Having struggled with Python for pretty much the entire first week of the project, this second week has gone (for the most part) a lot more smoothly – our understanding of Python continues to grow, reaching a level that would make even a herpetologist jealous. That said, we are, by no means, experts in the language, but it’s safe to say we’re feeling a lot more confident than we did a week ago.
Picking up from where we left off in the last blog post, we first endeavoured to calculate the AB magnitudes of a sun-like star (i.e. a star whose spectral class is G2v) once each of the bandpass filters have been applied. AB magnitudes are a measure of a star’s apparent brightness, defined in terms of its flux density, where lower magnitudes correspond to brighter stars because Astronomy is just weird sometimes. In order to calculate these magnitudes, we had to first take the convolved fluxes and find the average flux densities through each filter, and then we had to convert the units to get them in terms of ‘per frequency’ rather than in terms of ‘per wavelength’. These average flux densities are shown in the graph below, along with the convolved G2v spectra (shown at the bottom) for a better visualisation of what’s going on.
From these average flux densities, the AB magnitudes of the star through each filter were calculated as if the star were at a distance of 10 parsecs (this is generally the standard in Astronomy) and plotted against wavelength, giving the following graph:
Now that we had a means of calculating AB magnitudes of a star for each filter, we then went on to see how these magnitudes varied with distance form the star. Since the narrow band filter (NB392) generally imposes the biggest limit on what we can observe (on account of the allowed wavelengths covering such a small range), we decided to focus on that, which resulted in this graph:
For the sake of the graph, we selected distances of: 1 astronomical unit (AU), which is the distance from the Earth to the Sun; 10 parsecs; 100 parsecs; 100,000 parsecs; 200,000 parsecs. The limiting magnitude is approximately 25.5 – above this, stars generally become too dim to detect.
We then wanted to see how this relationship between AB magnitude and distance changes for each spectral type (still focusing on the NB392 filter). While we were at it, we decided to provide a small link between our project and the MUSE-VLT project by calculating the magnitudes that each spectral type would have if they were as far away as the galaxy VR7, which is the most distant galaxy in their data at a whopping 64,457.8 MILLION parsecs away. After doing the necessary calculations, interpolating our plots, and subsequently spending far too long on colour-coordination, the resulting graph was this:
From this graph, we can see that even for some of the most luminous stars (best represented by the O5v line) in the VR7 galaxy, their magnitudes (when convolved with the NB392 filter) will be as high as ~50. This is too dim to observe even with the James Webb Space Telescope, which is expected to detect stars with AB magnitudes up to ~33.
So, we have a method of calculating the magnitude of a star when viewed from any distance through different bandpass filters, starting from the very beginning with the raw data from the star’s original spectrum. Now, if you’re anything like us then you might initially be wondering what the point of that is. The point is that some of these magnitudes can be used to determine the observational criteria which confirm whether or not a star is metal-poor, and so being able to calculate them from a star’s original absorption spectrum is an extremely useful tool.
The hunt for metal-poor stars in our home galaxy is yet to begin, but that’s okay. I’m no hunter, but I imagine most will generally feel a lot more confident if they know they have all the right tools at the ready. So while it sometimes feels like we don’t have much to show for our work so far (except a plethora of pretty plots), these last two weeks have certainly not been in vain, and we’re all looking forward to seeing what the next week will bring.