Using integrated data analysis to extend measurement capability (invited)

Abstract

The analysis approach called integrated data analysis (IDA) provides a means to exploit all information present in multiple streams of raw data to produce the best inference of a plasma parameter. This contrasts with the typical approach in which information (data) from a single diagnostic is used to measure a given parameter, e.g., visible bremsstrahlung → Z eff. Data from a given diagnostic usually contain information on many parameters. For example, a Thomson scattering diagnostic is sensitive to bremsstrahlung and line emission in addition to electron temperature. This background light is typically subtracted off and discarded but could be used to improve knowledge of Z eff. IDA encourages explicit awareness of such information and provides the quantitative framework to exploit it. This gives IDA the ability to increase spatial and temporal resolution, increase precision and accuracy of inferences, and measure plasma parameters that are difficult or impossible to measure using single diagnostic techniques. One example is the measurement of Z eff on Madison symmetric torus using IDA since no single diagnostic can provide a robust measurement. As we enter the burning plasma era, application of IDA will be critical to the measurement of certain parameters, as diagnostic access in the harsh fusion environment will be extremely limited.

A versatile multi-energy soft x-ray diagnostic for Te measurements in the Madison Symmetric Torus

“…This forward model can be used not only to predict what measured data might look like given some supposed profiles, but also to quantify how likely a hypothetical T e profile is to have generated some given real data. This technique is based on the application of Bayes Rule, equation (5.3), which relates the probability that the model parameters {T e,0 , α} describe the data d (called the posterior, p(T e,0 , α|d, I)) to the probability of measuring the data given the model parameters [12,13]. Also important is the prior, p(T e,0 , α|I), which quantifies one's knowledge to the problem prior to any measurements.…”

Impact of human disturbance on the biogeochemical silicon cycle in a coastal sea revealed by silicon isotopes

“…Further changes in the Si cycle related to anthropogenic perturbations are expected to increase in coastal systems (Laruelle et al 2009) and thus detailed investigations of Si dynamics will allow for exploring ways of mitigation in such coastal areas. Determining the impacts of human pressures on Si cycling, especially in high-latitude systems where effects of global warming are amplified, is major challenge to the management of this anthropogenically impacted ecosystem (Reusch et al 2018).…”

“…The Baltic Sea is a semi-enclosed coastal sea, which is prone to anthropogenic perturbations and can serve as a representative of systems disturbed by a variety of multistressors (Reusch et al 2018). A significant decline in DSi concentration was observed throughout the Baltic Sea between 1970and 1990(e.g., Papush and Danielsson 2006, due to silicon retention in river basins and autochthonous diatom production in the Baltic Sea (Conley et al 2008).…”