Feedback-driven winds from star formation or active galactic nuclei might be a relevant channel for the abrupt quenching of star formation in massive galaxies. However, both observations and simulations support the idea that these processes are non-conflictingly co-evolving and self-regulating. Furthermore, evidence of disruptive events that are capable of fast quenching is rare, and constraints on their statistical prevalence are lacking. Here we present a massive starburst galaxy at redshift z=1.4, which is ejecting ~46% of its molecular gas mass at a startling rate of >10,000 solar masses per year. A broad component that is red-shifted from the galaxy emission is detected in four (low and high J) CO and [C I] transitions and in the ionized phase, which ensures a robust estimate of the expelled gas mass. The implied statistics suggest that similar events are potentially a major star-formation quenching channel. However, our observations provide compelling evidence that this is not a feedback-driven wind, but rather material from a merger that has been probably tidally ejected. This finding challenges some literature studies in which the role of feedback-driven winds might be overstated.
It may interest you
-
El Instituto de Astrofísica de Canarias y la empresa tecnológica han firmado un protocolo general de actuación para el desarrollo conjunto de instrumentación avanzada en los rangos MWIR y LWIR . El Instituto de Astrofísica de Canarias (IAC) y la empresa de alta tecnología de imagen infrarroja SENSIA Solutions, S.L. (SENSIA) han formalizado este viernes, 20 de marzo de 2026, un Protocolo General de Actuación con el objetivo de establecer un marco estratégico de colaboración científica y tecnológica . La colaboración se ha formalizado con la firma de este protocolo por parte de ValentínAdvertised on -
From 2–6 March 2026, Ghent University will host a landmark event at the intersection of astrophysics and artificial intelligence. Jointly organized by the EDUCADO , MWGaiaDN , and alongside a third partnering TALES , all MSCA Doctoral Networks. The EDUCADO Training School on Astro–AI and Machine Learning will bring together leading experts and early-career researchers to tackle the data challenges of modern science. The five-day programme offers a blend of expert-led lectures and hands-on training sessions. The curriculum focuses on high-impact fields, including artificial intelligenceAdvertised on -
Científicos del IAC publican en Nature Astronomy una guía práctica para mejorar propuestas y solicitudesAdvertised on