SSM-JTK – Results to Date — Benchmark cross-checks (observation-only; optional) (3.7)

Purpose
A simple, repeatable way for readers to audit results using a reputable public ephemeris. This uses your local CSVs or ephemeris outputs plus the deterministic metrics below. It does not change the evaluator in any way.

Metrics (ASCII)

  • Phase error on [0,30)
    Let d = ((L_true % 30) - (L_pred % 30) + 15) % 30 - 15.
    phase_err_deg = |d|
    Aggregates: phase_MAE_deg = mean(phase_err_deg), phase_P95_deg = P95(phase_err_deg).
  • Rāśi crossing timing (days; positive = late)
    rasi_cross_err_days = (t_cross_pred - t_cross_true)
    Aggregate: rasi_cross_MAE_days = mean(|rasi_cross_err_days|) after nearest-neighbor pairing within ±60 d.
  • Station date timing (days)
    station_date_MAE_days = mean(|t_station_pred - t_station_true|) after nearest-neighbor pairing within ±90 d.

Procedure (repeatable)

  1. Fix a span (e.g., 2000-01-01..2099-12-31) at one daily timestamp (e.g., 05:30 IST or 00:00 UTC).
  2. Compute model L_pred_deg using the one-line evaluator from a manifest (same timestamp).
  3. Obtain reference L_true_deg from a reputable public ephemeris using the same frame/time: geocentric, sidereal Lahiri, same daily timestamp.
  4. Compute metrics above per body and compare with the acceptance bands in §3.4.

Notes & tips

  • Use one-wrap display for comparison: wrap360(x) = x - 360*floor(x/360).
  • Always work on unwrapped tracks when interpolating events; wrap only for daily angle display.
  • Document the exact span, timestamp, and pairing caps used in your report.
  • When events are sparse (e.g., Uranus in short windows), expect NaN for crossing timing; rely on cusp/station metrics.

Lightweight reporting template

Span=YYYY-MM-DD..YYYY-MM-DD  Timestamp=<e.g., 05:30 IST>  Frame=Lahiri (geocentric)
Body  phase_MAE  phase_P95  rasi_cross_MAE_d  station_MAE_d
----  ---------  ---------  ----------------  -------------
...

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