Test Beam Simulation for ESA BepiColombo Mission Marcos Bavdaz, Alfonso Mantero, Barbara Mascialino, Petteri Nieminen, Alan Owens, Tone Peacock, Maria Grazia Pia

Mercury Atmosphere generated by solar wind High density (5.3 g/cm 3 ) Magnetic field (~ 330 nT - 1/1000 Earth) Magnetosphere Water presence at the poles (?) Observations from Earth are difficult Impossible observations from Hubble - optics damage Interplanetary Spacecrafts 3 fly-by (Mariner ) Planetary crust composition Formation Planet Solar System

Two orbiters for a variety of scientific experiments: Magnetic field study - Planet mapping - Surface study Named in honour of Giuseppe Colombo The ESA BepiColombo Mission MPO Planetary evolutionary models Solar corona measurements Precision measurements of general relativity Search for Near Earth Objects (NEO) Launch date 2012 MercuryPlanetaryOrbiter MercuryMagnetosphericOrbiter

HERMES experiment Planetary surface composition measurements by means of X-ray spectrography Choice for the most appropriate detector under study, particularly for GaAs. Incident Radiation Fluorescence soil Solar radiation variability + Cosmic Radiation Detector for incident radiation monitoring E BEAM =8.5 keV Energy (keV) Counts

Mission related problems Poor knowledge and no control on the measurement environment No repair possible in space Risk Analysis and Mitigation FUNCTIONAL REQUIREMENTS Fluorescence simulation resulting from atomic deexcitation Reproduction capability for complex materials, like the geological ones Geometry detailed description Detector features reproduction NON FUNCTIONAL REQUIREMENTS Results reliability, by means of PHYSICALVALIDATION PHYSICAL VALIDATION GRID GRID transposition for statistically significant samples production NON FUNCTIONAL REQUIREMENTS Results reliability, by means of PHYSICALVALIDATION PHYSICAL VALIDATION GRID GRID transposition for statistically significant samples production

Monocromatic photon beam HpGe detector Cu Fe Al Si Ti Stainless steel Pure material samples: Advanced Concepts and Science Payloads A. Owens, T. Peacock Test beam at Bessy - I

Parametric analysis: fit to a gaussian Compare experimental and simulated distributions Detector effects! (resolution, efficiency) Photon energy Experimental data Simulation Precision better than 1% % difference of photon energies Comparison with experimental data

Advanced Concepts and Science Payloads A. Owens, T. Peacock Si GaAs FCM beamline Si reference XRF chamber Complex geological materials Hawaiian basalt Icelandic basalt Anorthosite Dolerite Gabbro Hematite Test beam at Bessy - II

Simulation User-friendly modification of experimental set-up Detector (Si(Li)) response function and efficiency reproduction

Modeling the experimental set-up Rock samples irradiation and fluorescence emission measurement Geant4 Deexcitation Physics Validation Creation of a reference database The simulation reproduces: - Complex geological materials - Experimental Geometry - Response and efficiency of the detector

Physics involved ● The physics involved is based on the ● Low Energy Electromagnetic Package ● - Atomic Deexcitation ● - Fluorescence Emission ● Future test beam ● Test beams contributed significantly to the validation of Geant4 Low Energy Electromagnetic Package/Atomic Deexcitation

Simulation results: test beam validation Agreement between simulations and experimental data High statistical correlation between experimental data and simulations (p< 0.001) simulations experimental Fluorescence spectra from Iceland Basalt E=6.5 keV E=8.3 keV Fluorescence spectra from Iceland Basalt Energy (keV) Counts

Statistical Analysis Parametrical analysis of the results Pure elements Comparison between experimental and simulated entire distributions Complex materials Several peaks Physical background Anderson-Darling test Goodness-of-Fit test belonging to Kolmogorov test family Not sensitive to data binning No need for symmetric distributions No threshold counts/bin Anderson-Darling test Goodness-of-Fit test belonging to Kolmogorov test family Not sensitive to data binning No need for symmetric distributions No threshold counts/bin Good agreement between simulations and experimental data (p >0.05) Atomic Deexcitation Physical Validation

●i●i Simulation Results Differences between simulations and experimental data are ascribable to: - The nominal composition is different from the real one (extra peaks are due to K and L lines of Cr) - The detector response is not well known at low energies (E < 3.5 keV) (E < 3.5 keV) - Contaminations within the test beam (?)

Complex simulations require long execution time Execution time reducion gives fruibility for application DIANE allows GRID usage transaprently Integration for the application performed generally, available for any Geant4 application DIANE (Distributed Analysis Environment) 2 tests: public cluster (30 – 35 machines LXPLUS) and dedicated cluster (15 machines LXSHARE) Execution times reduction: ~ one order of magnitude (24h – 750M events) IN COLLABORATION WITH JUKUB MOSCICKI

CONCLUSIONS (I) Validation of the Validation of the Deexcitation Package Physics Complex materials modelisation Modelisation of the entire experimental set-up

CONCLUSIONS (II) This is one of the advanced examples of the unique using the Low Energy Package with fluorescence emission the unique using the Low Energy Package with fluorescence emission Creation of rocks libraries of astrophysics interest simulated spectra are validated with respect to experimental data simulated spectra are validated with respect to experimental data Future developments: - other rocks simulations (irradiated with solar spectra) - simulation code optimisation, - simulation of the BepiColombo Mission as a whole Paper submission to IEEE- Transactions on Nuclear Science: Novembre 2004