Spatiotemporal techniques for signal coordination with actively transmitting extraterrestrial civilizations, without the need for prior communication, can constrain technosignature searches to a significantly smaller coordinate space.
AI – Data – Apps – Cybernetics
Reinforcement Learning Allows Underwater Robots To Locate And Track Objects Underwater
Editor’s note: When we send robotic submersibles and rovers to other worlds to search for life in remote and hostile environments, we’re going to our droids to be as smart […]
Machine-learning Identified Molecular Fragments Responsible For Infrared Emission Features Of Polycyclic Aromatic Hydrocarbons
Machine learning feature importance calculations are used to determine the molecular substructures that are responsible for mid and far-infrared (IR) emission features of neutral polycyclic aromatic hydrocarbons (PAHs).
When ET calls, Can We Be Sure We’re Not Being Spoofed?
Scientists have devised a new technique for finding and vetting possible radio signals from other civilizations in our galaxy — a major advance in the search for extraterrestrial intelligence (SETI) […]
Information Gain as a Tool for Assessing Biosignature Missions
We propose the mathematical notion of information gain as a way of quantitatively assessing the value of biosignature missions.
Training Robots How To Learn And Make Their Own Decisions On The Fly
Mars rovers have teams of human experts on Earth telling them what to do. But robots on lander missions to moons orbiting Saturn or Jupiter are too far away to […]
Revisiting Equilibrium Condensation And Rocky Planet Compositions: Introducing The ECCOplanets Code
We introduce ECCOplanets, an open-source Python code that simulates condensation in the protoplanetary disk.
Away Team Tech: Proxima Centauri Interstellar Flyby Scientific Data Downlink Design
Editor’s note: one of the prime interests in the Proxima Centauri system (in addition to its proximity to Earth) is the presence of at least one of three detected planets […]
Combining Multi-spectral Data With Statistical And Deep-learning Models For Improved Exoplanet Detection In Direct Imaging At High Contrast
Exoplanet detection by direct imaging is a difficult task: the faint signals from the objects of interest are buried under a spatially structured nuisance component induced by the host star. […]
Using A Neural Network Approach To Accelerate Disequilibrium Chemistry Calculations In Exoplanet Atmospheres
In this era of exoplanet characterisation with JWST, the need for a fast implementation of classical forward models to understand the chemical and physical processes in exoplanet atmospheres is more […]
