Finding White Dwarf-Main Sequence Binaries in Gaia Data with Machine Learning
Despite having recently officially ended its science operations in January, Gaia, one of the most prolific star explorers ever, is still providing new scientific insights. A recent paper pre-published on arXiv (which has not been peer-reviewed but was submitted to the Astrophysical Journal) took another look at some Gaia data to try to find a unique type of astronomical entity - white dwarf stars that are paired up in a binary with a main sequence one. By applying a machine learning technique called a "self-organizing map," they found 801 new white dwarf-main sequence (WDMS) binaries, increasing the total number ever found by over 20%.
Despite having recently officially ended its science operations in January, Gaia, one of the most prolific star explorers ever, is still providing new scientific insights. A recent paper pre-published on arXiv (which has not been peer-reviewed but was submitted to the Astrophysical Journal) took another look at some Gaia data to try to find a unique type of astronomical entity - white dwarf stars that are paired up in a binary with a main sequence one. By applying a machine learning technique called a "self-organizing map," they found 801 new white dwarf-main sequence (WDMS) binaries, increasing the total number ever found by over 20%.
