1st Blog Post: Studying CR7 with ALMA

At the beginning of the first week I wasn’t sure what to expect and was worried about being the only first year. This is my first time completing an internship and my first taste into what being a researcher consists of.

On the first day, we downloaded all the software onto our laptops and started to have a look at what it could do. We are using GAIA, DS9 and Topcat to look at the 3D cubes from ALMA (Atacama Large Millimeter/submillimeter Array). We also did a lot of background reading about CR7. CR7 is a high redshift Lyman alpha emitter galaxy discovered by David Sobral and is the focus of our research for the next few weeks. The galaxy is modelled to be made up of three clumps, A, B and C with each region giving off different emissions.

The 3D cubes from ALMA are composed of different frequencies which are collapsed into an image that can be analysed using GAIA or DS9. We are looking at CII maps of CR7, as this is a good indicator of star formation rates in galaxies, and we started by using GAIA to look at the sources and determine if they are real sources or just noise.


In order to do this, we used aperture photometry, this consists of summing the pixel counts within a circular aperture of fixed size and subtracting the average sky count. (Count is the number of photons incident on a point and is related to flux). In GAIA, we used the Gaussian sky setting which assumes all errors are Gaussian. We took into account the effects of the size of the aperture, matching it to the size of clump A using contours. We repeated the procedure many times to be able to quantify the noise and look at the spread of the noise in different regions of the image. Later we will run scripts that can do this for us but we started off carrying it out by hand in order to get an understanding.

In final conclusions, I found 3 potential sources in the image with source 2 corresponding to the location of clump A in CR7.


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