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تسجيل مستخدم جديدThe Palomar Transient Factory photometric catalog 1.0
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We construct a photometrically calibrated catalog of non-variable sources from the Palomar Transient Factory (PTF) observations. The first version of this catalog presented here, the PTF photometric catalog 1.0, contains calibrated R_PTF-filter magnitudes for about 21 million sources brighter than magnitude 19, over an area of about 11233 deg^2. The magnitudes are provided in the PTF photometric system, and the color of a source is required in order to convert these magnitudes into other magnitude systems. We estimate that the magnitudes in this catalog have typical accuracy of about 0.02 mag with respect to magnitudes from the Sloan Digital Sky Survey. The median repeatability of our catalogs magnitudes for stars between 15 and 16 mag, is about 0.01 mag, and it is better than 0.03 mag for 95% of the sources in this magnitude range. The main goal of this catalog is to provide reference magnitudes for photometric calibration of visible light observations. Subseque
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The search for fast optical transients, such as the expected electromagnetic counterparts to binary neutron star mergers, is riddled with false positives ranging from asteroids to stellar flares. While moving objects are readily rejected via image pa
irs separated by $sim$1 hr, stellar flares represent a challenging foreground that significantly outnumber rapidly-evolving explosions. Identifying stellar sources close to and fainter than the transient detection limit can eliminate these false positives. Here, we present a method to reliably identify stars in deep co-adds of Palomar Transient Factory (PTF) imaging. Our machine-learning methodology utilizes the random forest (RF) algorithm, which is trained using $> 3times{10}^6$ sources with Sloan Digital Sky Survey (SDSS) spectra. When evaluated on an independent test set, the PTF RF model outperforms the SExtractor star classifier by $sim$4%. For faint sources ($rge{21}$ mag), which dominate the field population, the PTF RF model produces a $sim$19% improvement over SExtractor. To avoid false negatives in the PTF transient-candidate stream, we adopt a conservative stellar classification threshold, corresponding to a galaxy misclassification rate = 0.005. Ultimately, $sim$$1.70times{10}^8$ objects are included in our PTF point-source catalog, of which only $sim$$10^6$ are expected to be galaxies. We demonstrate that the PTF RF catalog reveals transients that otherwise would have been missed. To leverage its superior image quality, we additionally create an SDSS point-source catalog, which is also tuned to have a galaxy misclassification rate = 0.005. These catalogs have been incorporated into the PTF real-time pipelines to automatically reject stellar sources as non-extragalactic transients.
We present results of the Sky2Night project: a systematic, unbiased search for fast optical transients with the Palomar Transient Factory. We have observed 407 deg$^2$ in $R$-band for 8 nights at a cadence of 2 hours. During the entire duration of th
e project, the 4.2m William Herschel Telescope on La Palma was dedicated to obtaining identification spectra for the detected transients. During the search, we found 12 supernovae, 10 outbursting cataclysmic variables, 9 flaring M-stars, 3 flaring active Galactic nuclei and no extragalactic fast optical transients. Using this systematic survey for transients, we have calculated robust observed rates for the detected types of transients, and upper limits of the rate of extragalactic fast optical transients of $mathcal{R}<37times 10^{-4}$deg$^{-2}$d$^{-1}$ and $mathcal{R}<9.3times 10^{-4}$deg$^{-2}$d$^{-1}$ for timescales of 4h and 1d and a limiting magnitude of $Rapprox19.7$. We use the results of this project to determine what kind of and how many astrophysical false positives we can expect when following up gravitational wave detections in search for kilonovae.
The Palomar Transient Factory (PTF) is a fully-automated, wide-field survey aimed at a systematic exploration of the optical transient sky. The transient survey is performed using a new 8.1 square degree camera installed on the 48-inch Samuel Oschin
telescope at Palomar Observatory; colors and light curves for detected transients are obtained with the automated Palomar 60-inch telescope. PTF uses eighty percent of the 1.2-m and fifty percent of the 1.5-m telescope time. With an exposure of 60-s the survey reaches a depth of approximately 21.3 in g and 20.6 in R (5 sigma, median seeing). Four major experiments are planned for the five-year project: 1) a 5-day cadence supernova search; 2) a rapid transient search with cadences between 90 seconds and 1 day; 3) a search for eclipsing binaries and transiting planets in Orion; and 4) a 3-pi sr deep H-alpha survey. PTF provides automatic, realtime transient classification and follow up, as well as a database including every source detected in each frame. This paper summarizes the PTF project, including several months of on-sky performance tests of the new survey camera, the observing plans and the data reduction strategy. We conclude by detailing the first 51 PTF optical transient detections, found in commissioning data.
The Palomar Transient Factory (PTF) is a multi-epochal robotic survey of the northern sky that acquires data for the scientific study of transient and variable astrophysical phenomena. The camera and telescope provide for wide-field imaging in optica
l bands. In the five years of operation since first light on December 13, 2008, images taken with Mould-R and SDSS-g camera filters have been routinely acquired on a nightly basis (weather permitting), and two different H-alpha filters were installed in May 2011 (656 nm and 663 nm). The PTF image-processing and data-archival program at the Infrared Processing and Analysis Center (IPAC) is tailored to receive and reduce the data, and, from it, generate and preserve astrometrically and photometrically calibrated images, extracted source catalogs, and coadded reference images. Relational databases have been deployed to track these products in operations and the data archive. The fully automated system has benefited by lessons learned from past IPAC projects and comprises advantageous features that are potentially incorporable into other ground-based observatories. Both off-the-shelf and in-house software have been utilized for economy and rapid development. The PTF data archive is curated by the NASA/IPAC Infrared Science Archive (IRSA). A state-of-the-art custom web interface has been deployed for downloading the raw images, processed images, and source catalogs from IRSA. Access to PTF data products is currently limited to an initial public data release (M81, M44, M42, SDSS Stripe 82, and the Kepler Survey Field). It is the intent of the PTF collaboration to release the full PTF data archive when sufficient funding becomes available.
We describe the near real-time transient-source discovery engine for the intermediate Palomar Transient Factory (iPTF), currently in operations at the Infrared Processing and Analysis Center (IPAC), Caltech. We coin this system the IPAC/iPTF Discover
y Engine (or IDE). We review the algorithms used for PSF-matching, image subtraction, detection, photometry, and machine-learned (ML) vetting of extracted transient candidates. We also review the performance of our ML classifier. For a limiting signal-to-noise ratio of 4 in relatively unconfused regions, bogus candidates from processing artifacts and imperfect image subtractions outnumber real transients by ~ 10:1. This can be considerably higher for image data with inaccurate astrometric and/or PSF-matching solutions. Despite this occasionally high contamination rate, the ML classifier is able to identify real transients with an efficiency (or completeness) of ~ 97% for a maximum tolerable false-positive rate of 1% when classifying raw candidates. All subtraction-image metrics, source features, ML probability-based real-bogus scores, contextual metadata from other surveys, and possible associations with known Solar System objects are stored in a relational database for retrieval by the various science working groups. We review our efforts in mitigating false-positives and our experience in optimizing the overall system in response to the multitude of science projects underway with iPTF.
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