Exoplanet ThesisEdited just now

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1% main.tex
2\documentclass{article}
3\usepackage{graphicx, amsmath}
4\begin{document}
5\section{Results}
6We detect exoplanets via \emph{contrastive} learning.Alif
7\begin{equation}
8  \mathcal{L} = -\log p
9\end{equation}
10\end{document}

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Detecting Exoplanets with Contrastive Learning

S. S. Antor A. K. Alif · BRAC University

1. Results

We detect faint exoplanets in JWST/MIRI imagery via contrastive learning, separating planetary signals from bright host stars and recovering 92% of injected planets at a false-positive rate below 0.1 per frame.

𝓛= −log p(1)

Figure 1: JWST/MIRI direct imaging of a faint exoplanet (b).

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