next up previous contents
Next: Noise vs signal Up: The interferometric point source Previous: From the temperature power   Contents

Signal decorrelation

\ensuremath{J_\ensuremath{\mathrm{ant}}^\ensuremath{\mathrm{sd}}} characterizes the antenna hardware, i.e. it assumes perfect atmospheric conditions or the use of autocorrelations, as in single-dish measurements. In interferometric mode, the phase of the turbulent atmosphere above each antenna of a given baseline has a random part that causes an additional ``attenuation'' of the amplitude of the correlation. A point source of 1Jy flux will appear as a source of \ensuremath{\eta_\ensuremath{\mathrm{atm}}}Jy flux if we only use the \ensuremath{J_\ensuremath{\mathrm{ant}}^\ensuremath{\mathrm{sd}}} factor. This is called atmospheric decorrelation and it depends on the weather during the observations.

However, the last calibration step of interferometric data is to measure a point source of known flux to deduce the actual conversion factor, \ensuremath{J_\ensuremath{\mathrm{ant}}^\ensuremath{\mathrm{int}}}, taking into account the atmospheric decorrelation that happens during the observations. By definition of \ensuremath{\eta_\ensuremath{\mathrm{atm}}}, we yield

\begin{displaymath}
\ensuremath{J_\ensuremath{\mathrm{ant}}^\ensuremath{\mathrm...
...remath{J_\ensuremath{\mathrm{ant}}^\ensuremath{\mathrm{int}}}.
\end{displaymath} (7)

It can be shown that \ensuremath{\eta_\ensuremath{\mathrm{atm}}} is related to the atmospheric rms phase noise ( \ensuremath{\phi_\ensuremath{\mathrm{rms}}}) through
\begin{displaymath}
\ensuremath{\eta_\ensuremath{\mathrm{atm}}}{} = e^{-\frac{\ensuremath{\phi_\ensuremath{\mathrm{rms}}}^2}{2}}.
\end{displaymath} (8)


next up previous contents
Next: Noise vs signal Up: The interferometric point source Previous: From the temperature power   Contents
Gildas manager 2023-06-01