Correlated radio/gamma-ray variability  The hypothesis of correlated variability in radio and gamma-ray is popular  It would indicate a common spatial origin for radio and gamma-ray emission  But it needs to be proven!

Correlated radio/gamma-ray variability  Our approach:  Large sample of objects  Preselected as gamma-ray candidates  Observed independently of gamma-ray state  High cadence, observed twice per week  Statistical tests for correlations

A first look at the radio/gamma-ray cross-correlation  Data  Radio data published in Richards et al 2011 (ApJ submitted)  2 year light curves for CGRaBS sources + a few calibrators  Gamma-ray data published in blazar variability paper, Abdo et al ApJ, 722, 520  106 sources  11-month light curves, weekly sampling  52/106 are in the CGRaBS sample

Radio lags Radio precedes Example cross-correlations. 3-month Fermi detections, using 11-months of Fermi data and 2 years of radio monitoring β _radio = 2.5, β _gamma = 2.0 Significance evaluated using simulated data with a power-law PSD ~ 1/f^ β Radio/gamma-ray time lags and their significance

Radio lags Radio precedes Example cross-correlations. 3-month Fermi detections, using 11-months of Fermi data and 2 years of radio monitoring β _radio = 2.5, β _gamma = 2.0 Significance evaluated using simulated data with a power-law PSD ~ 1/f^ β Radio/gamma-ray time lags and their significance

Statistical test for the cross-correlation: Measuring the PSD  The significance level depends on the model used for the light curves  It is commonly assumed that it is red-noise with a simple power-law PSD  Uneven sampling complicates the model fitting  We use the method of Uttley et al 2002 MNRAS 332, 231  With some modifications  Basic idea is to simulate data with a given PSD and process it as the data. The mean PSDs and deviations are used for model fitting

β radio = 2.5, β gamma-ray = 2.0 β radio = 2.0, β gamma-ray = 1.5 β radio = 0.0, β gamma-ray = 0.0 Significance versus PSD power-law exponent

Significance for longer time seriesSignificance for longer time series  1 year of gamma-ray and 2 years of radio – dotted lines  5 years of gamma-ray and 6 years of radio – solid lines

Statistical test for the cross-correlation: Measuring the PSD J J Example light curves Goodness of fit –radio data Some PSDs are hard to constrain, we need longer time series A large fraction have well constrained PSDs slopes β β n>/N

PSD measurements first resultsPSD measurements first results  The distribution of PSD power-law indices is different for gamma-ray detected/non- detected sources  This is consistent with gamma-ray quiet objects looking like white noise, without flares  A peak near beta~2.0 can be used when measuring significance Gamma-ray detected Gamma-ray non detected

Cross-correlation the next stepCross-correlation the next step  Include all sources on 1LAC ( Fermi first year catalog) with 2 years of data in gamma-ray and at least 2 years in radio, more for CGRaBS  Main problem is to extract all the gamma-ray light curves and deal with upper limits, sparse or adaptive sampling  ~400 sources in our program  221 CGRaBS 

Summary  Paper in preparation using published Fermi and OVRO data  PSD is characterized for all radio sources  Cross-correlation significance will incorporate this new constraints on the variability behavior of blazars  Will submit before Fermi Symposium  Next step is to extend this to a larger set of gamma-ray sources and longer light curves at both bands