J/ApJ/698/895 Variations in QSOs optical flux (Kelly+, 2009)
Are the variations in quasar optical flux driven by thermal fluctuations? Kelly B.C., Bechtold J., Siemiginowska A. <Astrophys. J., 698, 895-910 (2009)> =2009ApJ...698..895K
ADC_Keywords: QSOs ; Active gal. nuclei ; Models Keywords: accretion, accretion disks - galaxies: active - methods: data analysis - quasars: general Abstract: We analyze a sample of optical light curves, compiled from the literature, for 100 quasars, 70 of which have black hole mass estimates. Our sample is the largest and broadest used yet for modeling quasar variability. The sources in our sample have z<2.8, 1042≲λLλ(5100Å)≲1046, and 106≲MBH/M☉≲1010. We model the light curves as a continuous time stochastic process, providing a natural means of estimating the characteristic timescale and amplitude of quasar variations. We employ a Bayesian approach to estimate the characteristic timescale and amplitude of flux variations; our approach is not affected by biases introduced from discrete sampling effects. Description: Our sample consists of 55 AGNs from the MACHO survey (Geha et al. 2003AJ....125....1G), 37 Palomar Green (PG) quasars from the sample of Giveon et al. (1999MNRAS.306..637G), and eight Seyfert galaxies from the AGN Watch database (http://www.astronomy.ohio-state.edu/~agnwatch/). File Summary:
FileName Lrecl Records Explanations
ReadMe 80 . This file table1.dat 48 109 Quasars analyzed in this work (table from erratum 2011, ApJ, 732, 128) table2.dat 50 109 Results from CAR(1) process fits to quasar light curves (table from erratum 2011, ApJ, 732, 128)
See also: J/ApJS/185/156 : The Lick AGN monitoring project (Walsh+, 2009) J/ApJ/625/78 : QSOs properties (Hao+, 2005) J/A+A/369/57 : Monitoring Mkn 279 in BVRI and Hβ fluxes (Santos-Lleo+, 2001) J/ApJ/269/352 : Quasar evolution (Schmidt+, 1983) http://www.astronomy.ohio-state.edu/~agnwatch/ : AGN Watch Website Byte-by-byte Description of file: table1.dat
Bytes Format Units Label Explanations
1- 2 I2 h RAh Hour of Right Ascension (J2000) 4- 5 I2 min RAm Minute of Right Ascension (J2000) 7- 10 F4.1 s RAs Second of Right Ascension (J2000) 12 A1 --- DE- Sign of the Declination (J2000) 13- 14 I2 deg DEd Degree of Declination (J2000) 16- 17 I2 arcmin DEm Arcminute of Declination (J2000) 19- 22 F4.1 arcsec DEs Arcsecond of Declination (J2000) 24- 28 F5.3 --- z Redshift 30- 34 F5.2 [10-7W] logL5100 Log of monochromatic luminosity at 5100Å 36- 40 F5.2 [Msun] logMBH ? Log of Blackhole mass 42- 45 F4.2 [Msun] e_logMBH ? The 1σ error in logMBH 47- 48 I2 --- Ref Optical light curve reference (1)
Note (1): Reference as follows: 1 = Giveon et al. (1999MNRAS.306..637G); 2 = Geha et al. (2003AJ....125....1G); 3 = Stirpe et al. (1994ApJ...425..609S); 4 = Peterson et al. (2000ApJ...542..161P); 5 = Kaspi et al. (1996ApJ...470..336K); 6 = Santos-Lleo et al. (2001, Cat. J/A+A/369/57); 7 = Peterson et al. (2002ApJ...581..197P); 8 = Carone et al. (1996ApJ...471..737C); 9 = Shemmer et al. (2001ApJ...561..162S; <[SRB2001] N> in Simbad); 10 = Collier et al. (1998ApJ...500..162C).
Byte-by-byte Description of file: table2.dat
Bytes Format Units Label Explanations
1- 2 I2 h RAh Hour of Right Ascension (J2000) 4- 5 I2 min RAm Minute of Right Ascension (J2000) 7- 10 F4.1 s RAs Second of Right Ascension (J2000) 12 A1 --- DE- Sign of the Declination (J2000) 13- 14 I2 deg DEd Degree of Declination (J2000) 16- 17 I2 arcmin DEm Arcminute of Declination (J2000) 19- 22 F4.1 arcsec DEs Arcsecond of Declination (J2000) 24- 27 F4.2 [d] logtau ? Log of characteristic time scale τ of the quasar lightcurve (1) 29 A1 --- f_logtau [c] poor fit (2) 31- 34 F4.2 [d] e_logtau ? Lower 95% confidence interval in logtau 36- 39 F4.2 [d] E_logtau ? Upper 95% confidence interval in logtau 41- 45 F5.2 [---] logsig ? Log of standard deviation in the input process to Equation 1 (1) 47- 50 F4.2 [---] e_logsig ? The error in logsigma
Note (1): In this work, we model quasar light curves as a continuous time first-order autoregressive process (CAR(1)). The CAR(1) process is described by the following stochastic differential equation (e.g., Brockwell & Davis 2002, Introduction to Time Series and Forecasting, 2nd ed. (New York: Springer)): dX(t)=-(1/τ)X(t)dt+σ(dtε(t))0.5+bdt, τ,σ,t>0 Here, τ is called the "relaxation time" of the process X(t), and ε(t) is a white noise process with zero mean and variance equal to 1. Within the context of this work, X(t) is the quasar flux. The relaxation time, τ, can be interpreted as the time required for the time series to become roughly uncorrelated, and σ can be interpreted as describing the variability of the time series on timescales short compared to τ. The standard deviation of quasar flux variations on time scales of 1 day is expected to be equal to σ. See section 3 for further details. Note (2): c = The CAR(1) process provided a poor fit to these lightcurves, and the data was not used in our regression analysis.
History: From electronic version of the journal
(End) Greg Schwarz [AAS], Emmanuelle Perret [CDS] 09-Jun-2011
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