# [Solution Title]

**Type:** L4 Solution / Certificate
**Target Benchmark:** [Benchmark + L3-XXX hash]
**Algorithm Author:** [Your wallet address; will be resolved to display name]
**Stake:** None (submission fee covers gas)

---

## Algorithm Description

### High-Level Approach
[1-2 paragraphs explaining the algorithm conceptually. What is the key idea?]

### Innovation / Novelty
[What's new about this approach versus existing methods?]

### Computational Complexity
[Big-O analysis. Memory requirements. Runtime expectations on standard hardware (T4/A10).]

---

## Implementation

### Dependencies
[Required Python packages with version pins. GPU requirements (T4 minimum, A10 if needed).]

### Code Repository
[GitHub URL or IPFS hash. Pin to a specific commit/release.]

### Container
[Docker image tag and SHA256 digest. Reproducibility requires a pinned container.]

### Reproduction Instructions

```bash
# 1. Pull the container
docker pull <image>@sha256:<digest>

# 2. Download the benchmark dataset
# (URL from benchmark page)

# 3. Run the solver
docker run --gpus all <image> python solve.py --input <path>

# 4. Verify the result
# (Output should match the cert hash registered on-chain)
```

---

## Performance on This Benchmark

### Quality Score (Q_int)
[Self-reported. Will be verified by S1-S4 gates during cert issuance.]

### Primary Metric
[e.g., PSNR 35.2 dB, SSIM 0.962. Match the benchmark's defined metric.]

### Runtime
[Wall-clock time on T4 or A10 GPU.]

### Memory Usage
[Peak GPU memory in GB.]

---

## License

[Open-source license required. MIT or Apache 2.0 recommended.]

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## Standards Met

- [ ] Code is open-source and tagged at a specific commit
- [ ] Reproducible via pinned container (digest specified)
- [ ] Performance self-reported on benchmark dataset
- [ ] License specified (MIT, Apache 2.0, BSD, GPL, …)
- [ ] No proprietary dependencies

---

## AI Authoring Notes

Notes for ChatGPT / Claude / other AI tools:

> "Fill in this solution template for benchmark **{target benchmark name}**. My algorithm is **{describe}**. Include real GitHub URL, container digest, and reproduction commands. Self-report performance honestly — the S1-S4 gates will verify. Specify a permissive open-source license. Follow the section structure above exactly. Return the result as a complete MD file."