The search continues for potentially habitable exoplanets capable of supporting life as we know it...

As of today, over five thousand stellar and planetary systems have been discovered and recorded by NASA/JPL and Caltech, with additions being dynamically added as information is normalized from the different instruments involved in observing the Cosmos. Some of these exoplanets might have the ability to sustain liquid water, but as of now the process to sort through this ever-increasing dataset is time-consuming and ineffective. This Project seeks to address this issue by simplifying the procedure of identification [of planetary objects] through the use of algorithms which identify any viable exoplanets within their parent star’s “Goldilocks” zone, meaning they have the potential to sustain liquid water [H2O between the temperatures of 0C & 100C], and thus life as we know it. We also seek to create a solution for determining habitability that functions on all stellar types, meaning that determination is possible regardless of the characteristics of a planet’s host star. A combination of Python and SQL was used to mine the extensive public dataset provided by NASA/JPL and Caltech. 

PUBLICATIONS

• Allen Chen, Hrithik Pai, Aryan Rustagi, Rishab Pangal, Aditya Iyengar, Aaryan Divate, Akhil Deshmukh, Stanley Luo, Aaron Li, Aarav Sharma, Robert Downing "Application of Data Mining to Search for Potentially Habitable Exoplanets." article preprint on Academia.edu [PDF Link]

Searching for mini-Black Holes using Stellar Radial Distortions & Velocities

If there are that many datasets out there that we can leverage, what else can we look for in the mountains of data that we already have?

• How about exosolar objects transiting our solar system. Anyone remember the object called Oumuamua? Some heavyweight astrobrains have said that they weren't ready to discard the idea it might have been an alien construct, under navigational control.

• Or how about  exosolar objects entering our solar system & then whacking into the Earth? One was just discovered [it was going way too fast to have originated in our solar system) in the dataset recording atmospheric impacts!

• Not all exosolar events [FRBs, GRBs, Pulsars, HIII molecular clouds] behave as we think they ought to behave. What hints at these abnormal behaviors might lurk in the data we already have accumulated, & what contributions might we make to the studies underway?

Looking for Interstellar Near Earth Objects [INEOs]

In  2017, an astronomer [Robert Weryk] discovered an unusual object on its way out of the Solar Systems. Formally designated 1/2017 U1, it became known by the more popular [Hawaiian] name of Oumuamua [Scout]. It betrayed unique characteristics that definitively identified it as having an extra-Solar (or Interstellar) origin. It was soon followed by a second, 2I/Borisov, "an interstellar comet and the second interstellar interloper discovered." [https://en.wikipedia.org/wiki/2I/Borisov]

It should be obvious that several things logically follow from these discoveries:

1. Objects with Interstellar origins are common [two in two years being observed, without their being the primary question being posed by astronomers]

2. More recent discoveries imply that this may be a function of the improving resolution of instrumentation, and

3. Having 'known good' examples lends itself well to Supervised Learning (a type of Machine Learning)

Identifying common characteristics of the above [U1 & U2], they were then applied to databases [e.g.: the CNEOS database] documenting observations of objects hitting the Earth's atmosphere (bolides/meteors/'shooting stars') looking for what might 'fall out of' our algorithms. As might be expected [re: # 1, above] two observations stood out above all the others, IM1 & IM2.

So, while we wait for increasing resolution [# 2, above, but also for more datasets coming online] we will pursue a supervised learning approach [#3, above]  to look for other candidates having an Interstellar origin, perhaps even being able to identify locations which can be explored for terrestrial evidence of those objects! [https://en.wikipedia.org/wiki/CNEOS_2014-01-08]

Observing in the Radio portion of the EM spectrum

We're all familiar with Optical astronomy [observing in the 'visible' portion of the EM spectrum],  & maybe some have heard of the more exotic types of astronomy like Infrared [IR] or X-ray (or maybe even using gravity!). Well, we're going to explore observing in the Radio portion of the EM spectrum [~ 1 to 10 meter wavelength]. 

We elected to participate in a NASA program [JOVE, https://radiojove.gsfc.nasa.gov/] & secured the materials for a kit radio telescope, & will be observing doubly- & triply-ionized hydrogen [H II & H III] in the Galactic disc, as well as our Sun, & Jupiter [in the range of 0.6–30 MHz] (depending on the schedule determined by the research group).

This group [like the others in Astrophysics] will be connecting via remote protocols to a radio telescope & receiver capable of capturing & serving spectral data in the radio portion of the EM spectrum.

For background, look for publications by Abraham [Avi] Loeb, Chairman of Astronomy @ Harvard University (among many other posts). He's written extensively on Oumuamua, Interstellar visitors & the search for terrestrial proof of 'visitations' by Interstellar objects (no, no one is saying 'aliens!').

Exploring potential solutions to the small scale problems of the Lambda Cold Dark Matter [CDM] Cosmological model.

This is a longer-running Project that is being transferred from Dr. McMahan to myself for Administrative purposes. The Project will continue as a 'remote' Project for the continuation of work done so far.

The first started our project off with familiarizing ourselves with the material for the first couple of months of the project. We read papers on baryonic physics, the lambda cold dark matter model and its small scale problems, the self interacting dark matter model, and the bullet cluster. We then decided that we wanted to simulate the Bullet cluster using a tool called Gadget 4. We settled upon simulating the Bullet cluster as it is very well studied and would be the most practical for us to run our simulation on. Our goal with using Gadget 4 is that we could simulate both the Lambda CDM model and SIDM model to compare which model of the Bullet Cluster generated an output closest in accuracy to astronomical observations. We wanted to familiarize ourselves with running simulations like gadget 4, so we first ran a simulation with N-body Python code that could simulate particles. Once we had done so, we began to move on to running Gadget 4. We first had to set up many files on our computers and familiarize ourselves with the various functions to actually run Gadget 4. We are currently studying Gadget 4 and are currently simulating the examples that are provided. We hope to use these simulations to familiarize ourselves with the tool so that we can eventually simulate the Bullet Cluster using Gadget 4.

Our plans for the future include first completely familiarizing ourselves with the Bullet Cluster. We have read about the Bullet Cluster through literature and have also read a paper covering its simulation in Gadget-2. Understanding the Bullet Cluster and instances of its simulation using the Gadget software will pave the way for us to simulate the Bullet Cluster using Gadget-4 on our own, both using the Lambda CDM model and the SIDM model. While we have studied research regarding dark matter and baryonic feedback, we must also study how these phenomena are to be simulated in simulations. We are also studying how to analyze the output generated by the simulations. After simulating the Bullet Cluster both using the Lambda CDM Model and the SIDM Model using baryonic feedback, we would compare which model of theBullet Cluster generated an output closest in accuracy to astronomical observations. Our goal with these simulations is to eventually generate a more accurate cosmological model of the universe to potentially solve the small scale problems of the lambda cold dark matter model.