# Phase 9A Memo: Checkpointed Offline Handoff

**Date**: 2026-03-25
**Config**: CIFAR-10, L=4, d=256, t0=5, 100 epochs, seed=42

## Question
If we offline-train Vec on a DFA checkpoint, can it take over and outperform continuing DFA?

## Results

| Branch | acc@20 | final acc | diff vs DFA |
|--------|--------|-----------|-------------|
| continue_DFA | 0.296 | 0.311 | baseline |
| handoff_to_Vec | 0.307 | 0.300 | -0.011 |
| **handoff_blend_05** | **0.312** | **0.317** | **+0.006** |

Vec quality at frozen t0=5 checkpoint: Gamma=0.229, rho=0.262.

## Key Finding: Blend Handoff Outperforms DFA

**This is Case B**: pure Vec takeover doesn't work, but **50% blend (Vec + DFA) outperforms pure DFA by +0.55%**.

This is the first time any Vec-involving method has beaten DFA on online CIFAR. The blend provides complementary information: DFA gives stable random projections, Vec adds learned directional credit. Neither alone is sufficient, but together they outperform.

## Implications

1. **Cold-start IS the main bottleneck** — offline-fitted Vec can help, confirming Vec is useful on DFA trajectory features.

2. **Pure Vec takeover fails** because once it takes over, the forward net trajectory diverges from what Vec was trained on, and online Vec retraining can't keep up.

3. **Blend works** because DFA provides a stable backbone that prevents trajectory divergence, while Vec contributes useful directional corrections.

4. **Next steps**: Test blend at different alpha values (0.25, 0.75), different t0, and 3 seeds for validation. Also test periodic refit to keep Vec fresh.