PhysicsLogic / Hubble 1929

Hubble's Distance Calibration

Inspect what a radial fit determines, what a distance anchor adds, and what the source leaves open.

Definitions and assumptions

Scope and physical limitations

The absolute-scale route fixes the solar solution, sample, and weights. The joint-fit extension instead keeps distances fixed while varying the solar solution and coefficient. Actual angular geometry distinguishes sufficient pairwise comparisons from a projection-correlated sample that retains ambiguity. Bounded peculiar residuals give a coefficient interval, not an exact empirical value. A further evidence diagnostic distinguishes agreement on obtained records from every possible test: the same radial data support two positive scales, an accessible but unobtained absolute-distance result does not yet discriminate them, and obtaining that result removes this particular ambiguity. The support and access relations stay fixed; only the obtained record set changes. Support here means compatibility within the stated residual tolerance or exact distance equality, not likelihood, confirmation strength, truth or posterior probability. The readout ranges, tolerance three, candidate scales one and two, and exact anchor value one are independent synthetic choices. These are diagnostics of the source equation, not a refit of the historical catalog, a Cepheid calibration, reconstruction of a least-squares procedure, or proof of cosmic expansion. None of the synthetic two- or three-object samples is Hubble's catalog.

Other arguments
Examples and distinctions

Constructed examples of this model; each answer includes the Lean statement.

Exact root statement

∀ {Object : Type u} (data : Data Object) (sample : Finset Object) (tolerance scale : ℝ),
  data.PhysicalFitOn (↑sample) tolerance →
    0 < scale →
      scale ≠ 1 →
        (data.rescaleDistance scale).PhysicalFitOn (↑sample) tolerance ∧
          (∀ (object : Object), (data.rescaleDistance scale).radialReadout object = data.radialReadout object) ∧
            (∀ (weight : Object → ℝ),
                (data.rescaleDistance scale).weightedResidualLoss sample weight =
                  data.weightedResidualLoss sample weight) ∧
              (data.rescaleDistance scale).coefficient ≠ data.coefficient
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Notes and questions

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Definitions, structures, and assumptions

Structures, classes, and inductive alternatives

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Definitions and domain choices

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Checked statements: parameters, hypotheses, and interpretation

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Constructors, projections, and other meaning dependencies

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