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Blazars in the Fermi Era: The OVRO 40-m Telescope Monitoring Program
The Large Area Telescope (LAT) aboard the Fermi Gamma-ray Space Telescope provides an unprecedented opportunity to study gamma-ray blazars. To capitalize on this opportunity, beginning in late 2007, about a year before the start of LAT science operations, we began a large-scale, fast-cadence 15 GHz...
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Published in: | arXiv.org 2010-11 |
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Main Authors: | , , , , , , , , , , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
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Summary: | The Large Area Telescope (LAT) aboard the Fermi Gamma-ray Space Telescope provides an unprecedented opportunity to study gamma-ray blazars. To capitalize on this opportunity, beginning in late 2007, about a year before the start of LAT science operations, we began a large-scale, fast-cadence 15 GHz radio monitoring program with the 40-m telescope at the Owens Valley Radio Observatory (OVRO). This program began with the 1158 northern (declination>-20 deg) sources from the Candidate Gamma-ray Blazar Survey (CGRaBS) and now encompasses over 1500 sources, each observed twice per week with a ~4 mJy (minimum) and 3% (typical) uncertainty. Here, we describe this monitoring program and our methods, and present radio light curves from the first two years (2008 and 2009). As a first application, we combine these data with a novel measure of light curve variability amplitude, the intrinsic modulation index, through a likelihood analysis to examine the variability properties of subpopulations of our sample. We demonstrate that, with high significance (7-sigma), gamma-ray-loud blazars detected by the LAT during its first 11 months of operation vary with about a factor of two greater amplitude than do the gamma-ray-quiet blazars in our sample. We also find a significant (3-sigma) difference between variability amplitude in BL Lacertae objects and flat-spectrum radio quasars (FSRQs), with the former exhibiting larger variability amplitudes. Finally, low-redshift (z |
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ISSN: | 2331-8422 |
DOI: | 10.48550/arxiv.1011.3111 |