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Hierarchical Progressive Survey (HiPS) format: moving from visualisation to scientific analysis
Fabrizio Giordano, Yago Ascasibar, Luca Cortese +2
Context. In the current era of multi-wavelength and multi-messenger astronomy, international organisations are actively working on the definition of new standards for the publicati…
SAS in ESA Datalabs: A New Platform for XMM-Newton Analysis
Esin G. Gulbahar, Camille M. Diez, Aitor Ibarra +6
XMM-Newton is a cornerstone mission of the European Space Agency (ESA) for X-ray astronomy, providing high-quality X-ray data for astrophysical research since the start of the cent…
Deep Learning-Based Super-Resolution and De-Noising for XMM-Newton Images
Sam F. Sweere, Ivan Valtchanov, Maggie Lieu +6
The field of artificial intelligence based image enhancement has been rapidly evolving over the last few years and is able to produce impressive results on non-astronomical images.…
Learning to Denoise Astronomical Images with U-nets
Antonia Vojtekova, Maggie Lieu, Ivan Valtchanov +4
Astronomical images are essential for exploring and understanding the universe. Optical telescopes capable of deep observations, such as the Hubble Space Telescope, are heavily ove…
The Herschel SPIRE Fourier Transform Spectrometer Spectral Feature Finder IV. Neutral Carbon Detection in the SPIRE FTS Spectra
Jeremy P. Scott, Locke D. Spencer, Rosalind Hopwood +2
The SPIRE FTS Spectral Feature Finder (FF), developed within the Herschel Spectral and Photometric Imaging Receiver (SPIRE) Fourier Transform Spectrometer (FTS) instrument team, is…
The Herschel SPIRE Fourier Transform Spectrometer Spectral Feature Finder II. Estimating Radial Velocity of SPIRE Spectral Observation Sources
Jeremy P. Scott, Natalia Hladczuk, Locke D. Spencer +3
The Herschel SPIRE FTS Spectral Feature Finder (FF) detects significant spectral features within SPIRE spectra and employs two routines, and external references, to estimate source…