# 3D Particle-Accelerator Benchmarks

GLOBE compresses three-dimensional beam–field states into a compact latent space, learns the dominant evolution with a control-conditioned neural operator, and captures fine-scale residuals with a generative model, then applies parameter-free constraint operators after decoding. On two high-resolution 3D benchmarks, bunched-beam transport and plasma-wakefield acceleration, relative error is 9% and 13% lower than the strongest baseline DPOT, mid-frequency spectral error is 54% and 20% lower, and hours of particle simulation become about a minute per rollout.

GLOBE compresses three-dimensional beam–field states into a compact latent space, learns the dominant evolution with a control-conditioned neural operator, and captures fine-scale residuals with a generative model, then applies parameter-free constraint operators after decoding. On two high-resolution 3D benchmarks, bunched-beam transport and plasma-wakefield acceleration, relative error is 9% and 13% lower than the strongest baseline DPOT, mid-frequency spectral error is 54% and 20% lower, and hours of particle simulation become about a minute per rollout.