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Antonino Ingargiola edited background-estimation.tex
about 8 years ago
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Figure~\ref{fig:bg_dist_all} allows to quickly identify pathological cases when the
background fitting procedure returns unreasonable values.
The second background-related plot is
the a timetrace of
the estimated background rates,
as shown in figure~\ref{fig:bg_timetrace}. This plot allows to monitor background changes
taking place during the
measurement. This plot measurement and is obtained with the
commans: command:
\begin{lstlisting}
dplot(d, timetrace_bg)
\end{lstlisting}
Coverglass Normally, samples should have a constant background as a function of time
like in figure~\ref{fig:bg_timetrace}(a). However, oftentimes, non-ideal
experimental conditions can yield a time-varying background, as shown in
figure~\ref{fig:bg_timetrace}(b).
For example, when the sample is not sealed in an observation chamber,
evaporation can induce background variations (typically increasing)
as a function of time. Additionally,
cover-glass impurities can contribute to the background even when focusing
deep into the sample (10μm or
more), more).
These impurities tend to bleach on timescales of minutes resulting in
background variations during the course of the
measurement, such as
the one shown in figure~\ref{fig:bg_timetrace}a.
Additionally, when the sample in not sealed in an observation chamber,
evaporation can contribute to background variations, similar to the
one shown in figure~\ref{fig:bg_timetrace}b. measurement.
\paragraph{Python details} For an ALEX measurement, the tuple passed to
\verb|tail_min_us| to define the thresholds, is required to have have