The Atacama Large Millimetre/submillimetre Array (ALMA) is the world's most advanced radio interferometric facility, producing science data with an average rate of about 1 TB per day. After a process of calibration, imaging and quality assurance, the scientific data are stored in the ALMA Science Archive (ASA), along with the corresponding raw data

The observation of Near Earth objects (NEOs) allows us to study the physical properties of the smallest size bodies of our Solar System and help impose constraints on their origin and evolution. The solar phase curve is a very important tool to derive diverse physical properties of a small body so that we set up an observational campaign to derive

Local primordial non-Gaussianity (PNG) is a promising observable of the underlying physics of inflation, characterized by $f_{\rm NL}^{\rm loc}$. We present the methodology to measure $f_{\rm NL}^{\rm loc}$ from the Dark Energy Survey (DES) data using the two-point angular correlation function (ACF) with scale-dependent bias. One of the focuses of

LiteBIRD, the Lite (Light) satellite for the study of B-mode polarization and Inflation from cosmic background Radiation Detection, is a space mission for primordial cosmology and fundamental physics. The Japan Aerospace Exploration Agency (JAXA) selected LiteBIRD in May 2019 as a strategic large-class (L-class) mission, with an expected launch in

Photochemistry is a fundamental process of planetary atmospheres that regulates the atmospheric composition and stability 1. However, no unambiguous photochemical products have been detected in exoplanet atmospheres so far. Recent observations from the JWST Transiting Exoplanet Community Early Release Science Program 2,3 found a spectral absorption

The large amounts of astrophysical data being provided by existing and future instrumentation require efficient and fast analysis tools. Transfer learning is a new technique promising higher accuracy in the derived data products, with information from one domain being transferred to improve the accuracy of a neural network model in another domain