Welcome to the JEDI KENOBI Blog Page.
A Long Time Ago, In A Galaxy Far. Far Away (z~2-6) …
There exists at its centre an SMBH that may be emitting a high concentration of electromagnetic flux in the radio band spectrum, we call these radio sources ‘jets’ or ‘quasars’. The purpose of our NLUAstro Project ; Jet Emission Data Interpretation for Known Enviroment Nuclei Orbiting Blackhole Infrastructure (or more simply JEDI KENOBI), will be to find some of these jets from the COSMOS 2015 data catalogue of over 1 million sources and study their effect on different morphological characteristics within the galaxy.
“Hey! I’m Eishwar, and I am going to be completing this weeks blog post upto and including week 2. A little bit about my role, I am the Group Coordinator/Project Manager/Code Lead, I will be overseeing progress on the group project and taking the lead when it comes to any coding/scripting we need to do.
During the preparatory week, we first attempted to brainstorm a few ideas about some of the topics that we would be studying, as well as some potential group names. Some of the potential subtopics we found to be interesting were how jet galaxies affect the spectra and morphological characteristics of a galaxy; looking how this also changes with jet intensity; and also looking at the instantaneous growth (how much the Blackholes are currently growing by. We also wanted to have a look at how accretion disk size changes with intensity of jets. This was soon dropped as a potential subtopic we now know that it becomes almost impossible to study accretion disk characteristics of AGN’s. This is because an AGN is extremely bright and outshines any radiation coming from the accretion disk. One last topic we wanted to explore was whether the intensities of x-rays, radio waves and UV waves of AGN’S have any variance with redshift of the AGN/galaxy. However as we had too many subtopics to choose from, we decided that it would be better to include redshift considerations into our data analysis when analysing luminosities and spectra, and that we would not be looking directly at any redshift correlations in depth.
Week 1 consisted mainly of finalising group project details such as aims and goals, group roles and a group name. The final subtopics that we chose were to look at the morphological characteristics (spectra, sfr, mass, age) of rare jet galaxies to common non jet galaxies, as well as to further analyse the correlations between jet intensity of the jet galaxies and these morphological characteristics. As for group roles, it was decided that Eishwar (myself) was to be the Project Coordinator and the code lead for any simulation/data work we needed to accomplish; Maddie was to be the team administrator and the literature lead for research and report writing; Robin was to be the analysis lead for data interpretation and explaining findings; and Ivana was to be the theory lead, in order to link background literature to our findings. However, whilst we have leads for each section, this does not mean they will be working alone. Generally we will help each other with each section as needed, but each lead gets the final call as to how we will be proceeding. Of the many popular (star wars themed) group project names, we ultimately had to choose one and Jet Emission Data Interpretations of Known Environment Nuclei Orbiting Blackhole Infrastructure –JEDI KENOBI – was chosen.”
During week 2, our primary focus was to get a presentation together so that we could explain what we were researching to our peers and to outline our aims and goals for the project. We discovered through reading literature on previous NLUASTRO group project work from BAHAMAS and SHREDS, that the main way of detecting AGN is through the detection of Lya emissions. These groups used data from SC4K and VLA catalogues to identify these jet galaxies. Using this method, once we have identified which galaxies we will be comparing, we can look at radio and X-ray/spectra and colour data and begin work on determining morphological characteristics. In the next two weeks we hope to start looking at the relevant literature on measuring these characteristics such as SFR, Stellar mass and Metallicity, and perhaps begin working with SC4K data to identify some of these jet galaxies using Lya emissions.”
“Hello! Welcome to our second blog post, where some details of our third week will be discussed. I am Maddie, and I am the Administrator and Literature lead for my group; like my colleagues I will also dabble in other project areas as the investigation progresses, such as theory and data analysis.
This week, we were able to finalise some of the aims we need to achieve solid methods for. Consequently, here is a list of some of the week’s aims:
- Identifying AGNs (Active Galactic Nucleis)
- Identifying which AGNs have Jets and which don’t
- A way of knowing the intensity/luminosity variance of Radio Jets
- A way of noting which galaxies DON’T have Jets, but may still have certain levels of Radio, X-ray etc
- A way of extrapolating Star Formation Rate
- Working out the instantaneous growth of Blackholes (this may link to Blackhole Accretion Rate)
You may be able to tell that these goals centre around obtaining ways of achieving certain aims, rather than doing the specific aims themselves just yet. This is to accommodate for the fact that for some of them we will need more time to achieve, implement code for and so on.
With this being said, AGNs were still able to be identified, and a plot produced shows their distribution and population:
Using the SC4K catalogue, it is possible to see detections of substantial Radio emissions (in the 1.4GHz and 3GHz bands) and X-Ray emissions. Abundance of such emissions are attributive of an Active Galactic Nuclei, and by using such identifiers in the SC4K survey we were able to produce a distribution of sources, highlighting which ones are likely to be AGN’s (i.e. the ones with red squares, and/or blue and green triangles).
