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ARTS2D: define a true reduced 2-V EDF marginal instead of a renormalized 3-D slice #137

Description

@joglekara

Problem

ARTS2D needs a reduced two-velocity EDF, but the spherical-harmonic path currently constructs 3-D-normalized radial/spherical components, samples them on the vz=0 plane, clips the result, and renormalizes that slice in 2-D (tsadar/core/modules/distribution_functions/spherical_harmonics.py:263-312).

A central slice is not the same as the marginal over the unobserved velocity component except for special distributions. Post-hoc 2-D normalization hides the dimensional mismatch while changing moments and introducing an artificial degeneracy between EDF shape and Te.

Directly measured normalized 2-V second moments from the current reconstruction are approximately:

  • super-Gaussian m=2: 2.01;
  • m=3: 2.19;
  • m=5: 2.35.

The intended normalized 2-V thermal second moment should remain 2 across shape parameterizations if Te keeps the documented meaning. The 1-D DLM construction maintains its corresponding variance across these values.

Decision required

Choose and document one model:

  1. ARTS2D directly parameterizes a physical reduced 2-V EDF on the velocity plane; or
  2. it parameterizes a 3-D EDF and analytically/numerically marginalizes the unobserved component before the Radon projection.

Do not silently substitute a central slice for a marginal.

Acceptance criteria

  • State the EDF dimensional convention, units, normalization, and relation between Te and velocity moments in code/docs/config schema.
  • Add an analytic Maxwellian 3-D-to-2-D marginal test.
  • Add high-accuracy numerical marginal tests for m != 2 and representative anisotropic modes.
  • Density, first moments, and thermal second moments obey the chosen normalization without post-hoc shape-dependent temperature drift.
  • Every 1-D projected EDF used by the susceptibility agrees with direct integration of the declared underlying distribution to a documented tolerance.
  • Positivity is imposed by construction or a smooth parameterization rather than a hard gradient-killing clip.

Related: #124 and the separate spherical-harmonic trainability issue.

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