首页|Researchers from McGill University Detail Findings in Machine Learning (Machine- learning Recovery of Foreground Wedgeremoved 21-cm Light Cones for High-z Galax y Mapping)
Researchers from McGill University Detail Findings in Machine Learning (Machine- learning Recovery of Foreground Wedgeremoved 21-cm Light Cones for High-z Galax y Mapping)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ma chine Learning. According to news reporting originating in Montreal, Canada, by NewsRx journalists, research stated, "Upcoming experiments will map the spatial distribution of the 21-cm signal over three-dimensional volumes of space during the Epoch of Reionization (EoR). Several methods have been proposed to mitigate the issue of astrophysical foreground contamination in tomographic images of the 21-cm signal, one of which involves the excision of a wedgeshaped region in cy lindrical Fourier space." Funders for this research include Canadian Institute for Advanced Research (CIFA R), Trottier Space Institute, New Frontiers in Research Fund Exploration grant p rogram, Canadian Institute for Advanced Research (CIFAR), Natural Sciences and E ngineering Research Council of Canada (NSERC), Alfred P. Sloan Foundation, Willi am Dawson Scholarship at McGill.
MontrealCanadaNorth and Central Amer icaCyborgsEmerging TechnologiesMachine LearningMcGill University
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