After two productive weeks working with the team on the ALMA project, we have developed a good level of insight into the fundamental principles that are underlying the method we will use to search for CII line emitters in the region around CR7.
This has included expanding on our method for determination of noise from the CII image. We began taking more localized noise measurements that were surrounding anything we identified as being a potential source. This is because noise may be non uniform across the image, and some regions may be systematically noisier than others. Several problems arose from this, however. We found that many of the sub 3σ sources that we identified became sources as localized noise was reduced, which is fine, but many of the 3σ sources, including clump A of CR7, were now discounted using this method. This was because we were only making 50-100 apertures for each individual noise measurement, and only about 300 for the overall image. This can be fixed utilizing a script to repeat the process. David sent us a script for this purpose which can be set to repeat this process for any number of apertures, and generates an astoundingly strong Gaussian distribution in our histogram, which was expected of our results. Using statistics from this distribution, this more accurate method of noise level determination will form part of the basis of the rest of our project.
We have also been considering what physical properties can be inferred from data that can be extracted from these images. In particular, how CII luminosity can be measured, and then how this CII luminosity can be used to estimate a star formation rate. For CII luminosity, we found that ALMA data is calibrated by using nearby sources of known luminosity such as bright quasars, and comparing this to the flux observed from a source a CII luminosity can be calculated. GAIA in fact can read this calibrated information which is stored within the .fits files. This in the units of mJy (milli-Jansky), a measurement of spectral flux density used in Astrophysics. Another script sent to us from David to try, in fact is made to measure the flux from a source. This script calculated for clump A of CR7 to be L=0.50×10^8 in units of Solar Luminosity.
This information can then be used to infer a star formation rate, by using an equation found in a paper from Vallini et al. in which a CII luminosity-Star formation rate relationship is inferred from the best fit line of observed data, taking into account how star formation rate varies with CII luminosity and metallicity of the source. This equation, using observed data and taking a lower bound of metallicity determined the star formation rate of clump A of CR7 to be ~44 Solar masses per year. This is a reasonable result, in the right order of magnitude and varies only according to what initial mass function model you use.
We will be using methods similar to those outlined in Emma’s blog post from last week, utilizing both python scripts and eye observation to analyze ‘slices’ from a cube of ALMA data. This ‘cube’ is essentially an image which contains information including a third dimension of distance, by accounting for small changes in redshift of the emission line. This 3D image can be split into ‘slices’ of space which we can analyze individually, first determining the noise using a scripted version of the method outlined in Emma’s previous blog post. Using statistical data from the noise, we can use GAIA’s features such as aperture photometry and SExtractor, to identify potential candidates for CII line emitters in the region about CR7. The unique feature of a cube, is that we can create a 3D map from the catalog of any observed emitters. We will also be using a CII flux measurement script to calculate the CII flux in a given aperture size (set to the Point Spread Function of the image) to measure the CII Luminosity.
After generating a catalog from this ALMA data cube of sources, we can begin exploring data from Hubble and search for different emission lines, that we can use to confirm which of these in the catalog that we have identified actually correspond to real sources. We are hoping to find a few sources in the region surrounding CR7 using this method.