Parallax Zero Point Correction

Subtract caller-provided source-specific astrometric parallax zero points, preserving nonpositive results rather than inverting them to distances.

Description

An astrometric parallax zero point is a supplied additive bias.

An astrometric parallax zero point is a supplied additive bias. Correcting it can produce zero or negative parallaxes, which should remain visible rather than being automatically converted to distances.1

Subtract caller-provided source-specific astrometric parallax zero points, preserving nonpositive results rather than inverting them to distances.

When to use Parallax Zero Point Correction

Use this tool to subtract caller-provided source-specific astrometric parallax zero points, preserving nonpositive results rather than inverting them to distances.

Prepare the source, detector or coordinate measurements. Confirm frame, epoch, angular units, axis directions and the stated RA proper-motion convention before entering values.

How to use Parallax Zero Point Correction and understand its results

  1. Prepare the source, detector or coordinate measurements. Confirm frame, epoch, angular units, axis directions and the stated RA proper-motion convention before entering values.
  2. Enter measuredParallaxesMas, zeroPointsMas using the field table and calculation rules, then run the tool.
  3. Read correctedParallaxesMas, nonpositiveIndexes. The explanation below defines the units, signs, ordering and any flags or placeholder values.
  4. If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.
Input fieldMeaningValue type; see rules belowRequirement
measuredParallaxesMasMeasured parallaxes maslist of numberRequired
zeroPointsMasZero points maslist of numberRequired

Enter aligned nonempty finite measured parallaxes and source-specific zero points in mas. The tool subtracts each matched bias and returns corrected values plus zero-based positions whose corrected parallax is at most zero. Negative measured or bias values are accepted.

Paired lists must be nonempty and have equal lengths.

correctedParallax_i=measuredParallax_i−zeroPoint_i

Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.

Output fieldMeaningValue type
correctedParallaxesMasCorrected parallaxes maslist of number
nonpositiveIndexesNonpositive indexeslist of number
json
{
  "input": {
    "measuredParallaxesMas": [
      1,
      0
    ],
    "zeroPointsMas": [
      -0.1,
      0.1
    ]
  },
  "output": {
    "correctedParallaxesMas": [
      1.1,
      -0.1
    ],
    "nonpositiveIndexes": [
      1
    ]
  }
}

Limitations and assumptions

It does not provide a catalog bias model, propagate uncertainties or infer distances. Corrected nonpositive observations can still be meaningful measurements; reciprocal-distance estimation requires separate assumptions.

Numeric inputs must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Lists are limited to 100,000 entries; the rules above may require smaller limits. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.

Alternative or Complementary methods

Use Positive Parallax Distance Uncertainty: Compare first-order distance uncertainty with the asymmetric inversion of a supplied ±1-error positive-parallax interval; neither is a posterior credible interval. For a complementary task, use Ruwe From Fit Normalization: Derive RUWE from chi-square, fit degrees of freedom, and caller-supplied magnitude/color normalization; no catalog calibration table is embedded.

References

  1. Parallax Zero Point Correction — tool.io

Similar or alternative tools

  • Positive Parallax Distance Uncertainty

    Compare first-order distance uncertainty with the asymmetric inversion of a supplied ±1-error positive-parallax interval; neither is a posterior credible interval.

  • Ruwe From Fit Normalization

    Derive RUWE from chi-square, fit degrees of freedom, and caller-supplied magnitude/color normalization; no catalog calibration table is embedded.

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