Palomar Transient Factory Data Research Articles

Galaxy optical variability of Virgo cluster: new tracer for environmental influences on galaxies

ABSTRACT We investigate the relationship between the optical variability of galaxies and their distances from the centre of the Virgo cluster using Palomar Transient Factory data. We define the ratio between the standard deviation of the galaxy brightness and the mean value of the standard deviation as a measure of a galaxy’s optical variability. A sample of 814 Virgo galaxies with 230 263 observations shows a monotonically decreasing trend of optical variability with increasing clustercentric distance. The variability level inside the cluster is 3.2σ higher than the level outside. We fit the variability with a linear function and find that the data reject a distance-independent model. We examine 217 background galaxies for comparison and find no significant trend in galaxy variability. We assess the relation with Monte Carlo simulation by rebuilding the brightness of each galaxy. The simulation shows a monotonically decreasing relation for member galaxy variability and a distance-independent relation for background galaxies. Our result is consistent with the theory that the cold gas flowing inwards the cluster centre fuels AGN activity. This work is a new implementation of the method using optical variability to investigate the relation between galaxies evolution and their environment.

A new and unusual LBV-like outburst from a Wolf–Rayet star in the outskirts of M33

ABSTRACT MCA-1B (also called UIT003) is a luminous hot star in the western outskirts of M33, classified over 20 yr ago with a spectral type of Ofpe/WN9 and identified then as a candidate luminous blue variable (LBV). Palomar Transient Factory data reveal that this star brightened in 2010, with a light curve resembling that of the classic LBV star AF And in M31. Other Ofpe/WN9 stars have erupted as LBVs, but MCA-1B was unusual because it remained hot. It showed a WN-type spectrum throughout its eruption, whereas LBVs usually get much cooler. MCA-1B showed an almost four-fold increase in bolometric luminosity and a doubling of its radius, but its temperature stayed ≳29 kK. As it faded, it shifted to even hotter temperatures, exhibiting a WN7/WN8-type spectrum, and doubling its wind speed. MCA-1B is reminiscent of some supernova impostors, and its location resembles the isolated environment of SN 2009ip. It is most similar to HD 5980 (in the Small Magellanic Cloud) and GR 290 (also in M33). Whereas these two LBVs exhibited B-type spectra in eruption, MCA-1B is the first clear case where a Wolf–Rayet (WR) spectrum persisted at all times. Together, MCA-1B, HD 5980, and GR 290 constitute a class of WN-type LBVs, distinct from S Doradus LBVs. They are most interesting in the context of LBVs at low metallicity, a possible post-LBV/WR transition in binaries, and as likely Type Ibn supernova progenitors.

Identification of Stellar Flares Using Differential Evolution Template Optimization

Abstract We explore methods for the identification of stellar flare events in irregularly sampled data of ground-based time domain surveys. In particular, we describe a new technique for identifying flaring stars, which we have implemented in a publicly available Python module called “PyVAN.” The approach uses the Differential Evolution algorithm to optimize parameters of empirically derived light curve templates for different types of stars to fit a candidate light curve. The difference of the likelihoods that these best-fit templates produced the observed data is then used to delineate targets that are well-explained by a flare template but simultaneously poorly explained by templates of common contaminants. By testing on light curves of known identity and morphology, we show that our technique is capable of recovering flaring status in 69% of all light curves containing a flare event above thresholds drawn to include <1% of any contaminant population. By applying to Palomar Transient Factory data, we show consistency with prior samples of flaring stars, and identify a small selection of candidate flaring G-type stars for possible follow-up.

Testing the Binary Hypothesis: Pulsar Timing Constraints on Supermassive Black Hole Binary Candidates

