Key Experiments Key Experiments and Simulation: and Simulation: - PowerPoint PPT Presentation

Key Experiments Key Experiments and Simulation: and Simulation: Status Report Status Report E.Farnea INFN Sezione di Padova, Italy AGATA Week, Strasbourg, November 24 th , 2005

Outline Outline • Performance of the Demonstrator • Some examples from “realistic” Monte Carlo simulations

The AGATA Demonstrator The AGATA Demonstrator 5 asymmetric triple-clusters (in the simulation!) 36-fold segmented crystals 540 segments 555 digital-channels Main issue is Doppler correction capability � coupling to beam and recoil tracking devices However, the performance However, the performance figures quoted in the following figures quoted in the following do include the effect of the do include the effect of the tracking algorithms tracking algorithms

Performance Performance Photopeak efficiency P/T Ratio ~14cm: Possible target-detector distance for the Demonstrator on PRISMA 1 MeV photons, point source at rest. Tracking is performed.

Effect of the recoil velocity Effect of the recoil velocity Peak FWHM Photopeak efficiency Typical values for reaction products at PRISMA 1 MeV photons, M γ = 1. Tracking is performed.

A simplified approach to PSA: Grid search A simplified approach to PSA: Grid search • The analysis of the MARS in-beam experiment proved that similar values for the peak FWHM are obtained using a (generic) genetic algorithm or a simplified grid search approach assuming a single interaction point per segment. • How does the performance of the Demonstrator change if such an approach is used? Grid search Genetic algorithm Raw F = 1 16 keV F = 2 F = 3 R.Venturelli, Munich PSA meeting, September 2004

Possibility to start with Possibility to start with a simplified PSA approach? a simplified PSA approach? Peak FWHM Photopeak efficiency 1 MeV photons. Tracking is performed. In the “pack” case, only one interaction per segment is assumed.

Detector response Pulse shape generation Event generation • • A 0.55 r [ cm ] • B • 1.0 • C • 1.45 • D 1.9 • E • 2.35 • • F 2.8 • • G 3.25 • H • 3.7 • 1.13 0.94 ∗ • 0.63 z [ cm ] 0.31 • 0.0 ϕ 15˚ 22.5˚ 27˚ 0˚ 7.5˚ 0 E F 0.2 G -0.25 A H 0 -0.5 B C D G E rel. amplitude rel. amplitude H F -0.75 -0.2 D C B A • • • • -1 0 0.2 -0.25 0 -0.5 -0.75 -0.2 • • • • -1 100 200 300 100 200 300 100 200 300 100 200 300 Data Analysis t [ ns ] t [ ns ] Electronics Response Function Packing and smearing of simulated data γ -ray tracking Pulse Shape Analysis to decompose recorded waves

An example generator: An example generator: cascadeEvents cascadeEvents • Written by F.Recchia • Suited for fusion-evaporation reactions • Cross sections and centre-of-mass spectra read from CASCADE output files • Discrete cascades generated with GammaWare (O.Stezowski) • Similar approach by C.Mihai (different treatment of the continuum γ rays) Short presentations by F.Recchia and C.Mihai Key Experiments and Simulation Team Meeting

AGATA vs. Conventional arrays AGATA vs. Conventional arrays π AGATA 1 π GASP Conf. II AGATA 1 GASP Conf. II 45 HPGe detectors 40 HPGe detectors (15 triple clusters) with anti Compton

Data generation and analysis Data generation and analysis • Event production with cascadeEvents • Response function of AGATA: list-mode file with the interaction points produced via the Geant4 code • Gamma-ray tracking with mgt and production of a reduced dataset in GASP reduced format (photon energy and direction; information from the ancillary detectors) • Analysis of the reduced dataset with the standard GASP data analysis programs

“Realistic” Simulations “Realistic” Simulations γ Fold 1 γ Fold 3 AGATA 1 π array GASP Conf.II 28 Si + 28 Si@125 MeV. Particle detection with EUCLIDES. Kinematical recalibration. E.Farnea, F.Recchia E.Farnea, F.Recchia

Better quality of the spectra? Better quality of the spectra? AGATA 28 Si + 28 Si@125 MeV. 1 π array Particle detection with EUCLIDES. No kinematical recalibration. GASP Conf.II No difference (save for efficiency) if kinematical recalibration is NOT performed!!!

Another example: PRISMA + AGATA Demonstrator Another example: PRISMA + AGATA Demonstrator ps, , Y ~ 350 ps X = 1 mm ∆ X = 1 mm t ~ 350 Y = 1 mm ∆ Y = 1 mm Y position ∆ Y = 2 mm Y = 2 mm Y position ∆ t ∆ ∆ AGATA ∆ ∆ X Demonstrator Dipole MCP Ion Chamber Quadrupole MWPPAC 195 MeV 195 MeV 36 36 S + S + 208 208 Pb, Pb, θ lab = 80 = 80 o o θ lab Z=28 Simplifications are Z=28 ∆ Z ~ 60 for Z=20 Z ~ 60 for Z=20 X position X position ps < 500 ps E/E < 2% ∆ E/E < 2% necessary to try t < 500 X = 1 mm ∆ X = 1 mm .) a.u.) E (a.u and describe such ∆ E ( ∆ t ∆ ∆ ∆ a complex setup! ∆ Z=16 Z=16 Z/ ∆ Z/ E. Fioretto E. Fioretto INFN - LNL INFN - LNL E ( E (a.u a.u.) .)

Physics Input: PRISMA + CLARA Physics Input: PRISMA + CLARA Mass Distribution Recoil Velocity How can we emulate such physics input in a MC Simulation?

Data generation and analysis Data generation and analysis • Goal of the simulation: evaluate the Doppler correction capabilities of Demonstrator + PRISMA • Major problem: reproduce the experimental distribution of reaction products and velocities • Solution: use experimental values! (N.M ă rginean) replaying an actual PRISMA+CLARA experiment • PRISMA entrance detector emulated with a pixel detector, pixel size corresponding to the typical position resolution

Data generation and analysis Data generation and analysis • Since the peak FWHM is the only concern, only one gamma per event is fired • Mass resolution is neglected • Trick to avoid contaminations from neighbouring peaks in the final spectra: only one nucleus emits its “real” energy, the others get a different one (with a large energy difference) • Velocity module of the recoil deduced from the simulated time of flight • Recoil direction deduced from the pixel

PRISMA+demonstrator PRISMA+demonstrator FWHM 3.3 keV 2.6 keV 5.9 keV Other isotopes: 1332.5 keV 78 Ge: 2 + → 0 + energy E.Farnea, N.M ă rginean E.Farnea, N.M ă rginean

Summary Summary • The performance of the Demonstrator Array have been reevaluated (see also http://agata.pd.infn.it) • Work has been done on the generation and analysis of “realistic” events • Much work on that remains! Contributions are more than welcome!