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Status of the AGATA PSA

Status of the AGATA PSA. For the PSA team, P. Désesquelles (IPN Orsay). desesque@ipno.in2p3.fr. PSA formalization (1). X =. One segment. One « Meta-signal » : hit segment+4(or 8) neighbors. 0 0 E 1 0 0 E 2 0. Energy deposit in a voxel. S 1. MGS. …. …. T. S =. …. T -1 ?.

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Status of the AGATA PSA

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  1. Status of the AGATA PSA For the PSA team, P. Désesquelles (IPN Orsay) desesque@ipno.in2p3.fr AGATA week in Darmstadt

  2. PSA formalization (1) X = One segment One « Meta-signal » : hit segment+4(or 8) neighbors 0 0 E1 0 0 E2 0 Energy deposit in a voxel S1 MGS … … T S = … T-1 ? … AGATA week in Darmstadt

  3. PSA formalization (2) 1 0 0 about 50 voxels/segment … X Each column = MGS signal 10 ns bins S1 TX = S : T S1 AGATA week in Darmstadt

  4. Tasks • Number of hits • Folding algo. (Milano/Munchen) not adapted. • Smoothing/derivation (Orsay) not adapted. • Derivation/data base (Milano) >65%(→ PSA meeting). • Acclivity (Darmstadt) in progress. • Neural networks (Orsay) in progress. • Discriminant Analysis (Strasbourg/Orsay) next. AGATA week in Darmstadt

  5. Tasks • Location and energy • Neural networks (Orsay/Munchen) not adapted. • Multivariate Analysis (Strasbourg) not adapted. • Genetic algo. (Legnaro/ Darmstadt) too slow → coupled with grid search (→ PSA meeting). • Wavelets (Darmstadt) in progress (→ PSA meeting). • Wavelets + grid descent (Orsay+Saclay) in progress (→ PSA meeting). • Matrix Inversion (Orsay+Strasbourg) in progress (→ PSA meeting). AGATA week in Darmstadt

  6. Thus… • Difficulties with A.I. methods. • Exp. info. must be used in an optimum way. • Math. before algo. AGATA week in Darmstadt

  7. Difficulties (1) “Sensitivity” = How much S is changed for a given X shift shift shift  very large sensitivity range  very low sensitivity zones AGATA week in Darmstadt

  8. Difficulties (2) 23 G ill conditioned transform  signals mainly sensitive to c.m. of energy deposits AGATA week in Darmstadt

  9. Difficulties (3) Treat the realistic case : • Multi hits • True noise • The signal does not belong to the base • distance between the hits • relative energies • neighbor segments • whole detector • number of hits unknown • sampling rate • time AGATA week in Darmstadt

  10. Grid to choice AGATA week in Darmstadt (we work with the last one)

  11. A grid adapted to the sensitivity c2 between grid points > c2min  Condition number divided by 4 to 10 AGATA week in Darmstadt

  12. Sampling time One hit in each of two neighboring segments Very preliminary  resolution is not worsen up to 150 ns bins ! AGATA week in Darmstadt

  13. Performances for one segment • Location : • 0.3 mm ! (1 hit) • 2 mm (simple multi-hit) • Energy : • 1% (1 hit) • some % (simple multi-hit) • Time : • ~ ms (1 hit) • 0.1 s (simple multi-hit on 2.4 GHz Matlab) AGATA week in Darmstadt

  14. Conclusions • The single-isolated hit PSA is solved → neural networks • The front-end can include : • Signals preprocessing • Single-isolated hit PSA • Tagging of events → which algo to use • The multi-hit PSA is difficult ! • The X → S transform is not well conditioned • Large sensitivity range • Multi hits at the same r,q • Juge an algo on realistic case • We should include numerical analysis specialists in our group AGATA week in Darmstadt

  15. Thank you AGATA week in Darmstadt

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