Photometry Pipeline Research Articles

Cosmological Distance Measurement of Twelve Nearby Supernovae IIP with ROTSE-IIIb

We present cosmological analysis of 12 nearby (z < 0.06) Type IIP supernovae (SNe IIP) observed with the ROTSE-IIIb telescope. To achieve precise photometry, we present a new image-differencing technique that is implemented for the first time on the ROTSE SN photometry pipeline. With this method, we find up to a 20% increase in the detection efficiency and significant reduction in residual rms scatter of the SN lightcurves when compared to the previous pipeline performance. We use the published optical spectra and broadband photometry of well-studied SNe IIP to establish temporal models for ejecta velocity and photospheric temperature evolution for our SNe IIP population. This study yields measurements that are competitive with other methods even when the data are limited to a single epoch during the photospheric phase of SNe IIP. Using the fully reduced ROTSE photometry and optical spectra, we apply these models to the respective photometric epochs for each SN in the ROTSE IIP sample. This facilitates the use of the Expanding Photosphere Method (EPM) to obtain distance estimates to their respective host galaxies. We then perform cosmological parameter fitting using these EPM distances, from which we measure the Hubble constant to be 72.9−4.3+5.7kms−1Mpc−1 , which is consistent with the standard ΛCDM model values derived using other independent techniques.

Systematic reanalysis of KMTNet microlensing events, paper I: Updates of the photometry pipeline and a new planet candidate

ABSTRACT In this work, we update and develop algorithms for KMTNet tender-love care (TLC) photometry in order to create a new, mostly automated, TLC pipeline. We then start a project to systematically apply the new TLC pipeline to the historic KMTNet microlensing events, and search for buried planetary signals. We report the discovery of such a planet candidate in the microlensing event MOA-2019-BLG-421/KMT-2019-BLG-2991. The anomalous signal can be explained by either a planet around the lens star or the orbital motion of the source star. For the planetary interpretation, despite many degenerate solutions, the planet is most likely to be a Jovian planet orbiting an M or K dwarf, which is a typical microlensing planet. The discovery proves that the project can indeed increase the sensitivity of historic events and find previously undiscovered signals.

The Magnificent Five Images of Supernova Refsdal: Time Delay and Magnification Measurements

In late 2014, four images of supernova (SN) “Refsdal,” the first known example of a strongly lensed SN with multiple resolved images, were detected in the MACS J1149 galaxy-cluster field. Following the images’ discovery, the SN was predicted to reappear within hundreds of days at a new position ∼8″ away in the field. The observed reappearance in late 2015 makes it possible to carry out Refsdal’s original proposal to use a multiply imaged SN to measure the Hubble constant H 0, since the time delay between appearances should vary inversely with H 0. Moreover, the position, brightness, and timing of the reappearance enable a novel test of the blind predictions of galaxy-cluster models, which are typically constrained only by the positions of multiply imaged galaxies. We have developed a new photometry pipeline that uses DOLPHOT to measure the fluxes of the five images of SN Refsdal from difference images. We apply four separate techniques to perform a blind measurement of the relative time delays and magnification ratios between the last image SX and the earlier images S1–S4. We measure the relative time delay of SX–S1 to be days and the relative magnification to be . This corresponds to a 1.5% precision on the time delay and 17% precision for the magnification ratios and includes uncertainties due to millilensing and microlensing. In an accompanying paper, we place initial and blind constraints on the value of the Hubble constant.

UnTimely: a Full-sky, Time-domain unWISE Catalog

We present the unTimely Catalog, a deep time-domain catalog of detections based on Wide-field Infrared Survey Explorer (WISE) and NEOWISE observations spanning the 2010 through 2020 time period. Detections are extracted from “time-resolved unWISE coadds,” which stack together each biannual sky pass of WISE imaging to create a set of ∼16 all-sky maps (per band), each much deeper and cleaner than individual WISE exposures. unTimely incorporates the W1 (3.4 μm) and W2 (4.6 μm) channels, meaning that our data set effectively consists of ∼32 full-sky unWISE catalogs. We run the crowdsource crowded-field point-source photometry pipeline (Schlafly et al. 2018) on each epochal coadd independently, with low detection thresholds: S/N = 4.0 (2.5) in W1 (W2). In total, we tabulate and publicly release 23.5 billion (19.9 billion) detections at W1 (W2). unTimely is ∼1.3 mag deeper than the WISE/NEOWISE Single Exposure Source Tables near the ecliptic, with further enhanced depth toward higher ecliptic latitudes. The unTimely Catalog is primarily designed to enable novel searches for faint, fast-moving objects, such as Y dwarfs and/or late-type (T/Y) subdwarfs in the Milky Way’s thick disk or halo. unTimely will also facilitate other time-domain science applications, such as all-sky studies of quasar variability at mid-infrared wavelengths over a decade-long time baseline.

