The Thresher : lucky imaging without the waste

JAH acknowledges funding from the Science and Technology Facilities Council of the United Kingdom.In traditional lucky imaging (TLI), many consecutive images of the same scene are taken with a high frame-rate camera, and all but the sharpest images are discarded before constructing the final shift-and-add image. Here, we present an alternative image analysis pipeline – The Thresher – for these kinds of data, based on online multi-frame blind deconvolution. It makes use of all available data to obtain the best estimate of the astronomical scene in the context of reasonable computational limits; it does not require prior estimates of the point-spread functions in the images, or knowledge of point sources in the scene that could provide such estimates. Most importantly, the scene it aims to return is the optimum of a justified scalar objective based on the likelihood function. Because it uses the full set of images in the stack, The Thresher outperforms TLI in signal-to-noise ratio; as it accounts for the individual-frame PSFs, it does this without loss of angular resolution. We demonstrate the effectiveness of our algorithm on both simulated data and real Electron-Multiplying CCD images obtained at the Danish 1.54-m telescope (hosted by ESO, La Silla). We also explore the current limitations of the algorithm, and find that for the choice of image model presented here, non-linearities in flux are introduced into the returned scene. Ongoing development of the software can be viewed at https://github.com/jah1994/TheThresher.Publisher PDFPeer reviewe

First Impressions: Early-Time Classification of Supernovae using Host Galaxy Information and Shallow Learning

Substantial effort has been devoted to the characterization of transient phenomena from photometric information. Automated approaches to this problem have taken advantage of complete phase-coverage of an event, limiting their use for triggering rapid follow-up of ongoing phenomena. In this work, we introduce a neural network with a single recurrent layer designed explicitly for early photometric classification of supernovae. Our algorithm leverages transfer learning to account for model misspecification, host galaxy photometry to solve the data scarcity problem soon after discovery, and a custom weighted loss to prioritize accurate early classification. We first train our algorithm using state-of-the-art transient and host galaxy simulations, then adapt its weights and validate it on the spectroscopically-confirmed SNe Ia, SNe II, and SNe Ib/c from the Zwicky Transient Facility Bright Transient Survey. On observed data, our method achieves an overall accuracy of $82 \pm 2$% within 3 days of an event's discovery, and an accuracy of $87 \pm 5$% within 30 days of discovery. At both early and late phases, our method achieves comparable or superior results to the leading classification algorithms with a simpler network architecture. These results help pave the way for rapid photometric and spectroscopic follow-up of scientifically-valuable transients discovered in massive synoptic surveys.Comment: 24 pages, 8 figures. Accepted to Ap

eleanor: An open-source tool for extracting light curves from the TESS Full-Frame Images

During its two year prime mission the Transiting Exoplanet Survey Satellite (TESS) will perform a time-series photometric survey covering over 80% of the sky. This survey comprises observations of 26 24 x 96 degree sectors that are each monitored continuously for approximately 27 days. The main goal of TESS is to find transiting planets around 200,000 pre-selected stars for which fixed aperture photometry is recorded every two minutes. However, TESS is also recording and delivering Full-Frame Images (FFIs) of each detector at a 30 minute cadence. We have created an open-source tool, eleanor, to produce light curves for objects in the TESS FFIs. Here, we describe the methods used in eleanor to produce light curves that are optimized for planet searches. The tool performs background subtraction, aperture and PSF photometry, decorrelation of instrument systematics, and cotrending using principal component analysis. We recover known transiting exoplanets in the FFIs to validate the pipeline and perform a limited search for new planet candidates in Sector 1. Our tests indicate that eleanor produces light curves with significantly less scatter than other tools that have been used in the literature. Cadence-stacked images, and raw and detrended eleanor light curves for each analyzed star will be hosted on MAST, with planet candidates on ExoFOP-TESS as Community TESS Objects of Interest (CTOIs). This work confirms the promise that the TESS FFIs will enable the detection of thousands of new exoplanets and a broad range of time domain astrophysics.Comment: 21 pages, 13 figures, 2 tables, Accepted to PAS

The three-dimensional structure of Galactic molecular cloud complexes out to 2.5 kpc

