Exploring Universe With JWST

An interactive website documenting research carried out during TIFR's NIUS 2025 (National Initiative on Undergraduate Science) programme — covering astronomical image processing and exoplanet transit detection, built from scratch with HTML/CSS/JS and interactive canvas visualizations.

Selected as 1 of ~35 students nationally for TIFR's undergraduate science research programme. This site walks through the methods, code, and findings from that work.

What's inside

index.html — Home

Landing page introducing the project and linking out to each module.

imageprocessing.html — Astronomical Image Processing

CCD image calibration pipeline, built interactive:

• Master Bias Frame Creation — removing read-out noise from raw CCD frames
• Aperture Photometry — with an adjustable-parameter interactive demo
• Image Subtraction (ILMT Data) — interactive reference-vs-difference image comparison for transient detection
• Complete CCD Calibration Pipeline — bias and flat-field correction end-to-end

Simulation_Transient_Curve.html — Transit Light Curve Analysis

A full walkthrough of detecting an exoplanet from light-curve data:

• Loading and cleaning real TESS data (WASP-100)
• PLD systematics correction
• Box Least Squares (BLS) algorithm for period finding
• Transit modelling with batman, parameter fitting via curve_fit
• MCMC posterior sampling for parameter uncertainty

Blogs.html — Field Blogs & Research Notes

Write-ups from the research process, including:

• Detecting an Exoplanet Transit with TESS & Batman
• Why Your Telescope Images Look Terrible (& How to Fix Them)
• Reading the Sun: Coronal Loops & Active Regions with SunPy
• Understanding the BLS Periodogram — Hunting Planets in Noise
• Image Subtraction on ILMT Data — Finding the Invisible
• What the Transit Depth Tells You — Inferring Planetary Properties
• JWST: Two Years of Science and What Comes Next

Built with

Vanilla HTML, CSS, and JavaScript — including hand-built canvas visualizations for the interactive photometry and image-subtraction demos (no external charting libraries).

Underlying analysis was done in Python using lightkurve, batman, ccdproc, photutils, astroalign, and sunpy.

Background

This project grew out of research on exoplanet detection via the Transit Method during TIFR's NIUS programme — modelling stellar light curves, processing CCD imaging data (bias/flat-field correction), and detecting transient objects through image subtraction and alignment.

Author

Mann Sutariya — B.Sc Physics, PDEU mannsutaria2605@gmail.com