A photometry pipeline for SDSS images based on convolutional neural networks

ABSTRACT In this paper, we propose a convolutional neural network (CNN)-based photometric pipeline for the Sloan Digital Sky Survey (SDSS) images. The pipeline includes three main parts: the target source detection, the target source classification, and the photometric parameter measurement. The last part is completed using traditional methods. The paper mainly focuses on the first two parts and does not present the last. In the 1st part, a network named TSD-YOLOv4 is proposed to detect new sources missed by the SDSS photometric pipeline according to the PhotoObjAll catalogue of SDSS. In the second part, a target source classification network named TSCNet is constructed to classify sources into galaxies, quasars, and stars directly from photometric images. Experiments show that TSD-YOLOv4 outperforms other networks (Faster-RCNN, YOLOv4, YOLOX, etc.) in all metrics, with an accuracy of 0.988, a recall of 0.997, and an F1-score of 0.992, and TSCNet has good performance with a classification accuracy of 0.944 on the test set with 23 265 sources, and precision rates of 0.98, 0.908, and 0.918 for galaxies, quasars, and stars, respectively. On the other hand, the recall rates are 0.982, 0.903, and 0.921 for galaxies, quasars, and stars, respectively. The TSCNet has higher accuracy, fewer parameters, and faster inference speed than the leading astronomical photometric source classification network, the APSCNet model. In addition, the effect of magnitude distribution on the classification results is discussed in the experiments. The experiments prove that the proposed pipeline can be used as a powerful tool to supplement the SDSS photometric catalogue.

A Conditional Autoencoder for Galaxy Photometric Parameter Estimation

Astronomical photometric surveys routinely image billions of galaxies, and traditionally infer the parameters of a parametric model for each galaxy. This approach has served us well, but the computational expense of deriving a full posterior probability distribution function is a challenge for increasingly ambitious surveys. In this paper, we use deep learning methods to characterize galaxy images, training a conditional autoencoder on mock data. The autoencoder can reconstruct and denoise galaxy images via a latent space engineered to include semantically meaningful parameters, such as brightness, location, size, and shape. Our model recovers galaxy fluxes and shapes on mock data with a lower variance than the Hyper Suprime-Cam photometry pipeline, and returns reasonable answers even for inputs outside the range of its training data. When applied to data in the training range, the regression errors on all extracted parameters are nearly unbiased with a variance near the Cramr-Rao bound.

The Lick Observatory Supernova Search follow-up program: photometry data release of 70 SESNe

ABSTRACT We present BVRI and unfiltered (Clear) light curves of 70 stripped-envelope supernovae (SESNe), observed between 2003 and 2020, from the Lick Observatory Supernova Search follow-up program. Our SESN sample consists of 19 spectroscopically normal SNe Ib, 2 peculiar SNe Ib, six SNe Ibn, 14 normal SNe Ic, 1 peculiar SN Ic, 10 SNe Ic-BL, 15 SNe IIb, 1 ambiguous SN IIb/Ib/c, and 2 superluminous SNe. Our follow-up photometry has (on a per-SN basis) a mean coverage of 81 photometric points (median of 58 points) and a mean cadence of 3.6 d (median of 1.2 d). From our full sample, a subset of 38 SNe have pre-maximum coverage in at least one passband, allowing for the peak brightness of each SN in this subset to be quantitatively determined. We describe our data collection and processing techniques, with emphasis toward our automated photometry pipeline, from which we derive publicly available data products to enable and encourage further study by the community. Using these data products, we derive host-galaxy extinction values through the empirical colour evolution relationship and, for the first time, produce accurate rise-time measurements for a large sample of SESNe in both optical and infrared passbands. By modelling multiband light curves, we find that SNe Ic tend to have lower ejecta masses and lower ejecta velocities than SNe Ib and IIb, but higher 56Ni masses.

