High-contrast Imaging with Spitzer: Deep Observations of Vega, Fomalhaut, and epsilon Eridani

Stars with debris disks are intriguing targets for direct imaging exoplanet searches, both due to previous detections of wide planets in debris disk systems, as well as commonly existing morphological features in the disks themselves that may be indicative of a planetary influence. Here we present observations of three of the most nearby young stars, that are also known to host massive debris disks: Vega, Fomalhaut, and eps Eri. The Spitzer Space Telescope is used at a range of orientation angles for each star, in order to supply a deep contrast through angular differential imaging combined with high-contrast algorithms. The observations provide the opportunity to probe substantially colder bound planets (120--330 K) than is possible with any other technique or instrument. For Vega, some apparently very red candidate point sources detected in the 4.5 micron image remain to be tested for common proper motion. The images are sensitive to ~2 Mjup companions at 150 AU in this system. The observations presented here represent the first search for planets around Vega using Spitzer. The upper 4.5 micron flux limit on Fomalhaut b could be further constrained relative to previous data. In the case of eps Eri, planets below both the effective temperature and the mass of Jupiter could be probed from 80 AU and outwards, although no such planets were found. The data sensitively probe the regions around the edges of the debris rings in the systems where planets can be expected to reside. These observations validate previous results showing that more than an order of magnitude improvement in performance in the contrast-limited regime can be acquired with respect to conventional methods by applying sophisticated high-contrast techniques to space-based telescopes, thanks to the high degree of PSF stability provided in this environment.Comment: 11 pages, 12 figures, accepted for publication in A&

Precision of a Low-Cost InGaAs Detector for Near Infrared Photometry

We have designed, constructed, and tested an InGaAs near-infrared camera to explore whether low-cost detectors can make small (<1 m) telescopes capable of precise (<1 mmag) infrared photometry of relatively bright targets. The camera is constructed around the 640x512 pixel APS640C sensor built by FLIR Electro-Optical Components. We designed custom analog-to-digital electronics for maximum stability and minimum noise. The InGaAs dark current halves with every 7 deg C of cooling, and we reduce it to 840 e-/s/pixel (with a pixel-to-pixel variation of +/-200 e-/s/pixel) by cooling the array to -20 deg C. Beyond this point, glow from the readout dominates. The single-sample read noise of 149 e- is reduced to 54 e- through up-the-ramp sampling. Laboratory testing with a star field generated by a lenslet array shows that 2-star differential photometry is possible to a precision of 631 +/-205 ppm (0.68 mmag) hr^-0.5 at a flux of 2.4E4 e-/s. Employing three comparison stars and de-correlating reference signals further improves the precision to 483 +/-161 ppm (0.52 mmag) hr^-0.5. Photometric observations of HD80606 and HD80607 (J=7.7 and 7.8) in the Y band shows that differential photometry to a precision of 415 ppm (0.45 mmag) hr^-0.5 is achieved with an effective telescope aperture of 0.25 m. Next-generation InGaAs detectors should indeed enable Poisson-limited photometry of brighter dwarfs with particular advantage for late-M and L types. In addition, one might acquire near-infrared photometry simultaneously with optical photometry or radial velocity measurements to maximize the return of exoplanet searches with small telescopes.Comment: Accepted to PAS

