TY - JOUR
T1 - The goodness of simultaneous fits in ISIS
AU - Kühnel, Matthias
AU - Falkner, Sebastian
AU - Grossberger, Christoph
AU - Ballhausen, Ralf
AU - Dauser, Thomas
AU - Schwarm, Fritz Walter
AU - Kreykenbohm, Ingo
AU - Nowak, Michael A.
AU - Pottschmidt, Katja
AU - Ferrigno, Carlo
AU - Rothschild, Richard E.
AU - Martínez-Núñez, Silvia
AU - Torrejón, José Miguel
AU - Fürst, Felix
AU - Klochkov, Dmitry
AU - Staubert, Rüdiger
AU - Kretschmar, Peter
AU - Wilms, Jörn
N1 - Publisher Copyright:
© Czech Technical University in Prague, 2016.
PY - 2016
Y1 - 2016
N2 - In a previous work, we introduced a tool for analyzing multiple datasets simultaneously, which has been implemented into ISIS. This tool was used to fit many spectra of X-ray binaries. However, the large number of degrees of freedom and individual datasets raise an issue about a good measure for a simultaneous fit quality. We present three ways to check the goodness of these fits: we investigate the goodness of each fit in all datasets, we define a combined goodness exploiting the logical structure of a simultaneous fit, and we stack the fit residuals of all datasets to detect weak features. These tools are applied to all RXTE-spectra from GRO 1008−57, revealing calibration features that are not detected significantly in any single spectrum. Stacking the residuals from the best-fit model for the Vela X-1 and XTE J1859+083 data evidences fluorescent emission lines that would have gone undetected otherwise.
AB - In a previous work, we introduced a tool for analyzing multiple datasets simultaneously, which has been implemented into ISIS. This tool was used to fit many spectra of X-ray binaries. However, the large number of degrees of freedom and individual datasets raise an issue about a good measure for a simultaneous fit quality. We present three ways to check the goodness of these fits: we investigate the goodness of each fit in all datasets, we define a combined goodness exploiting the logical structure of a simultaneous fit, and we stack the fit residuals of all datasets to detect weak features. These tools are applied to all RXTE-spectra from GRO 1008−57, revealing calibration features that are not detected significantly in any single spectrum. Stacking the residuals from the best-fit model for the Vela X-1 and XTE J1859+083 data evidences fluorescent emission lines that would have gone undetected otherwise.
KW - Data analysis
KW - Multiple datasets
KW - X-rays binaries
UR - https://www.scopus.com/pages/publications/84959313293
U2 - 10.14311/APP.2016.56.0041
DO - 10.14311/APP.2016.56.0041
M3 - Article
AN - SCOPUS:84959313293
SN - 1210-2709
VL - 56
SP - 41
EP - 46
JO - Acta Polytechnica
JF - Acta Polytechnica
IS - 1
ER -