We use a probability theory framework to discuss the search for biosignatures.
DolphinGemma, a large language model developed by Google, is helping scientists study how dolphins communicate — and hopefully find out what they’re saying, too.
Searching for planets analogous to Earth in terms of mass and equilibrium temperature is currently the first step in the quest for habitable conditions outside our Solar System and, ultimately, […]
With upcoming sample return missions across the solar system and the increasing availability of mass spectrometry data, there is an urgent need for methods that analyze such data within the […]
A team from the University of Bern and the National Centre of Competence in Research (NCCR) PlanetS has developed a machine learning model that predicts potential planetary systems with Earth-like […]
The search for atmospheric biosignatures in Earth-like exoplanets is one of the most pressing challenges in observational astrobiology. Detecting biogenic gases in terrestrial planets requires high resolution and long integration […]
University of Queensland scientists have helped to construct a detailed timeline for bacterial evolution, suggesting some bacteria used oxygen long before evolving the ability to produce it through photosynthesis.
In recent decades, artificial intelligence (AI) including machine learning (ML) have become vital for space missions enabling rapid data processing, advanced pattern recognition, and enhanced insight extraction.
We present the progress of work to streamline and simplify the process of exoplanet observation by citizen scientists.
Future missions to icy ocean worlds (OW) such as Europa and Enceladus will evaluate the habitability and potential for biosignatures on these worlds.
