Spectroscopy and Image Analysis of Celestial Bodies Using Mathematica and ImageJ
Major
Physics
Second Major
Computer Science
Submission Type
Poster
Area of Study or Work
Physics
Faculty Advisor
Marc Tiritilli
Location
CNS Atrium
Start Date
4-12-2025 11:15 AM
End Date
4-12-2025 12:15 PM
Abstract
Building upon previous work, this project focuses on utilizing Mathematica and ImageJ for spectroscopy and image analysis of various celestial objects, including stars, planets, and potentially nebulae and comets. By capturing and processing spectral data, we aim to analyze the composition, motion, and physical properties of these objects. This project serves as a hands-on opportunity for students to develop computational and analytical skills relevant to spectroscopy, which are highly applicable to fields such as materials science and engineering, astronomy, astrophysics, etc. We will employ image processing techniques to enhance spectral data and explore how computational tools can improve the accuracy and efficiency of spectral analysis. Our work will involve capturing spectral images, calibrating data, and applying mathematical models to interpret results, checking our results with RSPEC software. Through this approach, we’ll gain experience in data acquisition, image processing, coding, and quantitative analysis.
Spectroscopy and Image Analysis of Celestial Bodies Using Mathematica and ImageJ
CNS Atrium
Building upon previous work, this project focuses on utilizing Mathematica and ImageJ for spectroscopy and image analysis of various celestial objects, including stars, planets, and potentially nebulae and comets. By capturing and processing spectral data, we aim to analyze the composition, motion, and physical properties of these objects. This project serves as a hands-on opportunity for students to develop computational and analytical skills relevant to spectroscopy, which are highly applicable to fields such as materials science and engineering, astronomy, astrophysics, etc. We will employ image processing techniques to enhance spectral data and explore how computational tools can improve the accuracy and efficiency of spectral analysis. Our work will involve capturing spectral images, calibrating data, and applying mathematical models to interpret results, checking our results with RSPEC software. Through this approach, we’ll gain experience in data acquisition, image processing, coding, and quantitative analysis.