Untriggered data GRB analysis (M. Sanguineti)

Presentazione sul tema: "Untriggered data GRB analysis (M. Sanguineti)"— Transcript della presentazione:

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2 Untriggered data GRB analysis (M. Sanguineti)
Il rate di rivelazione di ANTARES è troppo elevato per registrare ogni singolo segnale, perciò i dati vengono filtrati per selezionare solo gli eventi di interesse fisico. Tuttavia quando i telescopi ottici rivelano un evento interessante come un GRB o una supernova, un segnale di allarme viene inviato ad ANTARES e tutti i filtri vengono disabilitati. Per l’analisi di questo “speciale” campione di dati è stato sviluppato un algoritmo di ricostruzione dedicato ed un filtro direzionale per privilegiare gli eventi coerenti con la posizione del GRB. I risultati della simulazioni Monte Carlo mostrano un discreto aumento della sensibilità specialmente a basse energie.

3 Moon shadow analysis (M. Sanguineti)
I raggi cosmici possono essere assorbiti dalla Luna creando un’ “ombra” nella distribuzione dei muoni rivelati da ANTARES. L’ombra della Luna può essere utilizzata come sorgente di calibrazione per verificare le performance di puntamento assoluto del telescopio. data Il deficit di eventi è stato rivelato con una significatività del 3 σ. La risoluzione angolare con cui è stata rivelata l’ombra della Luna è 0.7°, dunque la risoluzione angolare assoluta di ANTARES è 0.3°. Questo valore è perfettamente coerente con la risoluzione angolare prevista con simulazioni Monte Carlo. raggio della Luna distanza dal centro della Luna

4 Camera oscura per il test del piano torre
Coperchio mobile Supporto laterale Supporto centrale Parte inferiore fissa Cereseto Roberto

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6 Full GEANT4 simulation of optical module
Christophe Hugon

7 Water Properties studies
Simulation status Done and in production mode Well engaged, very experimental results Development initiated Done and in testing mode Antares Geom DOM Geom Nemo Geom Angular acceptance K40 measurement Water Properties studies KM3Sim Core PMT geometry PMT efficiency Material properties [...] Scattering in water GEANT4 The new code architecture allow to work on different tasks independently and easily Christophe Hugon

8 The simulation results
Geometry The geometry of the both ongoing detectors is done. The efficiency of the OMs are at their best fits Antares OMs KM3-NeT-t OMs + full structure geometry Water properties The water properties simulation (scattering+absorption) is fully implemented. It uses the ANTARES parameters and waits for the calibration analysis results. The K40 simulation (coincidences) Is done for ANTARES and KM3-NeT-it, It allowed to get a best fit for the OM efficiency. Christophe Hugon

9 Timing measurement in the detector
LED of the OM 11 of runs 684 to 687 LED mean wavelength at 470 nm LED flash at 2 kHz => peaks observables within a modulo 500 us timing plot 80 m Floor 8 Floor 7 Floor 6 Floor 5 Floor 4 Floor 3 Floor 2 Floor 1 3 Christophe Hugon

10 Previous results summary
The distribution gives a good time distribution. But the intensities in function of distance are not as expected LED positioning ? LED homogeneity ? LED used ? Different intensities ? A specific analysis is done to reduce those uncertainties This kind of information is really hard to find and imprecise (in time and duration) A specific analysis to deduce these informations ? Christophe Hugon

11 The water properties Two components: (200 meters of distance)
On particules Small angles, small delay On molecules Big angles, big time delay Those two effects are seen in simulation: Best fit is on going (200 meters of distance) Christophe Hugon

12 Water properties status
Concentric detection sphere Separated by the real floor to floor distance The source is in the center Send photons All the photon are kept at each level. Data kept Emission direction (in fact always (0,0,1) Time arrival at each spere Angle arrival Incident angle Then the AA is used to put a weigh to the arrival The goal is to include The km3 scattering parameter The theoretic implementation to do the best fit with data Time arrival to the 1st floor GEANT4 scattering parameters Very preliminary (40m of distance) Christophe Hugon

13 studies of the LED run characteristics
Floor charge per second OM1 from LED floor 2 4th floor 3rd floor 2nd floor 4th floor LED short test at low intensity Floor orientation effect LED of floor 1 Christophe Hugon

14 A. Orzelli, V. Kulikovskiy, P. Musico, C. Hugon, M. Cresta
CLBv2 at Genova A. Orzelli, V. Kulikovskiy, P. Musico, C. Hugon, M. Cresta A. Orzelli

15 Activity in Genova Schematic realization of CLBv2 (starting from CLBv1) Master realization of CLBv2 Acoustic and Instrumentation FW module implementation FW integration and debug (together with all working groups) A. Orzelli

16 CLBv2 Differences between CLBv2 and CLBv1: FPGA embedded
Instrumentation embedded Optical communication with Laser (not REAM) White Rabbit compliant A. Orzelli

17 FW development: Acoustic
Implemented and tested a FW module to decode the acoustic AES3 data format Debug and test of the module, receiving data on a PC Integration of the module in the whole CLBv2 FW A. Orzelli

18 FW development: Instrumentation
Implemented and tested the communication with the embedded instrumentation (temperature & humidity sensor, tilt & compass) via I2C bus (in collaboration with INFN – Bologna and LNS) Pitch stability of the tilt & compass A. Orzelli

19 Current work Integrating instrumentation FW in the whole design
Testing and debugging the data path of the whole design (acoustic and PMT data) PMT test: a Pattern Generator sends signals to the Pseudo Octopus boards plugged on the CLBv2. The FW acquire the data and send them to a PC via Optical Fiber A. Orzelli

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