Ultra-short-period Planets in K2. III. Neighbors are Common with 13 New Multiplanet Systems and 10 Newly Validated Planets in Campaigns 0–8 and 10

Abstract Using the EVEREST photometry pipeline, we have identified 74 candidate ultra-short-period planets (USPs; orbital period P &lt; 1 day) in the first half of the K2 data (Campaigns 0–8 and 10). Of these, 33 candidates have not previously been reported. A systematic search for additional transiting planets found 13 new multiplanet systems containing a USP, doubling the number known and representing a third (32%) of USPs in our sample from K2. We also identified 30 companions, which have periods from 1.4 to 31 days (median 5.5 days). A third (36 of 104) of the candidate USPs and companions have been statistically validated or confirmed in this work, 10 for the first time, including 7 USPs. Almost all candidates, and all validated planets, are small (radii R p ≤ 3 R ⊕) with a median radius of R p = 1.1 R ⊕; the validated and confirmed USP candidates have radii between 0.4 R ⊕ and 2.4 R ⊕ and periods from P = 0.18 to 0.96 days. The lack of candidate (a) ultra-hot-Jupiter (R p &gt; 10 R ⊕) and (b) short-period-desert (3 ≤ R p ≤ 10 R ⊕) planets suggests that both populations are rare, although our survey may have missed some of the very deepest transits. These results also provide strong evidence that we have not reached a lower limit on the distribution of planetary radius values for planets at close proximity to a star and suggest that additional improvements in photometry techniques would yield yet more USPs. The large fraction of USPs in known multiplanet systems supports origins models that involve dynamical interactions with exterior planets coupled to tidal decay of the USP orbits.

EDEN: Sensitivity Analysis and Transiting Planet Detection Limits for Nearby Late Red Dwarfs

Abstract Small planets are common around late-M dwarfs and can be detected through highly precise photometry by the transit method. Planets orbiting nearby stars are particularly important as they are often the best-suited for future follow-up studies. We present observations of three nearby M dwarfs referred to as EIC-1, EIC-2, and EIC-3, and use them to search for transits and set limits on the presence of planets. On most nights our observations are sensitive to Earth-sized transiting planets, and photometric precision is similar to or better than TESS for faint late-M dwarfs of the same magnitude (I ≈ 15 mag). We present our photometry and transit search pipeline, which utilizes simple median detrending in combination with transit least-squares-based transit detection. For these targets, and transiting planets between one and two Earth radii, we achieve an average transit detection probability of ∼60% between periods of 0.5 and 2 days, ∼30% between 2 and 5 days, and ∼10% between 5 and 10 days. These sensitivities are conservative compared to visual searches.

Lick Observatory Supernova Search follow-up program: photometry data release of 93 Type Ia supernovae

ABSTRACT We present BVRI and unfiltered light curves of 93 Type Ia supernovae (SNe Ia) from the Lick Observatory Supernova Search (LOSS) follow-up program conducted between 2005 and 2018. Our sample consists of 78 spectroscopically normal SNe Ia, with the remainder divided between distinct subclasses (3 SN 1991bg-like, 3 SN 1991T-like, 4 SNe Iax, 2 peculiar, and 3 super-Chandrasekhar events), and has a median redshift of 0.0192. The SNe in our sample have a median coverage of 16 photometric epochs at a cadence of 5.4 d, and the median first observed epoch is ∼4.6 d before maximum B-band light. We describe how the SNe in our sample are discovered, observed, and processed, and we compare the results from our newly developed automated photometry pipeline to those from the previous processing pipeline used by LOSS. After investigating potential biases, we derive a final systematic uncertainty of 0.03 mag in BVRI for our data set. We perform an analysis of our light curves with particular focus on using template fitting to measure the parameters that are useful in standardizing SNe Ia as distance indicators. All of the data are available to the community, and we encourage future studies to incorporate our light curves in their analyses.

