Search Results for author:
Found 6 papers, 1 papers with code
Machine learning for exoplanet detection in high-contrast spectroscopy Combining cross correlation maps and deep learning on medium-resolution integral-field spectra
Through this paper, we demonstrate that ML techniques have the potential to improve the detection limits and reduce false positives for directly imaged planets in IFS datasets, after transforming the spectral dimension into a radial velocity dimension through a cross-correlation operation.
Machine Learning for Exoplanet Detection in High-Contrast Spectroscopy: Revealing Exoplanets by Leveraging Hidden Molecular Signatures in Cross-Correlated Spectra with Convolutional Neural Networks
Once trained, MLCCS methods offer sensitive and rapid detection of exoplanets and their molecular species in the spectral dimension.
Photonic Structures Optimization Using Highly Data-Efficient Deep Learning: Application To Nanofin And Annular Groove Phase Masks
This study aims to introduce a surrogate optimization framework for these devices.
NA-SODINN: a deep learning algorithm for exoplanet image detection based on residual noise regimes
Supervised deep learning was recently introduced in high-contrast imaging (HCI) through the SODINN algorithm, a convolutional neural network designed for exoplanet detection in angular differential imaging (ADI) datasets.
Improving the RSM map exoplanet detection algorithm: PSF forward modelling and optimal selection of PSF subtraction techniques
Finally, we present a new framework to generate contrast curves based on probability maps.
Instrumentation and Methods for Astrophysics Earth and Planetary Astrophysics
High contrast imaging for the enhanced resolution imager and spectrometer (ERIS)
ERIS is a diffraction limited thermal infrared imager and spectrograph for the Very Large Telescope UT4.
Instrumentation and Methods for Astrophysics
