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 […]
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.
The search for exoplanets is an active field in astronomy, with direct imaging as one of the most challenging methods due to faint exoplanet signals buried within stronger residual starlight.
Next-generation telescopes will bring groundbreaking discoveries but they will also present new technological challenges. The Square Kilometre Array Observatory (SKAO) will be one of the most demanding scientific infrastructures, with […]
In this work, we explore the potential of machine learning, specifically Neural Operators, to emulate the Grackle chemistry solver, which is widely used in cosmological hydrodynamical simulations.
![The [Na/Fe] vs. [Fe/H] abundance plot (Ensemble 4) showing the stars that are most likely to host a planet (green), the known planet hosts (blue), and the stars less likely to host a planet (orange). Histograms are also included that show the [Na/Fe] relative distribution to the right of the scatterplot and [Fe/H] relative distribution at the top. We note the clear sub-solar Na abundances for each experiment’s known and predicted planet hosts (see Section 5). - Small planets -- astro-ph.EP](https://i0.wp.com/astrobiology.com/wp-content/uploads/2025/03/Utilizing-Machine-Learning-to-Predict.png?resize=1200%2C718&ssl=1)
Stars and their associated planets originate from the same cloud of gas and dust, making a star’s elemental composition a valuable indicator for indirectly studying planetary compositions.