J-PLUS: Identification of low-metallicity stars with artificial neural networks using SPHINX

Context.We present a new methodology for the estimation of stellar atmospheric parameters from narrow- and intermediate-band photometry of the Javalambre Photometric Local Universe Survey (J-PLUS), and propose a method for target pre-selection of low-metallicity stars for follow-up spectroscopic studies. Photometric metallicity estimates for stars in the globular cluster M15 are determined using this method.Aims.By development of a neural-network-based photometry pipeline, we aim to produce estimates of effective temperature,Teff, and metallicity, [Fe/H], for a large subset of stars in the J-PLUS footprint.Methods.The Stellar Photometric Index Network Explorer, SPHINX, was developed to produce estimates ofTeffand [Fe/H], after training on a combination of J-PLUS photometric inputs and synthetic magnitudes computed for medium-resolution (R~ 2000) spectra of the Sloan Digital Sky Survey. This methodology was applied to J-PLUS photometry of the globular cluster M15.Results.Effective temperature estimates made with J-PLUS Early Data Release photometry exhibit low scatter, σ(Teff) = 91 K, over the temperature range 4500 &lt;Teff(K) &lt; 8500. For stars from the J-PLUS First Data Release with 4500 &lt;Teff(K) &lt; 6200, 85 ± 3% of stars known to have [Fe/H] &lt; −2.0 are recovered by SPHINX. A mean metallicity of [Fe/H] = − 2.32 ± 0.01, with a residual spread of 0.3 dex, is determined for M15 using J-PLUS photometry of 664 likely cluster members.Conclusions.We confirm the performance of SPHINX within the ranges specified, and verify its utility as a stand-alone tool for photometric estimation of effective temperature and metallicity, and for pre-selection of metal-poor spectroscopic targets.

APPHi: An automated photometry pipeline for high cadence, large volume data

Abstract We present the software package APPHi (A utomated P hotometry P ipeline for Hi gh Cadence, Large Volume Data), developed to carry out in a computationally-efficient manner, the aperture and differential photometry of the large volume of data to be produced by the TAOS-II project. However, it can also be used to process other astronomical, wide field image data. The main features of the APPHi package are: its computational speed, the capacity to work with large volume data and to handle both FITS and HDF5 image formats. Due to the large number of stars (in excess of 10 4 ) that the software has to handle in a great number of frames (more than 10 5 for a typical TAOS-II visit), it is optimized to automatically find the best value for parameters to carry out the photometry, such as: mask size for aperture, size of the window for extraction of a single star and the number of counts for the threshold for faint star detection. Using images with similar features to those that will be collected in the TAOS-II project, we carry out a comparative performance study with the widely used software IRAF, and find that APPHi can obtain light curves of comparable quality, in terms of the Signal to Noise Ratio over the light curve ( S N R L C ), up to 300 times faster. In addition to its efficiency, the tests carried out prove that APPHi, although intended to work with TAOS-II data, can also be used to analyze other sets of astronomical images, being a robust and versatile tool to perform aperture and differential photometry of point sources.

Reducing and Analyzing the PHAT Survey with the Cloud

Abstract We discuss the technical challenges we faced and the techniques we used to overcome them when reducing the Panchromatic Hubble Andromeda Treasury (PHAT) photometric data set on the Amazon Elastic Compute Cloud (EC2). We first describe the architecture of our photometry pipeline, which we found particularly efficient for reducing the data in multiple ways for different purposes. We then describe the features of EC2 that make this architecture both efficient to use and challenging to implement. We describe the techniques we adopted to process our data, and suggest ways these techniques may be improved for those interested in trying such reductions in the future. Finally, we summarize the output photometry data products, which are now hosted publicly in two places in two formats. They are in simple fits tables in the high-level science products on MAST, and on a queryable database available through the NOAO Data Lab.

