1st Abstract
Title (1st Abstract) | SNRs with LOFAR |
First Author | Maria Arias |
Affiliation | University of Amsterdam |
Additional Authors | Jacco Vink |
Presentation options | |
Session | 1. Radiation studies from gamma-rays to radio in Galactic and Extragalactic SNRs |
1st Abstract | The LOw Frequency ARray (LOFAR) is a new-generation radio interferometer in the Netherlands that covers the largely unexplored low-frequency ranges of 10-90 MHz (with the Low Band Antenna, LBA) and 110-240 MHz (with the High Band Antenna, HBA) with unprecedented sensitivity and angular resolution. The telescope offers very interesting possibilities for the study of supernova remnants (SNR), whose steep spectral indexes render them more dominant at low frequencies. LOFAR frequencies allow us to observe different absorption processes affecting SNRs at low frequencies: both internal and external free-free absorption, and perhaps even synchrotron self-absorption in certain exceptional cases. In this talk I intend to present my initial results from LOFAR imaging of two SNRs: Cassiopeia A and VRO42.05.01. From a technical point of view, Cas A is of importance to LOFAR because, as the brightest source in the radio sky, it can contaminate entire observations if it enters a beam side lobe. In order to properly subtract its contribution to the visibilities of any given target a high resolution model of Cas A is required. This data set was taken with the aim of making such a model, and here I will present an LBA image and discuss the absorption processes present. VRO42.05.01 is a mixed-morphology SNR, and as such has an overall flat ($alpha=0.37$) spectral index. Some MMSNRs are known to have spectral index segregation, with faint steep spectral regions and bright flat spectral regions. We took both LBA and HBA data of VRO.42.05.01, which allows us to explore local variations in the spectral index and their correlation with density. For both sources, I will show how the morphology at LOFAR frequencies compares to high frequencies, and what we can learn from that. |
Account
First Name | Maria |
Last Name | Arias de Saavedra Benítez |
Institution | University of Amsterdam |
Country | Netherlands |