Heaviside-1, a foundation model for electromagnetism
Details
- External ID
- 49524789
- Source
- HN
- Company
- —
- Product
- Heaviside-1, a foundation model for electromagnetism
- Website domain
- arenaphysica.com
- Launched
- Sept. 1, 2026
- Cohort
- —
- Upvotes
- 5
- Upvotes percentile
- 0.12998405103668262
- Tags
- —
- Fetched at
- Sept. 10, 2026, 5:31 a.m.
- Updated at
- Sept. 10, 2026, 5:31 a.m.
Description
Heaviside-1 was trained on 500B field samples from over 250K unique physical layout designs, and is approximately the scale of GPT-2. It predicts a full design's fields ~10^5x faster than a commercial full-wave solver, with S-parameter magnitude error under 1 dB. and generalizes out of distribution.You can play around with the model and a subset of designs including hairpin filters and patch antennas with our Fields Studio. Design, adjust the geometry, and the predicted electric and magnetic fields will update in milliseconds.
Enrichment
- Theme
- scientific computing and deep tech tools
- Vertical
- Horizontal
- Function
- Model & infra
- Audience
- Developer
- AI stance
- AI-native
- Project type
- Commercial product
- Normalized one-liner
- foundation model for electromagnetism
- Manually corrected
- False
Could you build this?
No Heaviside-1 is a scientific foundation model trained on 500 billion physical field samples to simulate Maxwell's equations 100,000x faster than full-wave solvers.
What it would actually take: Requires building large-scale 3D electromagnetic simulation pipelines (e.g., FDTD, FEM solvers) to generate 500B field samples across 250K PCB/package layouts, requiring high-performance computing clusters. The model architecture likely uses neural operators (FNO/DeepONet) or 3D geometric transformers trained on multi-node GPU supercomputers. Building this requires combined expertise in computational electromagnetics, PDE-constrained deep learning, and distributed AI systems.
Discussion
1 comment analyzed.
Competitors
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Attention rank: #11 of 12 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 238 days after the earliest competitor.
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- No other launches for this product.
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