This Science White Paper, prepared in response to the ESA Voyage 2050 call for long-term mission planning, aims to describe the various science possibilities that can be realized with an L-class space observatory that is dedicated to the study of the interactions of cosmic microwave background (CMB) photons with the cosmic web. Our aim is

Context. Hot subdwarfs experienced strong mass loss on the red giant branch (RGB) and are now hot and small He-burning objects. These stars constitute excellent opportunities for addressing the question of the evolution of exoplanetary systems directly after the RGB phase of evolution. Aims: In this project we aim to perform a transit survey in all

Studying the resolved stellar populations of the different structural components that build massive galaxies directly unveils their assembly history. We aim at characterizing the stellar population properties of a representative sample of bulges and pure spheroids in massive galaxies (M ⋆ > 10 10 M ⊙) in the GOODS-N field. We take advantage of the

We present a short update about the Spanish Fireball and Meteorite Recovery Network (in brief known as SPMN) after 25 years of continuous monitoring of the sky over Spain and bordering countries. A recent progress has been done in the development of a unique software called 3D-FireToc, which allows the detection and fully automatic reduction of

There has been a longstanding discrepancy between the experimental measurements of the electron and muon anomalous magnetic moments and their predicted values in the Standard Model. This is particularly relevant in the case of the muon g -2 , which has attracted a remarkable interest in the community after the long-awaited announcement of the first

Large-scale sky surveys have played a transformative role in our understanding of astrophysical transients, only made possible by increasingly powerful machine learning-based filtering to accurately sift through the vast quantities of incoming data generated. In this paper, we present a new real-bogus classifier based on a Bayesian convolutional