PREDNASAJUCI / LECTURER :

Julius Koza

NAZOV / TITLE :

Semi-empirical spectral modeling in hindsight

ABSTRAKT / ABSTRACT :

Semi-empirical spectral modeling is a fundamental technique in
diagnostic of astrophysical plasma. In essence, it can be
characterized by the set of (i) observations (data) used to constrain
the model, (ii) physical approximations (formulas) employed, and (iii)
free parameters ("model") to be determined. Data is inevitably limited
in spectral, spatial, and temporal domains, modified by instrumental
characteristics, and burdened by omnipresent noise. Physical
approximations are complete only to the level of making a problem
tractable. An adopted complexity of model is justified by a need to be
computationally affordable. A balance in the three-point system
"data-formulas-model" is quantified by a multi-variate merit
function. Its global minimum represents the sought solution, which is
often identified with physical reality. The presentation aims to show
an application of the technique on solar flare loops, long off-limb
spicule, small-scale chromospheric jet, and quiescent
filament. Although in all these cases a good fit of data, i.e. a
balance in the system "data-formulas-model", was reached, the final
model parameters may be considered as suspicious and even
unrealistic. Only in particular case of cool flare loops the final
model is considered to be adequate and justified because substantially
different data and physical approximations yielded very similar
results. Conclusively, the presentation aims to demonstrate that a
data fit does not imply ultimate physical adequacy and realism of
model parameters but rather a balance in the "data-formulas-model"
system.