Optical versus Physical Pair Background Contamination Flag Checker

Caller independent parallax/motion/background-density observations vs declared optical/physical pair evidence criteria; no physical association established by angular proximity. Independently declared positive evidence requirements; overlaps and unknowns retained. Caller independently establishes frames, units, epoch, covariance and instrument context; not an identity, association or astrometric quality certification.

Description

A close apparent pair can have contamination evidence without an established physical association.

A close apparent pair can have contamination evidence without an established physical association.^[1]

A rule-based evidence comparison preserves unknown features rather than diagnosing the pair. Use Optical versus Physical Pair Background Contamination Flag Checker to evaluate the supplied inputs under the model explained below.

When to use Optical versus Physical Pair Background Contamination Flag Checker

Use Optical versus Physical Pair Background Contamination Flag Checker to evaluate the supplied inputs under the model explained below. Define the candidate classes and their positive-evidence requirements, then distinguish evidence presence from whether it is known.

How to use Optical versus Physical Pair Background Contamination Flag Checker and understand its results

Define the candidate classes and their positive-evidence requirements, then distinguish evidence presence from whether it is known.
Enter Caller pair contamination class ids, Caller pair contamination requirements, Observed pair contamination evidence, Known pair contamination flags using the field table and validation rules below, then run the tool.
Read Compatible caller classes, Fully witnessed caller classes; interpret the units, signs, ordering and unknown-value placeholders described below.
Correct reported input errors and rerun. Apply successful results according to their specific meanings and check the assumptions before using them in a decision.

Input field	Meaning	Value type	Requirement
callerPairContaminationClassIds	Caller pair contamination class ids	array of string	Required; constraints below
callerPairContaminationRequirements	Caller pair contamination requirements	array of array	Required; constraints below
observedPairContaminationEvidence	Observed pair contamination evidence	array of number	Required; constraints below
knownPairContaminationFlags	Known pair contamination flags	array of number	Required; constraints below

Supply unique nonblank class IDs, one rectangular binary requirement row per class, and aligned binary observation and known-flag arrays. Each class must require at least one positive witness. Requirement 0 ignores an evidence column; requirement 1 needs a known positive observation for full witnessing. An unknown requirement remains compatible, while a known absent requirement excludes the class. Both returned class lists preserve caller order. No readiness rubric is installed and compatible does not mean fully witnessed or approved.

compatible = no required known absence; fully witnessed = every required witness known and positive

Use the field order, units and branch conditions described above.

Output field	Meaning	Value type
compatibleCallerClasses	Caller classes with no known absence of required positive evidence.	array of string
fullyWitnessedCallerClasses	Caller classes with all required positive evidence known and present.	array of string

json

{
  "input": {
    "callerPairContaminationClassIds": [
      "a",
      "b"
    ],
    "callerPairContaminationRequirements": [
      [
        1,
        0
      ],
      [
        0,
        1
      ]
    ],
    "observedPairContaminationEvidence": [
      1,
      0
    ],
    "knownPairContaminationFlags": [
      1,
      0
    ]
  },
  "output": {
    "compatibleCallerClasses": [
      "a",
      "b"
    ],
    "fullyWitnessedCallerClasses": [
      "a"
    ]
  }
}

Limitations and assumptions

A rule-based evidence comparison preserves unknown features rather than diagnosing the pair. Apply the exact scope and assumptions explained above.

All listed fields require explicit values. Unexpected fields, incorrect types, nonfinite numbers and sparse arrays fail validation. Domain-specific bounds, alignments and supported tokens are explained above; extremely large inputs or outputs can also be rejected. Input errors differ from successful false results, empty match lists and unknown-evidence placeholders.

Alternative or Complementary methods

Use Speckle Interferometry Diffraction Limit lambda/D Resolution Check for a related task: The Rayleigh relation describes ideal circular-aperture angular resolution.

Use Excess Noise Astrometric Parameter Significance Classifier for a related task: Excess-noise significance summarizes one catalog diagnostic.

References

Optical versus Physical Pair Background Contamination Flag Checker — tool.io

Similar or alternative tools

Speckle Interferometry Diffraction Limit lambda/D Resolution Check
The Rayleigh relation describes ideal circular-aperture angular resolution.
Excess Noise Astrometric Parameter Significance Classifier
Excess-noise significance summarizes one catalog diagnostic.