= Reset pedestal variance
{title2=$\sigma_v^2=\sigma_Q^2/C^2$}
\b[Reset pedestal variance] is the acquisition-to-acquisition <variance> of the output offset associated with <integrator reset>. In a model where the only fluctuating contribution is an opening charge $Q$ on fixed <capacitance> $C$,
$$
P=Q/C,\qquad \operatorname{Var}(P)=\operatorname{Var}(Q)/C^2.
$$
Subtracting the mean of the <reset charge-injection pedestal> removes its constant component, not the random spread. The physical datasheet distinguishes charge-transfer offset from output noise; its charge-transfer limit alone is not a statistical variance specification.<ACF2101 Low Noise, Dual Switched Integrator datasheet>[p3, Output Noise and Charge Transfer Errors; p11, Charge Transfer]{ref}
Finite blank measurements introduce another contribution. Suppose independent pedestals have mean $\mu$ and <standard deviation> $\sigma_P$. Use $M$ independent zero-input acquisitions to estimate $\mu$, then subtract that same blank <sample mean> from each of $N$ new signal acquisitions. With a constant signal and no other noise, the corrected mean has
$$
\operatorname{Var}(\overline Y-\overline P_{\rm blank})
=\frac{\sigma_P^2}{N}+\frac{\sigma_P^2}{M}.
$$
This <variance of a pedestal-corrected sample> includes the uncertainty of the shared correction. Its second contribution does not shrink when more signal acquisitions reuse the same blank estimate. Covariance-based <uncertainty propagation> retains such shared terms.<Guide to the expression of uncertainty in measurement by JCGM>[§4.2.3, variance of an arithmetic mean; §5.2.2, correlated inputs]{ref}
For original stipulated $\sigma_P=0.20\,\mathrm{mV}$, $N=100$ and $M=25$, the corrected mean has <standard deviation> $0.0447\,\mathrm{mV}$. An exactly known pedestal mean would give $0.0200\,\mathrm{mV}$. Repeated zero-input acquisitions at a fixed delay after switching measure the combined pedestal/readout spread; separating its mechanisms requires additional tests. Slow drift or correlations between acquisitions invalidate the independent-sample formula and must enter the <measurement model>.
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