A Study of Hydroxyl (Oh) Maser Variability in Ngc 6334I
Abstract
The Cat’s Paw Nebula is part of our host Milky Way galaxy which experienced a significant
assumed accretion event resulting in highly variable hydroxyl, water and methanol masers.
Not only were these masers variable in intensity but also velocity. The source NGC 6334I
was included on the long-term observational program at Hartebeesthoek Radio Astronomy
Observatory and we report some of the findings.
We find that the peak velocity of some OH maser features varied periodically and experienced
a maximum velocity variance of about 8 10 %. The variance was observed in both the
LCP and RCP of the OH maser dynamic spectra. In LCP, the variation was observed at -10.6
km s1, and -10.2 km s1 and the period of variability was 366.01 3.33 and 365.89 1.28
days respectively. In RCP, the velocity only varied periodically at -6.7 km s1 and its period
was found to be 366.69 1.38 days. The period is within the error of one Earth year (365
days).
A source identified as NGC 6334-V south of NGC6334I, which is not at the beam center
of the telescope, has 1665 MHz OH masers that were detected while observing those from
NGC 6334I. As a result of its large angular distance from the beam center (NGC 6334I), the
applied local standard of rest velocity (Vlsr ) correction introduced a periodic variation for
OH masers originating from NGC 6334-V. Masers from this source whose Earth-Sun motion
was not corrected are roughly at angular separation of 500 corresponding to the velocity of
-10.2 km/s, 42.50 corresponding to the velocity of -6.7 km s1 and 400 corresponding to the
velocity of -10.6 km s1.
We attempted to determine the magnetic field strength by firstly identifying Zeeman pairs
based on the fact that they have similar variability. The magnetic field corresponding to
1665 MHz OH masers from NGC 6334I was found to be -5.8 0.5mG
The five years of data used for this study were provided by Hartesbeesthoek Radio Astronomy
Observatory (HartRAO) in South Africa. The data was processed and reduced using
an in-house program called lines which run on Linux and the analysis was done using a
program called Period04 and also using python scripts in Jupyter Notebook. The period of
variation was obtained by fitting a sine function to the observational data.
Publisher
university of nairobi