SMASH: Survey of the MAgellanic Stellar History

Abstract The Large and Small Magellanic Clouds are unique local laboratories for studying the formation and evolution of small galaxies in exquisite detail. The Survey of the MAgellanic Stellar History (SMASH) is an NOAO community Dark Energy Camera (DECam) survey of the Clouds mapping 480 deg2 (distributed over ∼2400 square degrees at ∼20% filling factor) to ∼24th mag in ugriz. The primary goals of SMASH are to identify low surface brightness stellar populations associated with the stellar halos and tidal debris of the Clouds, and to derive spatially resolved star formation histories. Here, we present a summary of the survey, its data reduction, and a description of the first public Data Release (DR1). The SMASH DECam data have been reduced with a combination of the NOAO Community Pipeline, the PHOTRED automated point-spread-function photometry pipeline, and custom calibration software. The astrometric precision is ∼15 mas and the accuracy is ∼2 mas with respect to the Gaia reference frame. The photometric precision is ∼0.5%–0.7% in griz and ∼1% in u with a calibration accuracy of ∼1.3% in all bands. The median 5σ point source depths in ugriz are 23.9, 24.8, 24.5, 24.2, and 23.5 mag. The SMASH data have already been used to discover the Hydra II Milky Way satellite, the SMASH 1 old globular cluster likely associated with the LMC, and extended stellar populations around the LMC out to R ∼ 18.4 kpc. SMASH DR1 contains measurements of ∼100 million objects distributed in 61 fields. A prototype version of the NOAO Data Lab provides data access and exploration tools.

PHOTOMETRYPIPELINE: An automated pipeline for calibrated photometry

PHOTOMETRYPIPELINE (PP) is an automated pipeline that produces calibrated photometry from imaging data through image registration, aperture photometry, photometric calibration, and target identification with only minimal human interaction. PP utilizes the widely used Source Extractor software for source identification and aperture photometry; SCAMP is used for image registration. Both image registration and photometric calibration are based on matching field stars with star catalogs, requiring catalog coverage of the respective field. A number of different astrometric and photometric catalogs can be queried online. Relying on a sufficient number of background stars for image registration and photometric calibration, PP is well-suited to analyze data from small to medium-sized telescopes. Calibrated magnitudes obtained by PP are typically accurate within 0.03 mag and astrometric accuracies are of the order of 0.3 arcsec relative to the catalogs used in the registration. The pipeline consists of an open-source software suite written in Python 2.7, can be run on Unix-based systems on a simple desktop machine, and is capable of realtime data analysis. PP has been developed for observations of moving targets, but can be used for analyzing point source observations of any kind.

NIR Tully–Fisher in the Zone of Avoidance – III. Deep NIR catalogue of the HIZOA galaxies

We present a deep near-infrared (NIR) photometric catalogue of sources from the Parkes HI Zone of Avoidance (HIZOA) survey, which forms the basis for an investigation of the matter distribution in the Zone of Avoidance. Observations were conducted between 2006 and 2013 using the Infrared Survey Facility (IRSF), a 1.4-m telescope situated at the South African Astronomical Observatory site in Sutherland. The images cover all 1108 HIZOA detections and yield 915 galaxies. An additional 105 bright 2MASS galaxies in the southern ZOA were imaged with the IRSF, resulting in 129 galaxies. The average $K_s$-band seeing and sky background for the survey are 1.38 arcsec and 20.1 mag, respectively. The detection rate as a function of stellar density and dust extinction is found to depend mainly on the HI mass of the HI detected galaxies, which in principal correlates with the NIR brightness of the spiral galaxies. The measured isophotal magnitudes are of sufficient accuracy (errors $\sim$ 0.02 mag) to be used in a Tully-Fisher analysis. In the final NIR catalogue, 285 galaxies have both IRSF and 2MASS photometry (180 HIZOA plus 105 bright 2MASX galaxies). The $K_s$-band isophotal magnitudes presented in this paper agree, within the uncertainties, with those reported in the 2MASX catalogue. Another 30 galaxies, from the HIZOA northern extension, are also covered by UKIDSS Galactic Plane Survey (GPS) images, which are one magnitude deeper than our IRSF images. A modified version of our photometry pipeline was used to derive the photometric parameters of these UKIDSS galaxies. Good agreement was found between the respective $K_s$-band isophotal magnitudes. These comparisons confirm the robustness of the isophotal parameters and demonstrate that the IRSF images do not suffer from foreground contamination, after star removal, nor under-estimate the isophotal fluxes of ZoA galaxies.

