Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-27T13:16:31.878Z Has data issue: false hasContentIssue false
  • English
  • Français

Detection Thresholds and Bias Correction in Polarized Intensity

Published online by Cambridge University Press:  02 January 2013

Samuel J. George ,
Jeroen M. Stil  and
Ben W. Keller
Samuel J. George*
Affiliation:
Institute for Space Imaging Science & Department of Physics and Astronomy, The University of Calgary, 2500 University Drive NW, Calgary AB, T2N 1N4, Canada
Jeroen M. Stil
Affiliation:
Institute for Space Imaging Science & Department of Physics and Astronomy, The University of Calgary, 2500 University Drive NW, Calgary AB, T2N 1N4, Canada
Ben W. Keller
Affiliation:
Institute for Space Imaging Science & Department of Physics and Astronomy, The University of Calgary, 2500 University Drive NW, Calgary AB, T2N 1N4, Canada
*
BCorresponding author. Email: samuel@ras.ucalgary.ca
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Detection thresholds in polarized intensity and polarization bias correction are investigated for surveys where the polarization information is obtained from rotation measure (RM) synthesis. Considering unresolved sources with a single RM, a detection threshold of 8 σQU applied to the Faraday spectrum will retrieve the RM with a false detection rate less than 10−4, but polarized intensity is more strongly biased than Ricean statistics suggest. For a detection threshold of 5 σQU, the false detection rate increases to ∼4%, depending also on λ2 coverage and the extent of the Faraday spectrum. Non-Gaussian noise in Stokes Q and U due to imperfect imaging and calibration can be represented by a distribution that is the sum of a Gaussian and an exponential. The non-Gaussian wings of the noise distribution increase the false detection rate in polarized intensity by orders of magnitude. Monte Carlo simulations assuming non-Gaussian noise in Q and U give false detection rates at 8 σQU similar to Ricean false detection rates at 4.9 σQU.

Keywords

polarizationmethods: statisticalmethods: data analysis
Type
Research Article
Information
Publications of the Astronomical Society of Australia , Volume 29 , Special Issue 3: Source Finding and Visualisation , 2012 , pp. 214 - 220
Copyright
Copyright © Astronomical Society of Australia 2012

References

Beck, R. & Gaensler, B. M., 2004, New Astronomy Reviews, 48, 1289CrossRefGoogle Scholar
Brentjens, M. A. & De Bruyn, A. G., 2005, A&A, 441, 1217Google Scholar
Burn, B. J., 1966, MNRAS, 133, 67CrossRefGoogle Scholar
Condon, J. J., Cotton, W. D., Greisen, E. W., Yin, Q. F., Perley, R. A., Taylor, G. B. & Broderick, J. J., 1998, AJ, 115, 1693CrossRefGoogle Scholar
Gaensler, B. M., Landecker, T. L. & Taylor, A. R., POSSUM Collaboration, 2010, BAAS, 41, 515Google Scholar
Grant, J. K., Taylor, A. R., Stil, J. M., Landecker, T. L., Kothes, R., Ransom, R. R. & Scott, D., 2010, ApJ, 714, 1689CrossRefGoogle Scholar
Heald, G., 2009, IAUS, 259, 591Google Scholar
Rice, S. O., 1945, Bell Syst. Tech. J., 24, 46CrossRefGoogle Scholar
Simmons, J. F. L. & Stewart, B. G., 1985, A&A, 142, 100Google Scholar
Stil, J. M. & Taylor, A. R., 2007, ApJ, 663, L21CrossRefGoogle Scholar
Subrahmanyan, R., Ekers, R. D., Saripalli, L. & Sadler, E. M., 2010, MNRAS, 402, 2792CrossRefGoogle Scholar
Taylor, A. R., Stil, J. M., Grant, J. K., Landecker, T. L., Kothes, R., Reid, R. I., Gray, A. D., Scott, D., Martin, P. G., Boothroyd, A. I., Joncas, G., Lockman, F. J., English, J., Sajina, A. & Bond, J. R., 2007, ApJ, 666, 201CrossRefGoogle Scholar
Taylor, A. R., Salter, C. J., 2010, Proceedings of the Conference ‘The Dynamic ISM: A Celebration of the Canadian Galactic Plane Survey’, ASP Conference SeriesGoogle Scholar
Vaillancourt, J. E., 2006, PASP, 118, 1340CrossRefGoogle Scholar