AIIC AI Intelligence Centre

SOURCE-LINKED INTELLIGENCE

Decomposition-Guided Diffusion Language Models for Inertial Confinement Fusion Prediction

arXiv · AI, language, vision and robotics · article · Sep 7, 2026 · UTC

Inertial confinement fusion (ICF) is a leading pathway toward clean energy, but each shot at the National Ignition Facility costs on the order of one million dollars, making accurate AI surrogates a high-value target. We study exogenous-driven ICF waveform prediction, where a 512-step neutron-rate diagnostic must be inferred directly from a laser pulse and target design parameters, with no historical response observed. The regime stresses standard time-series predictors with temporal sparsity (picosecond peak in a nanosecond window), input-output scale mismatch (under 300 real shots), and peak

Read original source ↗ Open in workspace

recordType
paper
region
Global

Evidence & attribution

First collected: 2026-09-20T20:32:20.942Z. This is not the publication date.