Extended Bayesian Estimation for In-flight Calibration of Space-based Instruments

Music City Center 

Instrument calibration is essential for space-based instruments to ensure accurate measurements of physical quantities, such as photon flux from astronomical sources. This process involves in-flight adjustments to address discrepancies arising from instrument-specific variations. To enhance calibration reliability, we propose a Bayesian hierarchical spectral model that leverages domain-specific priors and integrates information across different spectra, instruments, and sources. By analyzing measurements of the same set of objects from multiple instruments, the model estimates posterior uncertainties for calibration parameters and infers about structural parameters with statistical significance. Using a log-normal approximation for photon counts, our approach provides a principled alternative to empirical methods, improving the calibration of new equipment.

bayesian hierarchical model

shrinkage estimator

high energy spectral model 

Section on Bayesian Statistical Science