Knowledge of the three-dimensional structure of Galactic molecular clouds is important for understanding how clouds are affected by processes such as turbulence and magnetic fields and how this structure effects star formation within them. Great progress has been made in this field with the arrival of the Gaia mission, which provides accurate distances to $\sim10^{9}$ stars. Combining these distances with extinctions inferred from optical-IR, we recover the three-dimensional structure of 16 Galactic molecular cloud complexes at $\sim1$pc resolution using our novel three-dimensional dust mapping algorithm \texttt{Dustribution}. Using \texttt{astrodendro} we derive a catalogue of physical parameters for each complex. We recover structures with aspect ratios between 1 and 11, i.e.\ everything from near-spherical to very elongated shapes. We find a large variation in cloud environments that is not apparent when studying them in two-dimensions. For example, the nearby California and Orion A clouds look similar on-sky, but we find California to be more sheet-like, and massive, which could explain their different star-formation rates. In Carina, our most distant complex, we observe evidence for dust sputtering, which explains its measured low dust mass. By calculating the total mass of these individual clouds, we demonstrate that it is necessary to define cloud boundaries in three-dimensions in order to obtain an accurate mass; simply integrating the extinction overestimates masses. We find that Larson's relationship on mass vs radius holds true whether you assume a spherical shape for the cloud or take their true extents.Comment: accepted for publication by MNRAS, 23 pages, 9 figures, 3 table

An Efficient Automated Validation Procedure for Exoplanet Transit Candidates

Surveys searching for transiting exoplanets have found many more candidates than they have been able to confirm as true planets. This situation is especially acute with the Kepler survey, which has found over 2300 candidates but has confirmed only 77 planets to date. I present here a general procedure that can quickly be applied to any planet candidate to calculate its false positive probability. This procedure takes into account the period, depth, duration, and shape of the signal; the colors of the target star; arbitrary spectroscopic or imaging follow-up observations; and informed assumptions about the populations and distributions of field stars and multiple-star properties. I also introduce the concept of the "specific occurrence rate," which allows for the calculation of the FPP without relying on an assumed planet radius function. Applying these methods to a sample of known Kepler planets, I demonstrate that many signals can be validated with very limited follow-up observations: in most cases with only a spectrum and an AO image. Additionally, I demonstrate that this procedure can reliably identify false positive signals. Because of the computational efficiency of this analysis, it is feasible to apply it to all Kepler planet candidates in the near future, and it will streamline the follow-up efforts for Kepler and other current and future transit surveys.Comment: accepted to Ap

V1298 Tau with TESS: Updated Ephemerides, Radii, and Period Constraints from a Second Transit of V1298 Tau e

V1298 Tau is a young (20-30 Myr) solar-mass K star hosting four transiting exoplanets with sizes between 0.5 and 0.9 R J. Given the system's youth, it provides a unique opportunity to understand the evolution of planetary radii at different separations in the same stellar environment. V1298 Tau was originally observed 6 yr ago during K2 Campaign 4. Now, V1298 Tau has been re-observed during the extended mission of NASA's Transiting Exoplanet Survey Satellite (TESS). Here, we present new photometric observations of V1298 Tau from TESS. We use the TESS data to update the ephemerides for V1298 Tau bcde as well as compare newly observed radii to those measured from the K2 light curve, finding shallower transits for V1298 Tau bcd in the redder TESS bandpass at the 1-2σ level. We suspect the difference in radii is due to starspot crossing events or contamination from nearby faint stars on the same pixels as V1298 Tau. Additionally, we catch a second transit of V1298 Tau e and present a new method for deriving the marginalized posterior probability of a planet's period from two transits observed years apart. We find the highest probability period for V1298 Tau e to be in a near 2:1 mean motion resonance with V1298 Tau b which, if confirmed, could make V1298 Tau bcde a four-planet resonant chain. V1298 Tau is the target of several ongoing and future observations. These updated ephemerides will be crucial for scheduling future transit observations and interpreting future Doppler tomographic or transmission spectroscopy signals

A generative model for quasar spectra

High Energy AstrophysicsGalaxie