Abstract The advent of time domain astronomy is revolutionizing our understanding of the universe. Programs such as the Catalina Real-time Transient Survey (CRTS) or the Palomar Transient Factory (PTF) surveyed millions of objects for several years, allowing variability studies on large statistical samples. The inspection of ≈250 k quasars in CRTS resulted in a catalog of 111 potentially periodic sources, put forward as supermassive black hole binary (SMBHB) candidates. A similar investigation on PTF data yielded 33 candidates from a sample of ≈35 k quasars. Working under the SMBHB hypothesis, we compute the implied SMBHB merger rate and we use it to construct the expected gravitational wave background (GWB) at nano-Hz frequencies, probed by pulsar timing arrays (PTAs). After correcting for incompleteness and assuming virial mass estimates, we find that the GWB implied by the CRTS sample exceeds the current most stringent PTA upper limits by almost an order of magnitude. After further correcting for the implicit bias in virial mass measurements, the implied GWB drops significantly but is still in tension with the most stringent PTA upper limits. Similar results hold for the PTF sample. Bayesian model selection shows that the null hypothesis (whereby the candidates are false positives) is preferred over the binary hypothesis at about 2.3σ and 3.6σ for the CRTS and PTF samples respectively. Although not decisive, our analysis highlights the potential of PTAs as astrophysical probes of individual SMBHB candidates and indicates that the CRTS and PTF samples are likely contaminated by several false positives.

The space density of post-period minimum Cataclysmic Variables

Binary evolution theory predicts that accreting white dwarfs with sub-stellar companions dominate the Galactic population of cataclysmic variables (CVs). In order to test these predictions, it is necessary to identify these systems, which may be difficult if the signatures of accretion become too weak to be detected. The only chance to identify such "dead" CVs is by exploiting their close binary nature. We have therefore searched the Sloan Digital Sky Survey (SDSS) Stripe 82 area for apparently isolated white dwarfs that undergo eclipses by a dark companion. We found no such eclipses in either the SDSS or Palomar Transient Factory data sets among our sample of 2264 photometrically selected white dwarf candidates within Stripe 82. This null result allows us to set a firm upper limit on the space density, $\rho_0$, of dead CVs. In order to determine this limit, we have used Monte-Carlo simulations to fold our selection criteria through a simple model of the Galactic CV distribution. Assuming a $T_{WD}=7,500$ K, the resulting 2$\sigma$ limit on the space density of dead CVs is $\rho_0 \lesssim 2 \times 10^{-5}$ pc$^{-3}$, where $T_{WD}$ is the typical effective temperature of the white dwarf in such systems.

Real-time Recovery Efficiencies and Performance of the Palomar Transient Factory’s Transient Discovery Pipeline

Abstract We present the transient source detection efficiencies of the Palomar Transient Factory (PTF), parameterizing the number of transients that PTF found versus the number of similar transients that occurred over the same period in the survey search area but were missed. PTF was an optical sky survey carried out with the Palomar 48 inch telescope over 2009–2012, observing more than 8000 square degrees of sky with cadences of between one and five days, locating around 50,000 non-moving transient sources, and spectroscopically confirming around 1900 supernovae. We assess the effectiveness with which PTF detected transient sources, by inserting million artificial point sources into real PTF data. We then study the efficiency with which the PTF real-time pipeline recovered these sources as a function of the source magnitude, host galaxy surface brightness, and various observing conditions (using proxies for seeing, sky brightness, and transparency). The product of this study is a multi-dimensional recovery efficiency grid appropriate for the range of observing conditions that PTF experienced and that can then be used for studies of the rates, environments, and luminosity functions of different transient types using detailed Monte Carlo simulations. We illustrate the technique using the observationally well-understood class of type Ia supernovae.

How to COAAD Images. I. Optimal Source Detection and Photometry of Point Sources Using Ensembles of Images

Abstract Stacks of digital astronomical images are combined in order to increase image depth. The variable seeing conditions, sky background, and transparency of ground-based observations make the coaddition process nontrivial. We present image coaddition methods that maximize the signal-to-noise ratio (S/N) and optimized for source detection and flux measurement. We show that for these purposes, the best way to combine images is to apply a matched filter to each image using its own point-spread function (PSF) and only then to sum the images with the appropriate weights. Methods that either match the filter after coaddition or perform PSF homogenization prior to coaddition will result in loss of sensitivity. We argue that our method provides an increase of between a few and 25% in the survey speed of deep ground-based imaging surveys compared with weighted coaddition techniques. We demonstrate this claim using simulated data as well as data from the Palomar Transient Factory data release 2. We present a variant of this coaddition method, which is optimal for PSF or aperture photometry. We also provide an analytic formula for calculating the S/N for PSF photometry on single or multiple observations. In the next paper in this series, we present a method for image coaddition in the limit of background-dominated noise, which is optimal for any statistical test or measurement on the constant-in-time image (e.g., source detection, shape or flux measurement, or star–galaxy separation), making the original data redundant. We provide an implementation of these algorithms in MATLAB.

