Parametric Trailing Loss
Evaluate an explicitly supplied quadratic trailing-loss model coefficient; this is a matched-filter SNR approximation, not an aperture-flux correction.
Description
A source trail spreads signal relative to a point-like seeing profile.
A source trail spreads signal relative to a point-like seeing profile. This supplied quadratic model estimates matched-filter signal-to-noise loss rather than how much flux a chosen aperture recovers.1
Evaluate an explicitly supplied quadratic trailing-loss model coefficient; this is a matched-filter SNR approximation, not an aperture-flux correction.
When to use Parametric Trailing Loss
Use this tool to evaluate an explicitly supplied quadratic trailing-loss model coefficient; this is a matched-filter SNR approximation, not an aperture-flux correction.
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 Parametric Trailing Loss and understand its results
- Prepare the source, detector or coordinate measurements. Confirm frame, epoch, angular units, axis directions and the stated RA proper-motion convention before entering values.
- Enter trailArcseconds, seeingFwhmArcseconds, lossCoefficient using the field table and calculation rules, then run the tool.
- Read magnitudeLoss, relativeSignalToNoise. The explanation below defines the units, signs, ordering and any flags or placeholder values.
- 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 field | Meaning | Value type; see rules below | Requirement |
|---|---|---|---|
| trailArcseconds | Trail arcseconds | number | Required |
| seeingFwhmArcseconds | Seeing fwhm arcseconds | number | Required |
| lossCoefficient | Loss coefficient | number | Required |
Enter nonnegative trail length in arcseconds, positive seeing FWHM in arcseconds and nonnegative loss coefficient. Return magnitude penalty and relative signal-to-noise. Zero trail or coefficient produces zero magnitude loss and relative SNR one.
factor=1+coefficient(trail/FWHM)²; magnitudeLoss=1.25log10(factor); relativeSNR=1/sqrt(factor) Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| magnitudeLoss | Magnitude loss | number |
| relativeSignalToNoise | Relative signal to noise | number |
{
"input": {
"trailArcseconds": 1,
"seeingFwhmArcseconds": 1,
"lossCoefficient": 0.42
},
"output": {
"magnitudeLoss": 0.1903604304788206,
"relativeSignalToNoise": 0.8391813582966892
}
}Limitations and assumptions
The coefficient is a model choice, not fitted here. Aperture corrections, pixel sampling, background estimation and the actual matched filter are not calculated.
Numeric inputs must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.
Alternative or Complementary methods
Use Moving Source Trail Pixels: Project tangent-plane motion onto a detector trail length and position angle for a supplied exposure and pixel scale. For a complementary task, use Anisotropic Psf Sampling: Screen measured PSF FWHM sampling independently along both pixel axes using a supplied minimum; the two-pixel heuristic is not an exact Gaussian bandlimit.
References
-
Parametric Trailing Loss — tool.io
Similar or alternative tools
- Moving Source Trail Pixels
Project tangent-plane motion onto a detector trail length and position angle for a supplied exposure and pixel scale.
- Anisotropic Psf Sampling
Screen measured PSF FWHM sampling independently along both pixel axes using a supplied minimum; the two-pixel heuristic is not an exact Gaussian bandlimit.