For a constant-rate radiation measurement through identical absorbing sheets, a simple Poisson distribution model has expected counts . Here is the unattenuated signal rate, is attenuation per sheet, is an additive background rate and is exposure. At low attenuation the signal is approximately exponential; at strong attenuation the observed rate approaches . Consequently a logarithmic plot of raw counts bends towards a plateau rather than remaining a straight line. Measure background independently with the source absent, or fit it with its uncertainty; subtracting it and then taking a logarithm is unreliable when the net count is small or negative.
If a measured unattenuated reference rate includes the same additive background as subsequent measurements, then , where is signal alone. Substituting into an attenuation count model with an additive background gives . This automatically returns the measured reference at and tends to at strong attenuation. Adding directly to would count background twice at zero attenuation. A joint count likelihood can fit the reference and attenuated data with their separate exposure times, avoiding the need to regard the reference estimate as exact.
The time constant in exponential decay is the time over which the decaying quantity is multiplied by . A response approaching equilibrium as has the same time constant. For a resistor-inductor circuit it is .
A stretched exponential has the form with and . A boundary cost proportional to the square root of an enclosed area naturally produces exponent .
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