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Analyzer of Spectra for Age Determination (ASAD) is a new package that can easily predict the age and reddening of stellar clusters from their observed optical integrated spectra by comparing them to synthesis model spectra. The ages…
The analysis of optical spectra - emission or absorption -- has been arguably the most powerful approach for discovering and understanding matters. The invention and development of many kinds of spectrometers have equipped us with versatile…
Wide field small aperture telescopes are widely used for optical transient observations. Detection and classification of astronomical targets in observed images are the most important and basic step. In this paper, we propose an…
Foundation models are beginning to impact stellar spectroscopy, where spectra encode rich physical information in a structured, language-like form. A key challenge is adapting these models across heterogeneous surveys with differing…
The rapid growth of imaging and spectroscopic surveys has intensified the need for efficient tools that support visual inspection, a practice that remains essential for tasks such as classification, catalog refinement, and validation of…
Wavelength calibration is a routine and critical part of any spectral work-flow, but many astronomers still resort to matching detected peaks and emission lines by hand. We present RASCAL (RANSAC Assisted Spectral CALibration), a python…
We present DASH (Deep Automated Supernova and Host classifier), a novel software package that automates the classification of the type, age, redshift, and host galaxy of supernova spectra. DASH makes use of a new approach that does not rely…
Stellar activity interferes with precise radial velocity measurements and limits our ability to detect and characterize planets, particularly Earth-like planets. We introduce \aestra (Auto-Encoding STellar Radial-velocity and Activity), a…
To help improve the safety and accessibility of indoor spaces, researchers and health professionals have created assessment instruments that enable homeowners and trained experts to audit and improve homes. With advances in computer vision,…
CASA, the Common Astronomy Software Applications package, is the primary data processing software for the Atacama Large Millimeter/submillimeter Array (ALMA) and NSF's Karl G. Jansky Very Large Array (VLA), and is frequently used also for…
We present a method for automated classification of galaxies with low signal-to-noise (S/N) spectra typical of redshift surveys. We develop spectral simulations based on the parameters for the 2dF Galaxy Redshift Survey, and with these…
The expansion of satellite constellations poses a significant challenge to optical ground-based astronomical observations, as satellite trails degrade observational data and compromise research quality. Addressing these challenges requires…
EAS arrays are survey instruments able to monitor continuously all the overhead sky. Their sensitivity in the sub-TeV/TeV energy domain cannot compete with that of Cherenkov telescopes, but the wide field of view (about 2 sr) is ideal to…
Rapid assessment after a natural disaster is key for prioritizing emergency resources. In the case of landslides, rapid assessment involves determining the extent of the area affected and measuring the size and location of individual…
The upcoming generation of telescopes, instruments, and surveys is poised to usher in an unprecedented "Big Data" era in the field of astronomy. Within this context, even seemingly modest tasks such as spectral line analyses could become…
In this paper, we introduce ASDKit, a toolkit for anomalous sound detection (ASD) task. Our aim is to facilitate ASD research by providing an open-source framework that collects and carefully evaluates various ASD methods. First, ASDKit…
We present the design of the prototype telescope and spectrograph system for the Affordable Multiple Aperture Spectroscopy Explorer (AMASE) project. AMASE is a planned project that will pair 100 identical multi-fiber spectrographs with a…
Spectral vision task plays a pivotal role in extracting discriminative spectral-spatial features from high-dimensional data, enabling fine-grained identification beyond human vision. Traditional methods usually involve first collecting rich…
Context: Given the current big data era in Astronomy, machine learning based methods have being applied over the last years to identify or classify objects like quasars, galaxies and stars from full sky photometric surveys. Aims: Here we…
Humans have the ability to utilize visual cues, such as lip movements and visual scenes, to enhance auditory perception, particularly in noisy environments. However, current Automatic Speech Recognition (ASR) or Audio-Visual Speech…