[CharlelieLrt]

Description

This PR adds TrigFlowNoiseScheduler and TrigFlowPreconditioner to
physicsnemo.diffusion. Users can pair them with the same sigma_data value to train
a backbone that predicts normalized velocity while exposing clean-data
predictions through the usual diffusion model interface.

Built-in linear Gaussian schedules also gain snr_inv(q), which converts the
amplitude ratio q = alpha / sigma back to diffusion time.
Custom schedules can supply their own inverse. This gives the private FastGen
adapters a way to translate noise levels between schedules without relying on
inference grids.

Checklist

• This PR follows the contribution guidelines.
• The documentation describes the API and its role in the stack.
• This PR remains a draft.

Dependencies

• Depends on

  • PhysicsNeMo #2199 adds named diffusion inputs and outputs. This is the immediate prerequisite.

• Depends on this PR

  • PhysicsNeMo #2201 adds private adapters and public sCM and MeanFlow losses. It follows this PR directly in the stack.

• Later follow-ups

  • PhysicsNeMo #2202 extends the loss API to DMD2 and f-distill.
  • PhysicsNeMo #2203 adds checkpoint bundles for restarting distillation.
  • PhysicsNeMo #2204 adds the optional training strategy and the grouped changelog entry.

• Parallel FastGen work

  • FastGen #43 allows the NumPy 2 dependency used by PhysicsNeMo. PhysicsNeMo Add sCM and MeanFlow distillation losses #2201 uses an immutable fork pin, so it does not need to wait for this proposal to merge.
  • FastGen #44 provides shared loss hooks for external training loops. The initial PhysicsNeMo integration does not require these hooks.

• Conditional follow-up

  • PhysicsNeMo #2205 replaces local compatibility code with the proposed FastGen loss hooks. It depends on PhysicsNeMo Add optional diffusion distillation strategy #2204 and FastGen [other] Add modulus.models.fcn_mip_plugin #44, not the other way around.

If FastGen maintainers decline FastGen #44, we would close PhysicsNeMo #2205.
The preceding PhysicsNeMo stack would remain available.

Review process

This draft replaces PhysicsNeMo #2095 and comes from the personal fork. This migration preserves the implementation. The first commit also includes the requested documentation clarifications.

Review the isolated commit diff for this layer. Each branch adds one commit to its prerequisite branch. All replacement PRs target upstream main, so later PRs include prerequisite commits awaiting merge in their Files changed tab. After prerequisites merge, update the remaining branches to remove them from those diffs.

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[github-actions]

CODEOWNERS review map

Current for commit 93133b1e9659. An approval covers every file listed for that owner; one owner is sufficient for shared files.

⏳ @CharlelieLrt — 31 file(s)

• docs/api/diffusion/introduction.rst
• docs/api/diffusion/models.rst
• docs/api/diffusion/noise_schedulers.rst
• docs/api/diffusion/preconditioners.rst
• physicsnemo/diffusion/init.py
• physicsnemo/diffusion/base.py
• physicsnemo/diffusion/metrics/losses.py
• physicsnemo/diffusion/noise_schedulers/init.py
• physicsnemo/diffusion/noise_schedulers/edm.py
• physicsnemo/diffusion/noise_schedulers/iddpm.py
• physicsnemo/diffusion/noise_schedulers/linear_gaussian.py
• physicsnemo/diffusion/noise_schedulers/rectified_flow.py
• physicsnemo/diffusion/noise_schedulers/trigflow.py
• physicsnemo/diffusion/noise_schedulers/ve.py
• physicsnemo/diffusion/noise_schedulers/vp.py
• physicsnemo/diffusion/preconditioners/init.py
• physicsnemo/diffusion/preconditioners/preconditioners.py
• physicsnemo/diffusion/utils/model_wrappers.py
• test/diffusion/data/trigflow_precond_conv.mdlus
• test/diffusion/data/trigflow_precond_conv_coefficients.pth
• test/diffusion/data/trigflow_precond_conv_forward.pth
• test/diffusion/data/trigflow_precond_conv_sigma.pth
• test/diffusion/data/trigflow_precond_linear.mdlus
• test/diffusion/data/trigflow_precond_linear_coefficients.pth
• test/diffusion/data/trigflow_precond_linear_forward.pth
• test/diffusion/data/trigflow_precond_linear_sigma.pth
• test/diffusion/helpers.py
• test/diffusion/test_model_io.py
• test/diffusion/test_noise_schedulers.py
• test/diffusion/test_preconditioners.py
• test/diffusion/test_trigflow.py

⏳ @megnvidia — 4 file(s)

• docs/api/diffusion/introduction.rst
• docs/api/diffusion/models.rst
• docs/api/diffusion/noise_schedulers.rst
• docs/api/diffusion/preconditioners.rst

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• CHANGELOG.md

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