Quasar Selection Based on Photometric Variability

We develop a method for separating quasars from other variable point sources using SDSS Stripe 82 light curve data for ~10,000 variable objects. To statistically describe quasar variability, we use a damped random walk model parametrized by a damping time scale, tau, and an asymptotic amplitude (structure function), SF_inf. With the aid of an SDSS spectroscopically confirmed quasar sample, we demonstrate that variability selection in typical extragalactic fields with low stellar density can deliver complete samples with reasonable purity (or efficiency, E). Compared to a selection method based solely on the slope of the structure function, the inclusion of the tau information boosts E from 60% to 75% while maintaining a highly complete sample (98%) even in the absence of color information. For a completeness of C=90%, E is boosted from 80% to 85%. Conversely, C improves from 90% to 97% while maintaining E=80% when imposing a lower limit on tau. With the aid of color selection, the purity can be further boosted to 96%, with C= 93%. Hence, selection methods based on variability will play an important role in the selection of quasars with data provided by upcoming large sky surveys, such as Pan-STARRS and the Large Synoptic Survey Telescope (LSST). For a typical (simulated) LSST cadence over 10 years and a photometric accuracy of 0.03 mag (achieved at i~22), C is expected to be 88% for a simple sample selection criterion of tau>100 days. In summary, given an adequate survey cadence, photometric variability provides an even better method than color selection for separating quasars from stars.Comment: (v2) 50 pages, accepted to Ap

Improving selection stability of multiple testing procedures for fMRI

In search of an appropriate thresholding technique in the analysis of functional MRI-data, several methods to prevent an inflation of false positives have been proposed. Two popular (voxelwise) methods are the Bonferroni procedure (BF), which controls the familywise error rate (FWER), and the Benjamini-Hochberg procedure (BH), which controls the false discovery rate (FDR) (Benjamini & Hochberg 1995). Multiple testing procedures are typically evaluated on their average performance with respect to error rates, ignoring the aspect of variability. Resampling techniques allow to assess the selection variability of individual features (voxels). Following the approach of Gordon, Chen, Glazko & Yakovlev (2009) in the context of gene selection, we investigated whether variability on test results for BF and BH can be reduced by including both the significance and selection variability of the voxels in the decision criterion

A new extensive catalog of optically variable AGN in the GOODS Fields and a new statistical approach to variability selection

Variability is a property shared by practically all AGN. This makes variability selection a possible technique for identifying AGN. Given that variability selection makes no prior assumption about spectral properties, it is a powerful technique for detecting both low-luminosity AGN in which the host galaxy emission is dominating and AGN with unusual spectral properties. In this paper, we will discuss and test different statistical methods for the detection of variability in sparsely sampled data that allow full control over the false positive rates. We will apply these methods to the GOODS North and South fields and present a catalog of variable sources in the z band in both GOODS fields. Out of 11931 objects checked, we find 155 variable sources at a significance level of 99.9%, corresponding to about 1.3% of all objects. After rejection of stars and supernovae, 139 variability selected AGN remain. Their magnitudes reach down as faint as 25.5 mag in z. Spectroscopic redshifts are available for 22 of the variability selected AGN, ranging from 0.046 to 3.7. The absolute magnitudes in the rest-frame z-band range from ~ -18 to -24, reaching substantially fainter than the typical luminosities probed by traditional X-ray and spectroscopic AGN selection in these fields. Therefore, this is a powerful technique for future exploration of the evolution of the faint end of the AGN luminosity function up to high redshifts.Comment: Accepted for publication in The Astrophysical Journal (version 2: minor changes to text after receiving comments

The QUEST-La Silla AGN Variability Survey: selection of AGN candidates through optical variability

We used data from the QUEST-La Silla Active Galactic Nuclei (AGN) variability survey to construct light curves for 208,583 sources over $\sim 70$ deg$^2$, with a a limiting magnitude $r \sim 21$. Each light curve has at least 40 epochs and a length of $\geq 200$ days. We implemented a Random Forest algorithm to classify our objects as either AGN or non-AGN according to their variability features and optical colors, excluding morphology cuts. We tested three classifiers, one that only includes variability features (RF1), one that includes variability features and also $r-i$ and $i-z$ colors (RF2), and one that includes variability features and also $g-r$, $r-i$, and $i-z$ colors (RF3). We obtained a sample of high probability candidates (hp-AGN) for each classifier, with 5,941 candidates for RF1, 5,252 candidates for RF2, and 4,482 candidates for RF3. We divided each sample according to their $g-r$ colors, defining blue ($g-r\leq 0.6$) and red sub-samples ($g-r>0.6$). We find that most of the candidates known from the literature belong to the blue sub-samples, which is not necessarily surprising given that, unlike for many literature studies, we do not cut our sample to point-like objects. This means that we can select AGN that have a significant contribution from redshifted starlight in their host galaxies. In order to test the efficiency of our technique we performed spectroscopic follow-up, confirming the AGN nature of 44 among 54 observed sources (81.5\% of efficiency). From the campaign we concluded that RF2 provides the purest sample of AGN candidates.Comment: Accepted for publication in The Astrophysical Journal Supplement Serie

