluster environments. We find that the effects of massive stars, in the form of pre-supernova feedback and/or a supernova itself, do not appear to significantly reduce the available planet-forming material otherwise expected at the evolved age of $lambda$ Orionis. We also compare a lingering massive outlier disk in $lambda$ Orionis to similar systems in other evolved regions, hypothesizing that these outliers host companions in their inner disks that suppress disk dispersal to extend the lifetimes of their outer primordial disks. We conclude with numerous avenues for future work, highlighting how $lambda$ Orionis still has much to teach us about perhaps one of the most common types of planet-forming environments in the Galaxy.
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