Coverage excess from central quantiles at a zero-duration atom is the additional distributional probability included when a closed quantile interval captures an entire point mass at zero. Here coverage means probability under the stated duration model. For with , the zero mass is and the positive part is continuous. Let , , and use the lower quantiles from quantiles of a clipped Gaussian acquisition duration.
For the closed central interval , its probability is
To verify this, write the probability as . When both endpoints are positive, the lower left limit is and the upper value is . Once the lower endpoint is zero, its left limit is zero; if the upper endpoint is zero too, the interval contains exactly the zero atom. Endpoint inclusion is therefore part of the probability calculation.
For a nominal 95 percent central construction, zero masses , and give actual probabilities , and respectively. In the middle case, the excess is , not the whole atom: the interval already includes the probability between zero and the upper quantile.
As an original dimensional example, set , and , giving . The nominal central 95 percent interval is approximately and contains probability . SciPy documents the normal cdf and inverse-cdf ppf used to evaluate these Gaussian-component values.[ref]
A one-sided upper interval or a separately specified probability construction can target a different included probability. Randomized endpoint inclusion at a zero-duration atom would require an explicit randomization rule, not a change made silently after seeing an endpoint equal zero. NIST explains why interval interpretation requires the input distributions and the chosen construction.[ref] Distributional probability for this conditional acquisition model is separate from a worst-case optical-energy guarantee or a confidence procedure for an unknown fixed parameter.
Gaussian input uncertainty at a clipped acquisition-time threshold produces a mixed output distribution rather than an ordinary Gaussian error bar. Hold the decay time fixed and assume the logarithmic input ratio has distribution , with . The required extension is
The directional derivative of a clipped logarithmic acquisition time explains the kink; here the full input distribution is propagated through it.
Writing and for the standard normal cumulative distribution function and density, respectively,
For the continuous part has density . It integrates to less than one because the remaining probability is an atom at zero. Treating this density alone as the entire distribution loses that atom.
At the nominal threshold , half the outcomes are zero and the conditional positive part has a half-normal distribution. Direct integration of the normal density gives
For an original example, and logarithmic standard deviation give mean extension about and standard deviation , although inserting the nominal input into the clipped formula gives zero. The probability of an extension above is .
The quantiles of a clipped Gaussian acquisition duration must likewise include the zero atom. A symmetric interval around the nominal zero duration cannot represent these probabilities. NIST's uncertainty discussion stresses the need to know and combine input distributions when assigning an interval probability.[ref]
This is a stated uncertainty model for a conditional recording requirement, not a worst-case optical-energy guarantee. Uncertain decay time, correlation among the original envelope parameters or a non-Gaussian logarithmic ratio requires the corresponding joint propagation instead. Establishing the optical envelope remains a separate experimental task.