A conditional graph neural network serves as an accurate and fast surrogate for semi-analytic galaxy formation models, predicting key properties across cosmic time.
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Galaxy properties in IllustrisTNG form a continuum across the multiscale caustic skeleton, with formation time of web components influencing colors and star formation activity.
IRMaGiC extends redMaGiC to z=1-2 using joint LSST optical and Roman infrared data, reducing photo-z scatter and bias for LRGs.
citing papers explorer
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A graph-based Neural Network surrogate model for accelerating semi-analytical model of galaxy formation and evolution
A conditional graph neural network serves as an accurate and fast surrogate for semi-analytic galaxy formation models, predicting key properties across cosmic time.
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Galaxy Populations in the IllustrisTNG Caustic Skeleton
Galaxy properties in IllustrisTNG form a continuum across the multiscale caustic skeleton, with formation time of web components influencing colors and star formation activity.
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IRMaGiC: Extending Luminous Red Galaxy Selection into the Infrared with Joint Rubin Observatory's Large Survey of Space Time and Roman's High Latitude Imaging Survey
IRMaGiC extends redMaGiC to z=1-2 using joint LSST optical and Roman infrared data, reducing photo-z scatter and bias for LRGs.