Relevant Articles

The author addresses the feasible use of an artificial intelligence program in order to identify suprenovaes from images taken from low resolution images. The paper takes an experimental approach as the author creates a machine learning (ML) script in Python, using the Keras API. The author begins by laying the theoretical foundation upon which the application is built, discussing the current methods that are used in order to identify supernovae without computers, specifically the spectral types used to classify the different elements present near a supernovae. This information is then used in the ML when the program is “instructed” to identify pixels that exhibit similar spectral types to those that are typically found near a supernovae. Further constraints were then implemented, such as the pixels must be in a clustered location. This article will be very useful in unde

This paper presents an algorithm for determining the parameters of a black hole. While the paper mainly focuses on its application to self-potential data, it does provide insight into the triangulation of black holes. The black hole algorithm is population-based, means it uses the population of stars in a given area in order to generate a random population of candidate solution. xi(t) and xi(t+1) are the locations of the i-th star in the iterations t and t+1. X_BH represents the location of the black hole in the search space. This will be useful in understanding an algorithm to use in order to set up the parameters of the neural net. Black holes are a progenitors of GRBs so locating the BH will be useful as possible locations for GRBs.

This webpage gives a very useful overview of GRBs and current research that is progressing with the Swift data. It outlines the basics of what is currently known by NASA. GRBs get their name from the intense burst of energy classified as gamma rays which are produced from the collapse of massive stars or the merging of two neutron stars. It should be kept in mind that all events that happen in galaxies that are light years away have already happened. We are seeing the events that transpired millions of years ago because it takes the wavelength time for use to see. This is why redshifts are useful in determining the time and location of gamma ray bursts or any space-event in general. This article will be very useful in gaining a base understanding of astronomical data collection and the use of each variable.

This is webpage gives another overview of the Swift project. It goes into depth on the history of the Swift project. Originally launched in 2004, the Swift satellite is tasked with taking over 2,200 160 megapixel images. The light includes up to 3,300 angstroms, which are UV wavelengths that are blocked from Earth. The satellite also has a resolution of 2.5 arcseconds. This website is very useful in determining the capabilities of the Swift satellite and will give me a greater understanding of how the satellite moves so I may better calculate the distance and location of the GRBs.