1st Blog Post: HST Grism

Starting a week later than most of the other interns, I was worried about being so far behind. However, I quickly settled in and realised that we were all on the same page.

On my first day, I had an introduction to the various software I would be using over the course of the internship. This software includes Topcat and ds9. Topcat is designed for analysing lots of astronomical data, and ds9 is designed for viewing images. I had never heard of either of these before, but was looking forward to becoming competent in them.

My partner for this project, Umar, had been working on his other project (CLOUDY simulations) over the previous week and so we were both starting at the same place for this project. The idea for this week was to get used to handling the data and become accustomed to the new software. I was looking at the spectrum of CR7, which can tell us what ions are present in the galaxy by looking at what wavelengths of radiation are present. However, there is a lot of background noise when trying to read values off the spectrum, and so the aim is to find the Signal-to-Noise ratio (SNR). This is done by dividing the apparent signal by the background noise. I started off by taking a spectrum along one line of pixels where the galaxy lay, and then another one with no apparent source, and using the second line as my background noise. I soon found out this was not a good choice of method, and so another way had to be found.

Where the signal is much higher than the background, we can be confident this is an emission line.

The next few days were spent trying to find the standard deviation of the noise by looking at several rows of pixels with no apparent source and finding the standard deviation at each relevant wavelength (for example, a high flux at 1484.4Å indicates NIV). This was then used as the background noise and from there, a more accurate SNR could be calculated for each wavelength.

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