A GAN framework is trained on EAGLE simulation merger trees to generate new realistic trees for semi-analytic galaxy models at modest computational cost.
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UNVERDICTED 3representative citing papers
COLIBRE simulations underpredict bright-end UV galaxy luminosities by 1 to 2.5 magnitudes at z=7-15 compared with observations, with the discrepancy persisting after dust attenuation and uncertainty accounting.
DESI DR2 yields galaxy luminosity functions showing non-power-law faint-end behavior and bright-end deviations, with good North-South agreement and reduced errors compared to GAMA.
citing papers explorer
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A Halo Merger Tree Generation and Evaluation Framework
A GAN framework is trained on EAGLE simulation merger trees to generate new realistic trees for semi-analytic galaxy models at modest computational cost.
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The galaxy ultraviolet luminosity function from $z=7$ to $15$ in the COLIBRE simulations
COLIBRE simulations underpredict bright-end UV galaxy luminosities by 1 to 2.5 magnitudes at z=7-15 compared with observations, with the discrepancy persisting after dust attenuation and uncertainty accounting.
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DESI DR2 Galaxy Luminosity Functions
DESI DR2 yields galaxy luminosity functions showing non-power-law faint-end behavior and bright-end deviations, with good North-South agreement and reduced errors compared to GAMA.