SNAG: Studying Nearby AGN & Galaxies: Post 4

Missed out first blog post? Click here to read it.

It’s now week 4 and the project has been progressing well. We are now starting to tailor our investigations back together between the two groups. This will ensure that we will come to some conclusion and ensure that the two projects running side by side will combine together in the last week.
This led to a large planning session before the week even started outlining the direction which we wanted to go with these labs. The end of many of the projects from the previous week meant that we had to find investigations within the interesting results we had already had. This led to a plan and a manic whiteboard being produced on the way to the said plan.  

Group 2 (Jonathan, Tom & John) carried on using the CLOUDY simulation due to the familiarisation that they had developed in the previous weeks. Their aim for the lab was to find how the quantities which we had been studying about the galaxies such as mass, density, SFR etc., changes throughout each of the subsets.  This involved splitting the different galaxy regions(starforming, starburst and AGN), which they had been working on in week 2 up into sub sections within cloudy.  Due to the progress last week each subset had been created and the cloudy data which coincided with each subset was known and refined. This meant that the trends for each subsection could be found form the CLOUDY data points which lay in this section. 

The above graph is the starforming galaxies split up into seven sections. The below is the starburst data, this was harder to separate due to the shape and is in 12 sections. The AGN subset will be done in next week. 

From these subsets, created on TOPCAT, they will use the data in the CLOUDY simulation to extrapolate the average (sigma) value of each of the quantities in the subset. This will then produce values of parameter allowing errors  to be calculated and trends in parameters across each region 

This produced a mixed bag of results once average values had been calculated. There are some plots where the errors are large when compared to the spread of the data 

This allowed us to confirm some trends such as age/mass of a galaxy. However we were unable to confirm whether there was any correlation between some factors such as metallicity and temperature due to the large errors associated with these variables. The errors in solar metallicity are so large that we end up with negative metallicity values in some cases making the results  unusable. Over the course of the day we were able to find a large amount of data which supported the trend between mass and age of the galaxies. This trend was confirmed both in the star forming and starburst data sets (it was also confirmed by group 1, through the trends of passive galaxies) 

The CLOUDY models being used to find the trends have some different properties depending which model you use, such as age or temperature. This means that there are some properties which can only be found for some galaxy types. It also means that when the same properties are being calculated using two different CLOUDY models, a comparison between them can be made. This has allowed us to see differences between the models, we presume this is due to different assumptions made for the models.
It can be seen in the BB vs BPASS density figure, these are the predicted densities of the subsections made by the two different models plotted against each other. They have produced largely different destiny approximations depending on the model used. We may follow this by determining what it is that makes the CLOUDY models create such different values from different models. 

Group 1 – ( Charlie, Ciara, Pascale, Phoebe) We began investigating the passive galaxies which we had within our data set. These are galaxies which are no longer forming stars. We initially defined the passive galaxies as those who had a H Alpha flux line which was smaller than three times the error. In the process we had previously removed these data points to help remove noise from the data set, after adding them back in and marking them as passive galaxies we were able to split the data.  All the points in green we have classified as passive galaxies. Those in blue had already been classified. The points in red are still unclassified in our data set.  

We started the photo-metric analysis of the data using the colour lines. We did this by matching the data set with the photometric data in another set. From this we were able to retrieve the UGRIZ filter flux for each data point. U-ultraviolet G- visible (green)R – visible (red) I- infrared Z- far infrared Using this data we were able to plot two colour indexes against each other, e.g (U-R) in order to hopefully identify/confirm the passive galaxies in our data set as they should cluster in a particular area. 
In this figure the blue data is the passive galaxies in our sample. They tend to clearly cluster together agreeing that the 3 flux condition is a good indicator of passive galaxies. However there are classified (starforming and AGN) galaxies which lie under the passive galaxy points which increases the uncertainty in our definition of passive galaxies which we are hoping to improve on next week.  In this figure the U-R and R-I colour indexes were used. 

However when we plotted the newly defined passive galaxies on a plot which we know clearly defines the star forming and AGN galaxies, a clear grouping was not apparent.  It was hoped for a clear, defined group of passive galaxies which would help to confirm that a good choice of subset condition had been done. 

The final task of group 2 was to plot the percentage of a galaxy type against mass. This has produced the trend we were expecting with the passive galaxies dominating at high mass, and star forming galaxies at low. There is also the slight peak of AGN galaxies at the higher mass as is predicted from their properties. 

Looking Forward Next week we are hoping to define our passive galaxies better, ensuring that the selection which we have made is correct and is not including noise or non passive galaxies. We may also look at plots made in previous weeks and decided whether adding passive galaxies will tell us any more information. The team using CLOUDY will do the sectional analysis of the AGN galaxies to have a complete set of values to be able to analyse. Further investigation into the differences in the models and how this materialises in the results may also be possible. 

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