Spectroscopic follow-up of variability-selected active galactic nuclei in the Chandra Deep Field South

Luminous AGNs are usually selected by their non-stellar colours or their X-ray emission. Colour selection cannot be used to select low-luminosity AGNs, since their emission is dominated by the host galaxy. Objects with low X-ray to optical ratio escape even the deepest X-ray surveys performed so far. In a previous study we presented a sample of candidates selected through optical variability in the Chandra Deep Field South, where repeated optical observations were performed for the STRESS supernova survey. We obtained new optical spectroscopy for a sample of variability selected candidates with the ESO NTT telescope. We analysed the new spectra, together with those existing in the literature and studied the distribution of the objects in U-B and B-V colours, optical and X-ray luminosity, and variability amplitude. A large fraction (17/27) of the observed candidates are broad-line luminous AGNs, confirming the efficiency of variability in detecting quasars. We detect: i) extended objects which would have escaped the colour selection and ii) objects of very low X-ray to optical ratio. Several objects resulted to be narrow-emission line galaxies where variability indicates nuclear activity, while no emission lines were detected in others. Some of these galaxies have variability and X-ray to optical ratio close to active galactic nuclei, while others have much lower variability and X-ray to optical ratio. This result can be explained by the dilution of the nuclear light due to the host galaxy. Our results demonstrate the effectiveness of supernova search programmes to detect large samples of low-luminosity AGNs. A sizable fraction of the AGN in our variability sample had escaped X-ray detection (5/47) and/or colour selection (9/48). Spectroscopic follow-up to fainter flux limits is strongly encouraged.Comment: 14 pages, 11 figures, to appear in A&

Development of bipedal and quadrupedal locomotion in humans from a dynamical systems perspective

The first phase in the development 0f locomotion, pr,öary variability would occur in normal fetuses and infants, and those with Uner Tan syndrome. The neural networks for quadrupedal locomotion have apparently been transmitted epigenetically through many species since about 400 MYA.\ud The second phase is the neuronal selection process. During infancy, the most effective motor pattern(s) and their associated neuronal group(s) are selected through experience.\ud The third phase, secondary or adaptive variability, starts to bloom at two to three years of age and matures in adolescence. This third phase may last much longer in some patients with Uner Tan syndrome, with a considerably delay in selection of the well-balanced quadrupedal locomotion, which may emerge very late in adolescence in these cases

Variability selected high-redshift quasars on SDSS Stripe 82

The SDSS-III BOSS Quasar survey will attempt to observe z>2.15 quasars at a density of at least 15 per square degree to yield the first measurement of the Baryon Acoustic Oscillations in the Ly-alpha forest. To help reaching this goal, we have developed a method to identify quasars based on their variability in the u g r i z optical bands. The method has been applied to the selection of quasar targets in the SDSS region known as Stripe 82 (the Southern equatorial stripe), where numerous photometric observations are available over a 10-year baseline. This area was observed by BOSS during September and October 2010. Only 8% of the objects selected via variability are not quasars, while 90% of the previously identified high-redshift quasar population is recovered. The method allows for a significant increase in the z>2.15 quasar density over previous strategies based on optical (ugriz) colors, achieving a density of 24.0 deg^{-2} on average down to g~22 over the 220 deg^2 area of Stripe 82. We applied this method to simulated data from the Palomar Transient Factory and from Pan-STARRS, and showed that even with data that have sparser time sampling than what is available in Stripe 82, including variability in future quasar selection strategies would lead to increased target selection efficiency in the z>2.15 redshift range. We also found that Broad Absorption Line quasars are preferentially present in a variability than in a color selection.Comment: 14 pages, 21 figures, accepted for publication in A&

A Synoptic, Multiwavelength Analysis of a Large Quasar Sample

We present variability and multi-wavelength photometric information for the 933 known quasars in the QUEST Variability Survey. These quasars are grouped into variable and non-variable populations based on measured variability confidence levels. In a time-limited synoptic survey, we detect an anti-correlation between redshift and the likelihood of variability. Our comparison of variability likelihood to radio, IR, and X-ray data is consistent with earlier quasar studies. Using already-known quasars as a template, we introduce a light curve morphology algorithm that provides an efficient method for discriminating variable quasars from periodic variable objects in the absence of spectroscopic information. The establishment of statistically robust trends and efficient, non-spectroscopic selection algorithms will aid in quasar identification and categorization in upcoming massive synoptic surveys. Finally, we report on three interesting variable quasars, including variability confirmation of the BL Lac candidate PKS 1222+037.Comment: AJ, accepted for publication 15 Dec 200