THE PALOMAR TRANSIENT FACTORY AND RR LYRAE: THE METALLICITY–LIGHT CURVE RELATION BASED ON AB-TYPE RR LYRAE IN THE KEPLER FIELD

ABSTRACT The wide-field synoptic sky surveys, known as the Palomar Transient Factory (PTF) and the intermediate Palomar Transient Factory (iPTF), will accumulate a large number of known and new RR Lyrae. These RR Lyrae are good tracers to study the substructure of the Galactic halo if their distance, metallicity, and galactocentric velocity can be measured. Candidates of halo RR Lyrae can be identified from their distance and metallicity before requesting spectroscopic observations for confirmation. This is because both quantities can be obtained via their photometric light curves, because the absolute V-band magnitude for RR Lyrae is correlated with metallicity, and the metallicity can be estimated using a metallicity–light curve relation. To fully utilize the PTF and iPTF light-curve data in related future work, it is necessary to derive the metallicity–light curve relation in the native PTF/iPTF R-band photometric system. In this work, we derived such a relation using the known ab-type RR Lyrae located in the Kepler field, and it is found to be (where P is pulsational period and is one of the Fourier parameters describing the shape of the light curve), with a dispersion of 0.118 dex. We tested our metallicity–light curve relation with new spectroscopic observations of a few RR Lyrae in the Kepler field, as well as several data sets available in the literature. Our tests demonstrated that the derived metallicity–light curve relation could be used to estimate metallicities for the majority of the RR Lyrae, which are in agreement with the published values.

IPAC Image Processing and Data Archiving for the Palomar Transient Factory

The Palomar Transient Factory (PTF) is a multiepochal 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 optical bands. In the five years of operation since first light on 2008 December 13, images taken with Mould-R and SDSS-g′ camera filters have been routinely acquired on a nightly basis (weather permitting), and two different Hα filters were installed in 2011 May (656 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 co-added 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.

Connection between optical and γ-ray variability in blazars

We use optical data from the Palomar Transient Factory (PTF) and the Catalina Real-Time Transient Survey (CRTS) to study the variability of gamma-ray detected and non-detected objects in a large population of active galactic nuclei (AGN) selected from the Candidate Gamma-Ray Blazar Survey and Fermi Gamma-Ray Space Telescope catalogs. Our samples include 714 sources with PTF data and 1244 sources with CRTS data. We calculate the intrinsic modulation index to quantify the optical variability amplitude in these samples. We find the gamma-ray detected objects to be more variable than the non-detected ones. The flat spectrum radio quasars (FSRQs) are more variable than the BL Lac objects in our sample, but the significance of the difference depends on the sample used. When dividing the objects based on their synchrotron peak frequency, we find the low synchrotron peaked (LSP) objects to be significantly more variable than the high synchrotron peaked (HSP) ones, explaining the difference between the FSRQs and BL Lacs. This could be due to the LSPs being observed near their electron energy peak, while in the HSPs the emission is caused by lower energy electrons, which cool more slowly. We also find a significant correlation between the optical and gamma-ray fluxes that is stronger in the HSP BL Lacs than in the FSRQs. The FSRQs in our sample are also more Compton dominated than the HSP BL Lacs. These findings are consistent with models where the gamma-ray emission of HSP objects is produced by the synchrotron self-Compton mechanism, while the LSP objects need an additional external Compton component that increases the scatter in the flux-flux correlation.

