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Merged
ivanbasov merged 6 commits into from
Apr 11, 2026
Merged

docs(readme): add images and shields badges #65

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7f0f6c8
fix(ci): disable torch.compile in orientation training to prevent seg…
ivanbasov Mar 30, 2026
9d3fa08
Revert "fix(ci): disable torch.compile in orientation training to pre…
ivanbasov Mar 30, 2026
838d14f
Merge remote-tracking branch 'upstream/main'
ivanbasov Apr 3, 2026
32d20ae
docs(readme): add pipeline diagram and LER results images
ivanbasov Apr 11, 2026
336a9cc
docs(readme): add shields badges (license, release, paper, HF models)
ivanbasov Apr 11, 2026
c86d01c
chore: merge ising/main and resolve README conflict
ivanbasov Apr 11, 2026
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17 changes: 17 additions & 0 deletions README.md
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# Ising Decoding

[![License](https://img.shields.io/badge/License-Apache%202.0-blue)](./LICENSE)
[![Release](https://img.shields.io/badge/Release-v0.1.0-brightgreen)](https://github.com/NVIDIA/Ising-Decoding/tree/releases/v0.1.0)
[![Paper](https://img.shields.io/badge/Paper-NVIDIA%20Research-76b900)](https://research.nvidia.com/publication/2026-04_fast-ai-based-pre-decoders-surface-codes)
[![Model: Fast](https://img.shields.io/badge/🤗%20HuggingFace-Fast%20Model-ffd21e)](https://huggingface.co/nvidia/Ising-Decoder-SurfaceCode-1-Fast)
[![Model: Accurate](https://img.shields.io/badge/🤗%20HuggingFace-Accurate%20Model-ffd21e)](https://huggingface.co/nvidia/Ising-Decoder-SurfaceCode-1-Accurate)

This repo offers AI training frameworks and recipes to build, customize and deploy scalable quantum error correction **decoders**:

- A neural network consumes detector syndromes across space **and** time
Expand All @@ -8,6 +14,8 @@ This repo offers AI training frameworks and recipes to build, customize and depl

The public release exposes a **single user-facing config** and a **single runner script**.

![Pre-decoder pipeline](images/predecoder_pipeline.png)

### Quick start (train + inference)

From the repo root:
Expand Down Expand Up @@ -557,6 +565,15 @@ dispatch:
| `gpu-tests` | GPU | Full test suite on a self-hosted GPU runner |
| `gpu-tests` (train+inference) | GPU | Short train + inference with LER check |

## Results

Logical error rate (LER) vs. time for X-basis decoding at physical error rates p = 0.003 and 0.006:

<picture>
<source media="(prefers-color-scheme: dark)" srcset="images/ler_vs_time_model_card_p0.003_0.006_X_dark.svg">
<img src="images/ler_vs_time_model_card_p0.003_0.006_X_light.svg" alt="LER vs time (X basis, p=0.003–0.006)">
</picture>

## License

This project is released under the [Apache License 2.0](LICENSE).
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