The spectrographs WEAVE and 4MOST, both on 4m class telescopes, are two predecessors to the innovative WST facility.
Both spectrographs are characterized by high multiplexing capabilities over a large field of view (i.e., 3-4 sq. deg), wide optical spectral coverage (3700 - 9700 Å), and optimal resolution (R=4000-7000). StePS is the acronym for two surveys that make use of the WEAVE and...
The Wide-Field Spectroscopic Telescope (WST) will revolutionize astronomical spectroscopy in the 2040s by generating an unprecedented volume of data for the field: tens of thousands to millions of spectra hourly ($\sim$1 TB/night of raw science data).
While the raw data rate per se is modest compared to other facilities (like SKA), the complexity of spectroscopic data processing presents...
WST will deliver datasets of such staggering volume and complexity that conventional analysis methods will be rendered obsolete.
Much faster, precise and independent of our models, artificial intelligence emerges as the indispensable engine of discovery.
The current landscape of machine learning in astronomy, particularly in spectroscopic analysis, faces two critical limitations. The...
We developed a novel generated neural network to reconstruct the rest-frame spectra by giving the observed spectra and their flux error. This network provided all the necessary information for modeling spectra, including the eigenspectra and coefficient. Using this reconstruction, we can achieve the classifying, redshift estimation, and anomaly detection in the same framework. Our test...