STATISTICAL SEARCHES FOR MICROLENSING EVENTS IN LARGE, NON-UNIFORMLY SAMPLED TIME-DOMAIN SURVEYS: A TEST USING PALOMAR TRANSIENT FACTORY DATA

Many photometric time-domain surveys are driven by specific goals, such as searches for supernovae or transiting exoplanets, which set the cadence with which fields are re-imaged. In the case of the Palomar Transient Factory (PTF), several sub-surveys are conducted in parallel, leading to non-uniform sampling over its $\sim$$20,000 \mathrm{deg}^2$ footprint. While the median $7.26 \mathrm{deg}^2$ PTF field has been imaged $\sim$40 times in \textit{R}-band, $\sim$$2300 \mathrm{deg}^2$ have been observed $>$100 times. We use PTF data to study the trade-off between searching for microlensing events in a survey whose footprint is much larger than that of typical microlensing searches, but with far-from-optimal time sampling. To examine the probability that microlensing events can be recovered in these data, we test statistics used on uniformly sampled data to identify variables and transients. We find that the von Neumann ratio performs best for identifying simulated microlensing events in our data. We develop a selection method using this statistic and apply it to data from fields with $>$10 $R$-band observations, $1.1\times10^9$ light curves, uncovering three candidate microlensing events. We lack simultaneous, multi-color photometry to confirm these as microlensing events. However, their number is consistent with predictions for the event rate in the PTF footprint over the survey's three years of operations, as estimated from near-field microlensing models. This work can help constrain all-sky event rate predictions and tests microlensing signal recovery in large data sets, which will be useful to future time-domain surveys, such as that planned with the Large Synoptic Survey Telescope.

Automating Discovery and Classification of Transients and Variable Stars in the Synoptic Survey Era

ABSTRACTThe rate of image acquisition in modern synoptic imaging surveys has already begun to outpace the feasibility of keeping astronomers in the real-time discovery and classification loop. Here we present the inner workings of a framework, based on machine-learning algorithms, that captures expert training and ground-truth knowledge about the variable and transient sky to automate (1) the process of discovery on image differences, and (2) the generation of preliminary science-type classifications of discovered sources. Since follow-up resources for extracting novel science from fast-changing transients are precious, self-calibrating classification probabilities must be couched in terms of efficiencies for discovery and purity of the samples generated. We estimate the purity and efficiency in identifying real sources with a two-epoch image-difference discovery algorithm for the Palomar Transient Factory (PTF) survey. Once given a source discovery, using machine-learned classification trained on PTF data, we distinguish between transients and variable stars with a 3.8% overall error rate (with 1.7% errors for imaging within the Sloan Digital Sky Survey footprint). At >96% classification efficiency, the samples achieve 90% purity. Initial classifications are shown to rely primarily on context-based features, determined from the data itself and external archival databases. In the first year of autonomous operations of PTF, this discovery and classification framework led to several significant science results, from outbursting young stars to subluminous Type IIP supernovae to candidate tidal disruption events. We discuss future directions of this approach, including the possible roles of crowdsourcing and the scalability of machine learning to future surveys such as the Large Synoptic Survey Telescope (LSST).

THE PTF ORION PROJECT: A POSSIBLE PLANET TRANSITING A T-TAURI STAR

We report observations of a possible young transiting planet orbiting a previously known weak-lined T-Tauri star in the 7-10 Myr old Orion-OB1a/25-Ori region. The candidate was found as part of the Palomar Transient Factory (PTF) Orion project. It has a photometric transit period of 0.448413 +- 0.000040 days, and appears in both 2009 and 2010 PTF data. Follow-up low-precision radial velocity (RV) observations and adaptive optics imaging suggest that the star is not an eclipsing binary, and that it is unlikely that a background source is blended with the target and mimicking the observed transit. RV observations with the Hobby-Eberly and Keck telescopes yield an RV that has the same period as the photometric event, but is offset in phase from the transit center by approximately -0.22 periods. The amplitude (half range) of the RV variations is 2.4 km/s and is comparable with the expected RV amplitude that stellar spots could induce. The RV curve is likely dominated by stellar spot modulation and provides an upper limit to the projected companion mass of M_p sin i_orb < 4.8 +- 1.2 M_Jup; when combined with the orbital inclination, i orb, of the candidate planet from modeling of the transit light curve, we find an upper limit on the mass of the planetary candidate of M_p < 5.5 +- 1.4 M_Jup. This limit implies that the planet is orbiting close to, if not inside, its Roche limiting orbital radius, so that it may be undergoing active mass loss and evaporation.

