???? New technology for the search for intelligent extraterrestrial life

2023-11-04 07:00:06

The search for intelligent extraterrestrial life is armed with a new technique. An international collaboration aims to listen to the Universe on unexplored frequencies, bringing a breath of fresh air to the hunt for “technosignatures”.

The discovery of technosignatures might represent a major turning point in our understanding of the universe. By detecting radio signals or other forms of artificial emissions from other worlds, scientists would provide tangible proof of the existence of intelligent life outside our planet. planet is a celestial body orbiting the Sun or another star…). Not only would it answer one of humanity’s most fundamental questions – are we alone in the universe? – but it would also open a new chapter in the study of civilizations and their possible evolution, thus enriching our perspectives in astrophysics (Astrophysics (from the Greek astro = star and physiqui = physics) is a branch…), in philosophy and even ethics. Astrophysicists from Trinity College in Dublin and the Onsala Space Observatory in Sweden are tracking radio signals from other worlds. To do this, they use the LOFAR telescopes located in Ireland and Sweden. These devices target millions of star systems, marked as interesting by the Gaia and TESS space missions.

So far, the search for extraterrestrial signals has focused on frequencies above 1 GHz. This choice was limited by the capabilities of the unique telescopes used. The new collaboration diversifies sites and equipment, making it possible to probe lower frequencies, between 110 and 190 MHz. The multi-site method reduces the risk of “false positives”, these signals coming from terrestrial human sources. The Breakthrough Listen program (Listen is a free audio player.) is at the forefront of this quest, developing dedicated instruments at LOFAR stations.

According to Owen Johnson, a doctoral candidate at Trinity, improvements are planned for LOFAR. These upgrades will make it possible to explore even more star systems, with the help of machine learning techniques to process enormous volumes of data (In information technology (IT), data is an elementary description, often…).

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