A γ-ray background model for Monte Carlo simulations

Field Response Prediction: Framing the problem.

“…The most common approach for background estimation in field detection operations is to use previously measured background data. There is also extensive work on modelling the backgrounds most commonly found in field applications ( [20], [25], [26], [27]) to be used in detector and algorithm testing as possible substitution to intensive background measurement campaigns. Although such models could be complex, they might be still unable to capture in situ spectral changes (e.g., nearby building materials, temperature changes, etc.)…”

“…High purity germanium detectors ( [21], [25], [28], [29]) are the gold standard for gamma-ray spectroscopy, with resolutions of typically 1.3 keV (0.2%) full width half maximum at 662 keV. This allows precise determination of peak energies, separation of peaks and detection of relatively weak peaks in the presence of a strong background; see an example HPGe spectrum in Figure 2.…”

“…As mentioned in [14], the information provided by background measurement campaigns can be the input to modelling efforts attempting to predict the background distribution that a given detector system would observe. In [25], a gamma-ray background model for a typical urban environment is created by simulating the response of a typical coaxial HPGe detector with the Monte Carlo-based Geant4 toolkit [41] and matching it with observed data. Though [25] succeeds in satisfactorily approaching the measured data, their multi-stage process reveals the difficulties to account for all background lines and scatter radiation contributing to the final spectra.…”

“…In [25], a gamma-ray background model for a typical urban environment is created by simulating the response of a typical coaxial HPGe detector with the Monte Carlo-based Geant4 toolkit [41] and matching it with observed data. Though [25] succeeds in satisfactorily approaching the measured data, their multi-stage process reveals the difficulties to account for all background lines and scatter radiation contributing to the final spectra. Another example of background modeling is presented in [20], where the terrestrial background spectrum expected from the three families of isotopes, 40 K, 232 Th and 235 U/ 238 U, measured with a HPGe detector in an open space location at a seaport is modelled using the Monte Caro N-Particle (MCNP) transport code [42].…”

“…Another example of background modeling is presented in [20], where the terrestrial background spectrum expected from the three families of isotopes, 40 K, 232 Th and 235 U/ 238 U, measured with a HPGe detector in an open space location at a seaport is modelled using the Monte Caro N-Particle (MCNP) transport code [42]. In contrast with [25], this work manages to match with good agreement the simulation and measured spectra using simple scaling of each family of isotopes; only at energies below 400 keV the difference is about 30%, which the authors discovered is due to lack of accounting for the skyshine effect. Once the skyshine, cosmic and terrestrial gamma backgrounds are considered, the simulation of a NaI(Tl) detector spectra in [20] achieves an excellent match with data collected in an open field site.…”