Master's Thesis: Deep Learning for Microlensing Event Classification

Author: Kunal Bhatia
Institution: [Your University]
Degree: Master of Science
Target Journal: Astronomy & Astrophysics / MNRAS

Abstract

Early classification of gravitational microlensing events using 1D CNNs with TimeDistributed architecture for real-time LSST survey operations.

Structure

• Chapter 1: Introduction (6 pages, 2,000 words)
• Chapter 2: Theoretical Background (10 pages, 3,500 words)
• Chapter 3: Literature Review (10 pages, 3,500 words)
• Chapter 4: Methodology (12 pages, 4,000 words)
• Chapter 5: Results (15 pages, 5,000 words)
• Chapter 6: Discussion (8 pages, 2,500 words)
• Chapter 7: Conclusions (4 pages, 1,500 words)

Total: ~60 pages, ~22,000 words

Compilation

make          # Full compilation
make quick    # Quick compile (no biber)
make clean    # Remove auxiliary files
make view     # View PDF

Related Repositories

• Code: https://github.com/kunalb541/thesis-microlensing
• Data: [HPC storage path]

Status

• Chapter 1: Introduction
• Chapter 2: Theory
• Chapter 3: Literature Review
• Chapter 4: Methodology
• Chapter 5: Results (awaiting training)
• Chapter 6: Discussion
• Chapter 7: Conclusions

Timeline

• Week 1-2: Chapters 1-3
• Week 3-4: Chapter 4
• Week 5: Training + Results
• Week 6-7: Chapters 5-6
• Week 8: Chapter 7 + Final edits