Add topological modeling for action forward dynamics

[teerthsharma]

Summary

This PR adds Topological Modeling for Cosmos Action Forward Dynamics as one cohesive optional evaluation layer for Cosmos3 action FD rollouts.

It covers the full modeling scope:

• FD/FDTD modeling: adds finite-difference topology traces over rollout state so frame/chunk dynamics have deterministic velocity, acceleration, local-change, and convergence diagnostics.
• Topology metrics: evaluates visual FD rollouts from binary or labeled masks with connected components, hole/loop proxies, Euler-characteristic-style summaries, drift, stability, JSON, and CSV outputs.
• Topological inference: adds compact topology state vectors, weighted sparse-neighborhood distance, Betti-stability windows, and theorem-style convergence gates.
• Swarm robotics extension: adds sparse top-k specialist ranking using topology-aware state similarity, task tags, reliability, cost, and utilization signals.

The helper is side-effect-free. It does not alter default Cosmos3 inference and does not require GPU/model weights/segmentation dependencies for CI-style validation.

Files

• cookbooks/cosmos3/generator/action/topology_helpers.py
  • mask topology metrics
  • optional persistent-homology enrichment when ripser is available
  • finite-difference rollout traces
  • convergence gates
  • topology state vectors
  • sparse specialist ranking
  • JSON/CSV report writers
• cookbooks/cosmos3/generator/action/topological_modeling.md
  • reviewer-facing modeling note for FD/FDTD, topology metrics, topological inference, and swarm robotics extension
• cookbooks/cosmos3/generator/action/README.md
  • cookbook entry point and minimal mask-first usage snippet
• tests/cookbooks/cosmos3/generator/action/test_topology_helpers.py
  • 16 CPU-only synthetic-mask tests

Verification

python -m py_compile cookbooks/cosmos3/generator/action/topology_helpers.py
python -m unittest tests.cookbooks.cosmos3.generator.action.test_topology_helpers -v
git diff --check

All passed locally.

Maintainer context

Opened proposal issue before implementation: #222

Non-goals

• No change to default Cosmos3 generation behavior.
• No required segmentation model dependency.
• No GPU or model-weight requirement for tests.
• No claim of improved generation quality without a controlled validation protocol.
• No vendored external research prototype code.

[fwd4]

heads up for reviewers: NVIDIA/NeMo-Relay#282

[mli0603]

Interesting feature. @teerthsharma is the idea that if FD retains the same connected components, the prediction is good? And this is used as a proxy for FD eval?