Ver 1.31

Initial Condition (IC) Support: All models now require (q0, p0) as input
- New forward signature: model(V, t, ic) where ic = (batch, 2)
- ICEmbedding module added for conditioning
- Additive conditioning in decoder: x = x + ic_embed(ic)
Autoregressive Long-term Prediction: Chain multiple windows using predicted endpoints
- New function: autoregressive_predict(model, V, n_windows, ...)
Data Pipeline Updates:
- load_data() now returns (V, t, q, p, ic) with IC extracted from q[:, 0], p[:, 0]
- solvers.rs and true_trajectories.jl use actual IC from data (not origin)
Build System: just build-cargo now builds only required binaries (neural_hamilton, relevant, solvers)
Breaking Change: Existing checkpoints incompatible (new ic_embed layers)

Ver 1.30

Introduce NDIFFCONFIG to control the number of different time configurations per potential.
- This version uses NDIFFCONFIG=2 by default, which means two different time configurations per potential.