Looking at the raw data and the above plot, we realised some counts are actually results of overlaps. That is, a given AGN can sometimes be observed “twice” due to it having detectable X-Ray and Radio emissions for example. This means we needed to remedy these count overlaps in order to get an accurate count for our total number of AGNs. With the above plot, we were looking at our AGN count to be approximately 394 (using SC4K and Chandra data), however this changed when a new cleaner plot was made; such a plot had the aim of reducing the overlap miscounts, and is shown here:
We have decided that for identifying if given AGNs have Jets, we may use the NASA/IPAC Infrared Science Archive COSMOS Cutouts programme (available here: COSMOS Cutouts (caltech.edu) ). This allows us to input relevant RA and DEC coordinates, and then see visuals corresponding to given coordinates with a range of telescopes. The potential of this is quite exciting; as an example, using the VLA (Very Large Array) visual, we are able to see the Radio picture of our sources. Given AGN Jets emit abundances of Radio emissions, we could expect to see two areas of high radio emission corresponding to the two Jets coming off the AGN. Looking at source “SC4K-IA464-75921” from the SC4K survey, a radio visual can be seen:
As you can see, this AGN appears to have Jets- indicated by the two “blobs” there- these are the lobes of the Radio Jets coming off the AGN. These Jets could be spanning across 100s-1000s of light years, which is really exciting!
One of our investigation aims of the project was to see if there was a relationship between Radio intensity of AGN Jets, and their host galaxy characteristics. For example, is there a relationship between the Jet intensity of the central AGN and the star formation rate of the host galaxy? This is quite an interesting question, but it’s viability is threatened slightly by the fact that obtaining the Jet intensities is a very difficult thing to do. A variety of literature and papers has been traversed to try and help our exploration of this. One thing that has resulted from it is the discovery of a scaling relationship between Radio Power and Jet Power:
Pjet ≈ 5.8 × 1043(Pradio/1040) 0.70 erg s−1
This was found from this paper: [Cavagnolo KW, McNamara BR, Nulsen PEJ, Carilli CL, Jones C, Bîrzan L. A relationship between agn jet power and radio power. Astrophys J. 2010;720(2):1066–72. Available from: C: (iop.org) ], and could potentially be chosen as an alternate observable to look at as opposed to intensity. However, our endeavours to find a way of obtaining intensity will continue, and we are making steps to try and learn more about the issue of measuring Radio Jet intensity. For example, at present, an inquiry email has been sent from myself to Astrophysicist Dr Megan Argo, University of Central Lancashire, asking about this issue and if the alternate plan of focusing more on power appears more viable. We hope to be able to comment more on this subtopic focus as time progresses.
Amongst some of the goals aimed for this week, one that made progress was the investigation into ways to quantify instantaneous growth of Blackholes. With AGNs, the hot gas and matter surrounding the central Blackhole is responsible for a magnitude of X-Ray emissions. The information they provide is therefore very valuable since they come from an area closer to the central Blackhole itself, and will therefore be more sensitive to any changes in this area. It follows that observing “instantaneous” Blackhole growth, parallel to Blackhole Accretion Rate, may be done best by observing certain X-Ray emissions. This notion was supported by one of our plots from the SC4K data, looking at the correlation between X-ray luminosity and X-ray measured Blackhole Accretion Rate. An excerpt of this can be seen here:
Here you can see the direct link between these two observables. Further to this, to test the waters so to speak, another plot was made to see the distribution of X-ray Blackhole Accretion Rate with Star Formation Rate. This plot was again quite an interesting one:
At present it is difficult to tell, but the above plot looks as though it may have a very slight positive correlation. If this is well-founded, it may be the case that a more active AGN entails a more active host galaxy. We will need to study this further to make more solid conclusions perhaps. Something of interest to note, are the outliers; for example, the one towards the top left of the previous plot. This data point has an extremely high X-ray flux, but a relatively low Star Formation Rate- a very curiosity-inducing point and something we could investigate more, time-permitting.
This week has been quite an important one in our journey; we have traversed and explored data sets such as SC4K, LEGA-C and VLA whilst building the paths to our future findings. It has been an exciting time and we look forward to building on our current achieved methods next week!”
Hello there, and welcome back to our blog. My name is Robin, I’m the data and error analysis lead and will be in charge of this week’s blog.
This week may seem a bit slow in terms of progress, but we have taken important steps towards our goals for this project. We mainly want to focus on AGNs that have jets and how that might change the properties of the galaxies. The first obvious step we need to take is to identify these AGNs from the SC4K data set. This was done last week and left us with 312 unique AGNs. The next step was to identify which ones of these are jet AGNs.
