A GNN surrogate model for HTS magnet circuits achieves 4.3% mean MAPE on voltage prediction within the tested design space and supports zero-shot and few-shot generalization to new topologies.
A Surrogate model for High Temperature Superconducting Magnets to Predict Current Distribution with Neural Network,
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SuperCond-GNN: Scalable Graph Neural Network Surrogate for Superconducting Circuit Simulations
A GNN surrogate model for HTS magnet circuits achieves 4.3% mean MAPE on voltage prediction within the tested design space and supports zero-shot and few-shot generalization to new topologies.