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GSoC 2025 Stingray Shanice Mack: Interactive Database for X‐ray Observations
Name:Shanice Mack
Email:Shanice.mack99@gmail.com
Time-zone:Eastern
Slack Handle:https://stingraysoftware.slack.com/team/U08KMJJSQMS
Github username:ShaniceM9
PR links:https://github.com/StingraySoftware/notebooks/pull/121
I am a recent graduate from Georgia State University with my Bachelor's in Physics & Astronomy. I've accumulated many different skills by completing class projects and research projects. I'm most proud of my research on Active Galactic Nuclei and studying the relationship between its global covering fraction and luminosity. I worked on this project for about two(2) years, received a fellowship, and presented this project at two conferences. In order to complete this project, I've had to learn how to code in Linux C++, as well as complete data analysis through excel. It's safe to say I'm proficient in my programming skills in both Python and C++. I've gained my python programming skills through numerous projects during my degree, such as studying the kinematics of the Orion Nebula. I enjoy doing research and making any contributions to the team I'm working with. I also enjoy learning. No matter what the information is, I enjoy being open to always learn something new. I believe this trait makes not only a good teammate, but also a great researcher.
I'm interested in Open Astronomy because of my interest in studying and researching astronomy. I love how this organization allows for those who'd like to contribute and collaborate with other astrophysicists and open source astronomy coders. I believe I would be a great contribution to the team, by bringing along my programming skills, knowledge in astrophysics, and being an overall team player.
This project focuses on developing an interactive visualization tool to analyze and track the evolution of accreting black hole binaries using data from X-ray telescopes such as RXTE, NICER, NuSTAR, XMM-Newton, Chandra, HXMT, and INTEGRAL. These systems exhibit complex behaviors during outbursts, but current methods of study typically examine only isolated observations and single data products at a time. This fragmented approach limits our ability to form a comprehensive understanding of black hole evolution. Due to the large volume and complexity of X-ray telescope data, it's challenging to visualize the evolution of black hole systems. The current practice of analyzing one observation and one product at a time prevents researchers from efficiently identifying patterns and interactions across different observational parameters. To address this issue, we are creating a tool that aggregates & visualizes key data products, such as energy spectra and light curves, across time and instruments. This provides a unified view of black hole evolution.
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Familiarization Phase (Initial Phase): Study the data and products from multiple X-ray observatories (e.g., RXTE, NICER, NuSTAR). Understand the types of observations and data products relevant to black hole binaries.
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Database and Visualization Tool (First Evaluation Deliverable): Build a database containing cleaned and pre-processed data files. Generate secondary data products (e.g., spectra, energy bands, light curves). Develop a graphical interface that interacts with the database to allow visualization over time.
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Classification and Advanced Analysis (Final Evaluation Deliverable): Use machine learning techniques to classify observations based on their properties. Lay the foundation for more advanced modeling and multi-wavelength data integration in the tool.
Community Bonding period (May 8 - June 1): This time (about 3 weeks) should be used to complete the first milestone. We will ensure our programming environment is downloaded, up to date and we have everything we need to work on this project. We will also begin with getting familiar with the different Xray telescopes we will potentially use data from.
Week 1(June 2): We will begin setting up our environment for data reduction through NICER. This process involves multiple steps such as accessing and downloading our data we will work with, download key components used for data reduction and ensure we have all the necessary components for pipeline processing in NICER.
Weeks 2-4(June 9 -June 23): Clean files will have been created and we start creating and analyzing our secondary products. This will include completing spectra and light curve analysis through NICER.
Weeks 5-8(June 30-July 21): We will complete background estimation and filter our data. July 18 : Midterm Evaluation
Weeks 9-10(July 28-August 4): Data analysis and calibration will begin. Weeks 11-13(August 11-August 25): These final weeks will be used to classify our products and introduce our machine learning techniques to complete this step. Final week(August 21-28): In the final week, our work will be finalized and prepared for the final evaluation.
#GSoC ##Have you ever participated previously in GSoC? When? With which project? NO
NO
I'm a new mother, my baby will be about 6-8 months old during this program. I have a planned trip out of town for my baby's baptism, this will be in June during a weekend. Other than this, I'm fully available complete. to this project.
I understand that being a new mother comes with a lot of responsibilities, even taking up time, but I'm confident I'm fully capable of completing this project within the timeline guidelines. I'm passionate about contributing to the organization for the experience and mentorship. I believe I would bring a lot to the team and we will make great accomplishments together.