Like mentioned in last week’s post, we used the COSMOS cutouts from the NASA / IPAC infrared science archive (https://irsa.ipac.caltech.edu/data/COSMOS/index_cutouts.html) and used the VLA (Very Large Array) in order to identify jets. This website lets us insert the RA and DEC coordinates of our AGNs, and by choosing VLA, we get images of the galaxies in the 3GHz radio band. This is perfect as the jet will be visible in this band.
The process of going through all 312 galaxies was a tedious task since it all had to be done manually. When looking for jets, we are looking for a galaxy with two “blobs” on each side of it which would be our jets. This is also easier said than done, since in the 3GHz range there will be a lot of noise from around the galaxies, and the resolution of the images does not make it any easier. Underneath shows a galaxy we have determined to be a jet, one which is nothing but noise, and one which is currently undetermined (as of writing this)
As you might see, this task is not as clear cut as it may seem at first. Most of the AGNs do not have jets, which is as expected since jet galaxies are quite rare. Although it might be easy to let the excitement take over and label a galaxy as to have jets, it is important to be critical as a wrongly labeled galaxy might change our conclusions if we are not careful.
In the coming week, we would like to determine all the uncertain galaxies we still have. Since jets are a rare phenomena, we would also like to look at some more AGNs if possible with an extended data set. As of now, we only have about 4 Jet galaxies (the same ones as BAHAMAS). With such a small sample size it would be difficult to draw any sort of conclusion from this. With regards to these more uncertain galaxies, we will discuss and gain the opinions of David Sobral as to what distinguishes between a Jet and Non Jet galaxy in these extremely close cases.
Hey, Ivana and Eishwar here for an update to our progress for week 5&6.
Week 5 has been a week of getting all of our resources organised. This has been an interesting task since we are working with two different catalogues, each of which holds different information (are even if they have similar columns, the values might have been calculated in a completely different way). The smaller catalogue we are working with is the SC4K where we have 310 AGN (out of the nearly 4000 galaxies in the catalogue) of which we know the masses thanks to (Santos at al. 2020). Our larger catalogue is the VLA catalogue which has significantly more sources. In order to get information similar to what we have for the SC4K catalogue we had to match a table of 9000+ sources (taken from Smolcic et al. 2017) to the larger COSMOS15 survey which had over 1.1 million sources. At the end our matched table has 3559 AGNs. This means that we have a total of 3869 AGNs which we can study between our two catalogues. Unfortunately, neither one of the VLA tables contained BHARs, which meant that we had to calculate them ourselves. We used the flux in the 0.5-10keV band (one of the many wavelengths the objects have been observed) and found the BHAR for 529 AGNs with a mean BHAR of 0.1907 solar mass per year (the rest unfortunately do not have provided the flux, but we might be able to get it ourselves for some of them). An additional task for this week was going through some of the objects that we were uncertain about whether they had jets or not. And of course we had to prepare ourselves for the real challenge -looking for jets in the VLA catalogue.
During week 6 we focused primarily on detecting jets in our VLA catalogue. Using our matched table from last week, we had roughly 3500 AGNS from redshifts of roughly 0-6. Therefore, we decided to take the same approach as we did in the SC4K data set, as without an advanced AI, it becomes impossible to automate this task in order to find jet galaxies. We started from the top of the VLA catalogue (high redshifts) and worked our way downwards. This is because jets have been known to be found more frequently at higher redshifts. However, one issue we found with this approach was that these jets of galaxies at redshifts >3.5 become increasingly difficult to detect due to negative fluxes, artefacts and the quality of the images due to these vast distances.
We found jets of a galaxy at a high redshift ~ 4 which was initially exciting. However this was just our target galaxy being obscured by one with jets. You can see our target galaxy in the centre, denoted by the yellow circle and our obscuring galaxy to the south with a jet being emitted further south.
As this was such a large task, it took most of the week for members to go over the VLA images in their spare time. By the end of the week, In addition to some of the Bahamas jets we confirmed in our sample, we found two more within the Bahamas redshift range that we thought provided enough evidence to be determined as jet galaxies and another one outside their redshift range.
Three of Bahamas’s Jets were omitted from our jet collection as they either did not qualify as being an AGN as described in Smolcic et al 2017 or were not a Cosmos 2015 detected source. The reason for this is because Jets are produced from AGNs. Therefore, by excluding any data not classified as an AGN, we can save doing unnecessary work, such as going through the images, for these galaxies as the chances of a jet being present are unlikely. As it turned out, there was a detected jet that was not classified as an AGN in the BAHAMAS dataset. This may be due to the constraints as to what is classified as an AGN in the Smolcic catalogue. We are still deciding whether or not to include it in our data set or include it within a separate category. We ended up going down to a redshift of 1.7 as this keeps our sources to a reasonable number given the limited time we have to finish data collection. As we are taking such larger redshift ranges compared to BAHAMAS, we will likely need to take this into account as part of our systematic biases.