Asteroid rotation periods from the Palomar Transient Factory survey

The Palomar Transient Factory (PTF) is a synoptic survey designed to explore the transient and variable sky in a wide variety of cadences. We use PTF observations of fields that were observed multiple times (>=10) per night, for several nights, to find asteroids, construct their lightcurves and measure their rotation periods. Here we describe the pipeline we use to achieve these goals and present the results from the first four (overlapping) PTF fields analyzed as part of this program. These fields, which cover an area of 21 deg^2, were observed on four nights with a cadence of ~20 min. Our pipeline was able to detect 624 asteroids, of which 145 (~20%) were previously unknown. We present high quality rotation periods for 88 main-belt asteroids and possible period or lower limit on the period for an additional 85 asteroids. For the remaining 451 asteroids, we present lower limits on their photometric amplitudes. Three of the asteroids have lightcurves that are characteristic of binary asteroids. We estimate that implementing our search for all existing high-cadence PTF data will provide rotation periods for about 10,000 asteroids mainly in the magnitude range ~14 to ~20.

The Palomar Transient Factory Photometric Calibration

ABSTRACTThe Palomar Transient Factory (PTF) provides multiple epoch imaging for a large fraction of the celestial sphere. Here, we describe the photometric calibration of the PTF data products that allows the PTF magnitudes to be related to other magnitude systems. The calibration process utilizes Sloan Digital Sky Survey (SDSS) r ∼ 16 mag point-source objects as photometric standards. During photometric conditions, this allows us to solve for the extinction coefficients and color terms and to estimate the camera illumination correction. This also enables the calibration of fields that are outside the SDSS footprint. We test the precision and repeatability of the PTF photometric calibration. Given that PTF is observing in a single filter each night, we define a PTF calibrated magnitude system for the R band and g band. We show that, in this system, ≈59% (47%) of the photometrically calibrated PTF R-band (g-band) data achieve a photometric precision of 0.02–0.04 mag and have color terms and extinction coefficients that are close to their average values. Given the objects’ color, the PTF magnitude system can be converted to other systems. Moreover, a night-by-night comparison of the calibrated magnitudes of individual stars observed on multiple nights shows that they are consistent to a level of ≈0.02 mag. Most of the data that were taken under nonphotometric conditions can be calibrated relative to other epochs of the same sky footprint obtained during photometric conditions. We provide a concise guide describing how to use the PTF photometric-calibration data products, as well as the transformations between the PTF magnitude system and the SDSS and Johnson-Cousins systems.

CORE-COLLAPSE SUPERNOVAE FROM THE PALOMAR TRANSIENT FACTORY: INDICATIONS FOR A DIFFERENT POPULATION IN DWARF GALAXIES

We use the first compilation of 72 core-collapse supernovae (SNe) from the Palomar Transient Factory (PTF) to study their observed subtype distribution in dwarf galaxies compared to giant galaxies. Our sample is the largest single-survey, untargeted, spectroscopically classified, homogeneous collection of core-collapse events ever assembled, spanning a wide host-galaxy luminosity range (down to M_r ~ -14 mag) and including a substantial fraction (>20%) of dwarf (M_r >= -18 mag) hosts. We find more core-collapse SNe in dwarf galaxies than expected and several interesting trends emerge. We use detailed subclassifications of stripped-envelope core-collapse SNe and find that all Type I core-collapse events occurring in dwarf galaxies are either SNe Ib or broad-lined SNe Ic (SNe Ic-BL), while "normal" SNe Ic dominate in giant galaxies. We also see a significant excess of SNe IIb in dwarf hosts. We hypothesize that in lower metallicity hosts, metallicity-driven mass loss is reduced, allowing massive stars that would have appeared as "normal" SNe Ic in metal-rich galaxies to retain some He and H, exploding as Ib/IIb events. At the same time, another mechanism allows some stars to undergo extensive stripping and explode as SNe Ic-BL (and presumably also as long-duration gamma-ray bursts). Our results are still limited by small-number statistics, and our measurements of the observed N(Ib/c)/N(II) number ratio in dwarf and giant hosts (0.25_{-0.15}^{+0.3} and 0.23_{-0.08}^{+0.11}, respectively; 1 sigma uncertainties) are consistent with previous studies and theoretical predictions. As additional PTF data accumulate, more robust statistical analyses will be possible, allowing the evolution of massive stars to be probed via the dwarf-galaxy SN population.