This article explains how to correctly retrieve data from the NSDD operand for use in the Universal Plot 1D and 2D analysis features.
Authored By Sanjay Gangadhara
The NSDD Merit Function operand allows users to retrieve incoherent intensity data from a detector. Depending on the values specified for the Pix# and Data parameters, a number of results may be obtained, such as the mean flux, the maximum flux/area, or the standard deviation of all non-zero pixel data. The variation of these quantities with different setup conditions may be determined using the Universal Plot 1D and 2D analysis features.
It is important to realize that the NSDD operand cannot be used directly in either the 1D or 2D Universal Plot because this operand requires that the detector be cleared and that a ray trace be performed before any data can be retrieved. These tasks need to be completed each time the setup conditions are altered, i.e. for each step that the independent variables take when they are scanned in the Universal Plot features.
Thus, for the Universal Plot features to use data obtained by NSDD, the data must be extracted from the Merit Function. To sum up, the NSDD operand retrieves information from a ray trace, and so, can’t be use alone. The workaround is to use it with other operands in a Merit Function which take care of clearing the detector and launching a raytrace before the NSDD operand. An example (NSDD_Example.ZMX) illustrating how this is done is provided as an article attachment.
Open the attached file called “NSDD_Example.zmx”.
This simple example contains a Source Ellipse launching rays towards a Detector Rectangle. A Merit Function is constructed in which the detector is cleared using the NSDD operand (with the Det# parameter set to 0), rays are traced using the NSTR operand, and the total power on the detector is retrieved with another NSDD operand. The total power is plotted as a function of the Source Distance parameter for the Source Ellipse using the Universal Plot 1D feature, by specifying the Merit Function as the dependent variable and specifying explicitly which line of the Merit Function to evaluate:
The results show the expected variation:
Similar methods will be necessary for any other operands which do not function independently (e.g. NSDC, etc.), but require the presence of other operands to work correctly.