A NEW ANALYSIS OF THE EXOPLANET HOSTING SYSTEM HD 6434

The current goal of exoplanetary science is not only focused on detecting but characterizing planetary systems in hopes of understanding how they formed, evolved, and relate to the Solar System. The Transit Ephemeris Refinement and Monitoring Survey (TERMS) combines both radial velocity (RV) and photometric data in order to achieve unprecedented ground-based precision in the fundamental properties of nearby, bright, exoplanet-hosting systems. Here we discuss HD 6434 and its planet, HD 6434b, which has a M_p*sin(i) = 0.44 M_J mass and orbits every 22.0170 days with an eccentricity of 0.146. We have combined previously published RV data with new measurements to derive a predicted transit duration of ~6 hrs, or 0.25 days, and a transit probability of 4%. Additionally, we have photometrically observed the planetary system using both the 0.9m and 1.0m telescopes at the Cerro Tololo Inter-American Observatory, covering 75.4% of the predicted transit window. We reduced the data using the automated TERMS Photometry Pipeline, developed to ensure consistent and accurate results. We determine a dispositive null result for the transit of HD 6434b, excluding the full transit to a depth of 0.9% and grazing transit due to impact parameter limitations to a depth of 1.6%

Gravitational lensing analysis of the Kilo-Degree Survey

The Kilo-Degree Survey (KiDS) is a multi-band imaging survey designed for cosmological studies from weak lensing and photometric redshifts. It uses the European Southern Observatory VLT Survey Telescope with its wide-field camera OmegaCAM. KiDS images are taken in four filters similar to the Sloan Digital Sky Survey ugri bands. The best seeing time is reserved for deep r-band observations. The median 5σ limiting AB magnitude is 24.9 and the median seeing is below 0.7 arcsec. Initial KiDS observations have concentrated on the Galaxy and Mass Assembly (GAMA) regions near the celestial equator, where extensive, highly complete redshift catalogues are available. A total of 109 survey tiles, 1 square degree each, form the basis of the first set of lensing analyses of halo properties of GAMA galaxies. Nine galaxies per square arcminute enter the lensing analysis, for an effective inverse shear variance of 69 arcmin−2. Accounting for the shape measurement weight, the median redshift of the sources is 0.53. KiDS data processing follows two parallel tracks, one optimized for weak lensing measurement and one for accurate matched-aperture photometry (for photometric redshifts). This technical paper describes the lensing and photometric redshift measurements (including a detailed description of the Gaussian aperture and photometry pipeline), summarizes the data quality and presents extensive tests for systematic errors that might affect the lensing analyses. We also provide first demonstrations of the suitability of the data for cosmological measurements, and describe our blinding procedure for preventing confirmation bias in the scientific analyses. The KiDS catalogues presented in this paper are released to the community through http://kids.strw.leidenuniv.nl.

Serendipitous science from the K2 mission

AbstractThe K2 mission is a repurposed use of the Kepler spacecraft to perform high-precision photometry of selected fields in the ecliptic. We have developed an aperture photometry pipeline for K2 data which performs dynamic automated aperture mask selection, background estimation and subtraction, and positional decorrelation to minimize the effects of spacecraft pointing jitter. We also identify secondary targets in the K2 “postage stamps” and produce light curves for those targets as well. Pipeline results will be made available to the community. Here we describe our pipeline and the photometric precision we are capable of achieving with K2, and illustrate its utility with asteroseismic results from the serendipitous secondary targets.

THE SPITZER SURVEY OF STELLAR STRUCTURE IN GALAXIES (S 4 G): STELLAR MASSES, SIZES, AND RADIAL PROFILES FOR 2352 NEARBY GALAXIES

The Spitzer Survey of Stellar Structure in Galaxies is a volume, magnitude, and size-limited survey of 2352 nearby galaxies with deep imaging at 3.6 and 4.5 μm. In this paper, we describe our surface photometry pipeline and showcase the associated data products that we have released to the community. We also identify the physical mechanisms leading to different levels of central stellar mass concentration for galaxies with the same total stellar mass. Finally, we derive the local stellar mass–size relation at 3.6 μm for galaxies of different morphologies. Our radial profiles reach stellar mass surface densities below ~1 M⊙ pc^(-2). Given the negligible impact of dust and the almost constant mass-to-light ratio at these wavelengths, these profiles constitute an accurate inventory of the radial distribution of stellar mass in nearby galaxies. From these profiles we have also derived global properties such as asymptotic magnitudes (and the corresponding stellar masses), isophotal sizes and shapes, and concentration indices. These and other data products from our various pipelines (science-ready mosaics, object masks, 2D image decompositions, and stellar mass maps) can be publicly accessed at IRSA (http://irsa.ipac.caltech.edu/data/SPITZER/S4G/).