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A Graph-based Neural-network Surrogate Model for an Accelerating Semianalytical Model of Galaxy Formation and Evolution

  • Authors: Xuejie Li, Zhongxu Zhai, Xiaohu Yang, Andrew Benson, Yun Wang

Xuejie Li et al 2026 The Astrophysical Journal Supplement Series 286 .

  • Provider: AAS Journals

Caption: Figure 2.

Schematic overview of the model pipeline. Halo merger trees are encoded by a shared GNN backbone, conditioned on the SAM parameter vector for the catalog and evaluated with separate prediction heads for each redshift. In the current architecture, M, Lz ,and J are modeled with heteroscedastic regression heads, while sSFR and MZ,gas are modeled with mixture-of-experts heads.

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