LF4 plan B (step 1): the moment marginal as a Haar marginal #
Category: 3-Local (the moment marginal as a Haar marginal).
Plan B is to discharge the hypothesis h_uniform of fs_born_volume_ratio_qubit
and qubit_born_frequency_convergence, i.e. to prove
(fun p => momentMap p 0)∗ fubiniStudyMeasure p₀ = uniform on [0,1].
Everything is finite-dimensional (CPN N = ℂℙ^{N-1}, U(N)); plan B is purely a
finite-dimensional measure computation — it does not touch CSD's finiteness.
This file lands the first, committable half: the measure-level reduction.
Since fubiniStudyMeasure p₀ = (orbitMap p₀)∗ unitaryHaarProb and
momentMap (U • p₀) i = ‖(U·rep)ᵢ‖²/‖U·rep‖² (momentMap_orbit), the moment
marginal is the Haar law of the squared-modulus ratio of U acting on a
representative:
(momentMap · i)∗ fubiniStudyMeasure p₀
= (fun U => ‖(U·rep)ᵢ‖²/‖U·rep‖²)∗ unitaryHaarProb.
So h_uniform (for i = 0, N = 2) reduces exactly to: the Haar law of
U ↦ ‖(U·rep)₀‖²/‖U·rep‖² on U(2) is Uniform[0,1]. With a unit
representative ‖U·rep‖ = ‖rep‖, this is "|U₀₀|² (the first squared-modulus of a
Haar-random unit column) is Uniform[0,1]" — the Beta(1,1) / Archimedes fact.
Remaining (the hard core). Proving that Haar marginal is uniform is the
genuine analytic content with no current Mathlib support: it routes through
either (Haar-orbit → uniform S³) + (uniform S³ → Uniform[0,1]), or the
complex-Gaussian route (normalised Gaussian → uniform sphere; |z₀|²/‖z‖² ~ Beta(1,1)). Tools: MeasureTheory.Constructions.HaarToSphere,
Probability.Distributions.Beta/Gaussian. This is a multi-session build; see
specs/carve-out-plan.md Tranche M, plan B.
Plan B, step 1 (the reduction). The moment-coordinate marginal of the
Fubini–Study measure equals the Haar law of the squared-modulus ratio of U
acting on a representative of p₀. Reduces h_uniform to a concrete
distributional statement about Haar unitaries.