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→Integrated data analysis
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== Integrated data analysis == | == Integrated data analysis == | ||
Often, various different diagnostics provide information on the same physical parameter (e.g., in a typical fusion plasma experiment, the electron temperature ''T<sub>e</sub>'' is possibly measured by Thomson Scattering, ECE | Often, various different diagnostics provide information on the same physical parameter (e.g., in a typical fusion plasma experiment, the electron temperature ''T<sub>e</sub>'' is possibly measured by Thomson Scattering, ECE, and indirectly also by SXR, although mixed with information on the electron density ''n<sub>e</sub>'' and ''Z<sub>eff</sub>''. The electron density is measured directly by Thomson Scattering, the HIBP, reflectometry, and interferometry, and indirectly by SXR). | ||
Part of this information is local, and part is line-integrated. Instead of cross-checking these diagnostics for one or a few discharges, one could decide to make an integrated analysis of data. | Part of this information is local, and part is line-integrated. Instead of cross-checking these diagnostics for one or a few discharges, one could decide to make an integrated analysis of data. | ||
This means using all information available to make the best possible reconstruction of, e.g., the electron density and temperature that is compatible with all diagnostics simultaneously. | This means using all information available to make the best possible reconstruction of, e.g., the electron density and temperature that is compatible with all diagnostics simultaneously. | ||
To do this, the following conditions must apply: 1) The data should not contradict each other mutually. This requires a previous study concerning the mutual compatibility, i.e. data validation. 2) The data should be available with proper calibration and independent error estimates in a routine fashion. This means regular calibrations of the measuring device and crosschecks. 3) A suitably detailed model of the physical system should be available, capable of modelling all experimental conditions and all corresponding measurement data. Techniques based on e.g. [[Bayesian data analysis|Bayesian statistics]] then allow finding the most probable value of all physical parameters in the model, compatible with all measured signals. | To do this, the following conditions must apply: 1) The data should not contradict each other mutually. This requires a previous study concerning the mutual compatibility, i.e. data validation. 2) The data should be available with proper calibration and independent error estimates in a routine fashion. This means regular calibrations of the measuring device and crosschecks. 3) A suitably detailed model of the physical system should be available, capable of modelling all experimental conditions and all corresponding measurement data. Techniques based on e.g. [[Bayesian data analysis|Bayesian statistics]] then allow finding the most probable value of all physical parameters in the model, compatible with all measured signals. | ||
== Summary == | == Summary == | ||