Full-depth Coadds of the WISE and First-year NEOWISE-Reactivation Images

The Near Earth Object Wide-field Infrared Survey Explorer (NEOWISE) Reactivation mission released data from its first full year of observations in 2015. This data set includes ~2.5 million exposures in each of W1 and W2, effectively doubling the amount of WISE imaging available at 3.4 and 4.6 microns relative to the AllWISE release. We have created the first ever full-sky set of coadds combining all publicly available W1 and W2 exposures from both the AllWISE and NEOWISE-Reactivation (NEOWISER) mission phases. We employ an adaptation of the unWISE image coaddition framework (Lang 2014), which preserves the native WISE angular resolution and is optimized for forced photometry. By incorporating two additional scans of the entire sky, we not only improve the W1/W2 depths, but also largely eliminate time-dependent artifacts such as off-axis scattered moonlight. We anticipate that our new coadds will have a broad range of applications, including target selection for upcoming spectroscopic cosmology surveys, identification of distant/massive galaxy clusters, and discovery of high-redshift quasars. In particular, our full-depth AllWISE+NEOWISER coadds will be an important input for the Dark Energy Spectroscopic Instrument (DESI) selection of luminous red galaxy and quasar targets. Our full-depth W1/W2 coadds are already in use within the DECam Legacy Survey (DECaLS) and Mayall z-band Legacy Survey (MzLS) reduction pipelines. Much more work still remains in order to fully leverage NEOWISER imaging for astrophysical applications beyond the solar system.Comment: coadds available at http://unwise.me, zoomable full-sky rendering at http://legacysurvey.org/viewe

Holographic Imaging of Crowded Fields: High Angular Resolution Imaging with Excellent Quality at Very Low Cost

We present a method for speckle holography that is optimised for crowded fields. Its two key features are an iterativ improvement of the instantaneous Point Spread Functions (PSFs) extracted from each speckle frame and the (optional) simultaneous use of multiple reference stars. In this way, high signal-to-noise and accuracy can be achieved on the PSF for each short exposure, which results in sensitive, high-Strehl re- constructed images. We have tested our method with different instruments, on a range of targets, and from the N- to the I-band. In terms of PSF cosmetics, stability and Strehl ratio, holographic imaging can be equal, and even superior, to the capabilities of currently available Adaptive Optics (AO) systems, particularly at short near-infrared to optical wavelengths. It outperforms lucky imaging because it makes use of the entire PSF and reduces the need for frame selection, thus leading to higher Strehl and improved sensitivity. Image reconstruction a posteriori, the possibility to use multiple reference stars and the fact that these reference stars can be rather faint means that holographic imaging offers a simple way to image large, dense stellar fields near the diffraction limit of large telescopes, similar to, but much less technologically demanding than, the capabilities of a multi-conjugate adaptive optics system. The method can be used with a large range of already existing imaging instruments and can also be combined with AO imaging when the corrected PSF is unstable.Comment: Accepted for publication in MNRAS on 15 Nov 201

ASTRA: ASTrometry and phase-Referencing Astronomy on the Keck interferometer

ASTRA (ASTrometric and phase-Referencing Astronomy) is an upgrade to the existing Keck Interferometer which aims at providing new self-phase referencing (high spectral resolution observation of YSOs), dual-field phase referencing (sensitive AGN observations), and astrometric (known exoplanetary systems characterization and galactic center general relativity in strong field regime) capabilities. With the first high spectral resolution mode now offered to the community, this contribution focuses on the progress of the dual field and astrometric modes.Comment: 10 pages, 6 figures, 2 tables, SPIE 201

Improving Task-Parameterised Movement Learning Generalisation with Frame-Weighted Trajectory Generation

Learning from Demonstration depends on a robot learner generalising its learned model to unseen conditions, as it is not feasible for a person to provide a demonstration set that accounts for all possible variations in non-trivial tasks. While there are many learning methods that can handle interpolation of observed data effectively, extrapolation from observed data offers a much greater challenge. To address this problem of generalisation, this paper proposes a modified Task-Parameterised Gaussian Mixture Regression method that considers the relevance of task parameters during trajectory generation, as determined by variance in the data. The benefits of the proposed method are first explored using a simulated reaching task data set. Here it is shown that the proposed method offers far-reaching, low-error extrapolation abilities that are different in nature to existing learning methods. Data collected from novice users for a real-world manipulation task is then considered, where it is shown that the proposed method is able to effectively reduce grasping performance errors by ${\sim30\%}$ and extrapolate to unseen grasp targets under real-world conditions. These results indicate the proposed method serves to benefit novice users by placing less reliance on the user to provide high quality demonstration data sets.Comment: 8 pages, 6 figures, submitted to 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS