add 'What we actually tested' section

README.md

@@ -127,6 +127,27 @@ scripts/export_heart.py  checkpoint → dynamic ONNX exporter
 `examples/inputs/` also contains the original Real-ESRGAN test images, so you
 can inspect full-size inputs and run the models yourself.
 
+## What we actually tested
+
+Every design choice came from a measured experiment, not a guess. The full log
+(including dead ends, benchmarks and the "considered and decided" register) is
+in [`docs/EXPERIMENTS.md`](docs/EXPERIMENTS.md). Highlights:
+
+- **HEART vs HAT_M** (30k, identical settings): effectively a tie on quality
+  (25.02 vs 25.05 dB, within noise) at **~half the peak VRAM** (1.44 vs
+  2.84 GB), and **~1.16-1.24x faster + ~2.7x less VRAM at inference in bf16**
+  (the deployment-relevant precision).
+- **ATD**: OOM'd at iter 1 on a 12 GB card on the same config — a real
+  deployment result.
+- **torch.compile**: ~1.5x training speed, quality-neutral (validated).
+- **i-LN** (norm choice) for stable bf16 AMP with no fp32 gymnastics.
+- **RIB** replaces HAT's relative-position-bias table + OCAB with a
+  FlashAttention-friendly dot product.
+- **Shifted-window bug** found and fixed during ablations (it was quietly
+  costing quality).
+- **OTF GAN lq96 window alignment**: diagnosed the bright band + tile grid and
+  fixed it via the `lq_size` multiple-of-32 rule.
+
 ## Relation to NERVE
 
 HEART and NERVE are the two members of the **BODY** suite (by Philip Hofmann):