From the 1 of 12 linked papers with an AI index.
12 papers
Enhancing WISE Infrared Imaging to Spitzer Resolution Using Deep Learning Super-Resolution
Saeed Rezaee, Shoubaneh Hemmati, Bahram Mobasher +4
The paper introduces a deep‑learning model that upscales WISE infrared images to near‑Spitzer resolution, achieving about 4.6× higher spatial detail and improved flux recovery and…
Diffusion-based Galaxy Simulations for the Roman High Latitude Survey
Diana Scognamiglio, Jake H. Lee, Eric Huff +2
Future weak lensing analyses with the Nancy Grace Roman Space Telescope will require highly realistic image simulations to control shear systematics at unprecedented precision. A k…
Learning to See Sharper: A Physics-Informed Artificial Intelligence Framework for Super-Resolving Galaxy Spectra
Aryana Haghjoo, Shoubaneh Hemmati, Bahram Mobasher +6
The information recoverable from galaxy spectra depends fundamentally on spectral resolution, yet assembling large samples at high resolution remains observationally expensive. We…
Reducing the Dimensions of AGN Lightcurve Manifolds
Shoubaneh Hemmati, Jessica Krick, Daniel Stern +10
The Active Galactic Nuclei (AGN) glossary is vast and complex. Depending on selection method, observing wavelength, and brightness, AGNs are assigned distinct labels, yet the relat…
Mapping the Galaxy Color-Star Formation Rate Relation with Manifold Learning and Infrared Image Stacking
Yu-Heng Lin, Daniel Masters, Andreas L. Faisst +7
Modern surveys present us with billions of faint galaxies for which we only have broadband images in 6-8 optical-to-near-infrared (NIR) filters. Galaxy star formation rates (…
Selection of Dwarf Galaxies Hosting AGNs: A Measure of Bias and Contamination using Unsupervised Machine Learning Techniques
Sogol Sanjaripour, Archana Aravindan, Gabriela Canalizo +4
Identifying AGNs in dwarf galaxies is critical for understanding black hole formation but remains challenging due to their low luminosities, low metallicities, and star formation-d…