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README.md

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+---
+license: other
+title: RFT Adaptive Computing Kernel
+sdk: gradio
+emoji: 🚀
+colorFrom: yellow
+colorTo: pink
+short_description: Adaptive RFT kernel computing stability and coherence metric
+---
+# 🧠 RFT Adaptive Computing Kernel (v1.0)
+
+The **Rendered Frame Theory (RFT) Adaptive Computing Kernel** simulates harmonic stability and coherence across CPU, GPU, and TPU environments.  
+It benchmarks computational self-stabilisation under varying workloads and randomised system noise, providing a verified proof log for every run.
+
+---
+
+## ⚙️ How It Works
+Each simulation dynamically generates:
+- **QΩ (Stability Metric):** Reflects harmonic equilibrium of compute operations.  
+- **ζ_sync (Coherence Metric):** Measures synchronization under fluctuating workloads.  
+- **rate_items_per_sec:** Estimated throughput (adaptive, noise-adjusted).  
+- **SHA-512 Sealed Log:** Each run produces a cryptographically signed verification record.
+
+---
+
+## 🧩 Parameters
+| Parameter | Description |
+|------------|--------------|
+| **Compute Profile** | CPU, GPU, or TPU mode |
+| **Workload Type** | Matrix, Transformer, or Mixed |
+| **Cycles** | Number of operational iterations |
+| **Seed** | Random seed for reproducibility |
+
+---
+
+## 📊 Output Example
+```json
+{
+  "profile": "GPU",
+  "workload": "transformer",
+  "cycles": 5,
+  "rate_items_per_sec": 8.12e+08,
+  "QΩ": 0.841,
+  "ζ_sync": 0.792,
+  "status": "nominal",
+  "timestamp_utc": "2025-10-29T15:02:14Z",
+  "sha512": "..."
+}