Neural Operator Surrogates for Two-Dimensional Neutron Flux Estimation
Article summary
Quick briefing — cleaned from the original RSS feed
arXiv:2607.19388v1 Announce Type: new Abstract: This work extends our one-dimensional single-sweep neural-operator studies to two dimensions. We consider one-group transport with isotropic scattering. As in the one-dimensional work, we use Fourier neural operators (FNOs) to approximate the high-fidelity scalar flux. Additionally, we also investigate U-shaped neural operators (UNOs) in this study. We consider three surrogates. The first two map the material and source fields directly to the…
1Key Takeaways
- arXiv:2607.19388v1 Announce Type: new Abstract: This work extends our one-dimensional single-sweep neural-operator studies to two dimensions.
- We consider one-group transport with isotropic scattering.
- As in the one-dimensional work, we use Fourier neural operators (FNOs) to approximate the high-fidelity scalar flux.
- Additionally, we also investigate U-shaped neural operators (UNOs) in this study.
2AIWedia Score
10/10
Must-read — high impact for AI builders
Based on source trust, recency, category impact, and story depth.
3Why it matters
Research breakthroughs often arrive in products months later—early signals matter for strategy. arXiv ML reports that arXiv:2607.19388v1 Announce Type: new Abstract: This work extends our one-dimensional single-sweep neural-operator studies to two dimensions.
Explore related
Browse toolsRelated tools
Research news
Explore curated research tools on AIWedia — compare, rank, and launch from our directory.
Full story on arXiv ML
Read full articleHeadlines aggregated via RSS for discovery on AIWedia. Original content © arXiv ML. We link to the source and do not republish full articles.