Reflectance spectroscopy remains a cornerstone of remote mineralogical analysis of airless bodies. However, traditional spectral unmixing techniques face limitations when dealing with nonlinear mixing, instrument-specific noise, or spectral coverage constraints. To overcome these, we have developed a suite of robust convolutional neural network

The large number of star clusters in nearby galaxies permits us to statistically test the predictions of stellar, dust, and gas models. Using Hubble Space Telescope (HST) broadband plus Hα imaging combined with JWST near-infrared imaging, we use a total of 10 filters spanning near-ultraviolet through near-infrared wavelengths to model key physical

On March 12, 2025, the ESA Hera mission performed a flyby of Mars on the way to its target, the binary asteroid system Didymos-Dimorphos. This event provided a unique opportunity to acquire spectral data (within the 0.65-0.96 micron wavelength range) and high-resolution images of the far side of the Martian moon Deimos. The observations were

We present the SPECDIS value-added stellar distance catalog accompanying DESI Data Release 1. SPECDIS trains a feed-forward neural network (NN) with Gaia parallaxes and gets the distance estimates. To build up an unbiased training sample, we do not apply selections on parallax error or signal-to-noise (S/N) of the stellar spectra, and instead, we