Status of Sirene Maarten de Jong. What?  Sirene is yet another program that simulates the detector response to muons and showers  It uses a general.

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Presentation transcript:

Status of Sirene Maarten de Jong

What?  Sirene is yet another program that simulates the detector response to muons and showers  It uses a general purpose collections framework for PDF tables ‒allows for optimisation of accuracy and speed of interpolations ‒facilitates I/O

JTools  A Java inspired collections framework in C ++ with multi- dimensional interpolation functionality – different collection types each collection has map functionality – variable bin size O (log(N))access time – equidistant bins O (1)access time – allows for any number of dimensions and bins binning in dimension n may depend on bin in dimension n-1 – allows for different interpolation algorithms polynomial spline – allows for a mixture of different collection types (new) use of type lists

JPhysics  Formalism for light production, propagation and detection ‒semi-analytical PDFs, based on single scattering approximation  Custom classes for PDF/CDF tables ‒treatment of weight functions to improve accuracy of interpolations (or equivalently reduce number of bins) ‒may serve as input to Sirene  Custom muon energy loss cross sections and shower energy generation (Paul Kooijman) – Bremmstrahlung(threshold 10 MeV) – pair production(threshold100 MeV) – implementation photo-nuclear interactions pending

Procedure 1.Make PDF tables ‒at present, JPhysics table generators are used ‒other applications can be interfaced readily 2.Convert PDFs to CDFs ‒allows to make various checks 3.Run event processor ‒read detector geometry ‒setup radiation tables (to speed up determination of cross section and shower energy for pair production) ‒setup tables with maximal light yield (eliminate dependence on orientation of PMT) ‒event loop

Standard Antares Monte Carlo production “km3 + geasim”

Processing steps 1.Read Event from MonteCarloEventWriter output file 2.Remove existing hits, if any 3.Propagate muon(s) ‒simulate energy loss and EM-showers ‒generate hits 4.Process shower particles from primary vertex ‒simulate hadronic showers as an EM shower, but assign different weights to the energies of different particle species ‒generate hits as one shower but use correct longitudinal profile of individual showers 5.Merge hits (to speed-up TriggerEfficiency) ‒  T max typically 15 ps 6.Write Event to MonteCarloEventWriter compatible output file

E [GeV] Trigger effective volume Volume [m 3 ] km3 (V3.7) Sirene ± 10% Ratio

Muon light yield light yield [n.p.e] direct scattered km3 (V3.7) Sirene E [GeV]

Muon PDF  t [ns] direct scattered km3 (V3.7) Sirene light yield [n.p.e]

EM-shower light yield direct scattered km3 (V3.7) Sirene E [GeV] light yield [n.p.e]

EM-shower PDF  t [ns] direct scattered km3 (V3.7) Sirene light yield [n.p.e]

Performance E [GeV] time [ms] ¶ Events with ≥ 1 hits Average time per event ¶

First tests KM3NeT Monte Carlo production

KM3NeT  Detector ‒154 towers, each with 40 optical modules, each with 31 PMTs ‒number of PMTs154 x 40 x 31 = 190,960 ‒geometryref154_3inch31pm180_ det  PMT ‒type3 inch, standard Bialkali ‒light collector ringacceptance += 20%  Generation ‒particlesmuon neutrinos ‒Energy spectrumE -1.4 ‒Energy range[10 2,10 7 ] GeV  Running time – km3 (V4.3) ~ 135minutes / 35,000 events – Sirene ~ 12minutes / 35,000 events

muon light yield direct scattered km3 (V4.3) Sirene E [GeV] light yield [n.p.e]

Muon PDF  t [ns] direct scattered km3 (V4.3) Sirene light yield [n.p.e]

EM-shower light yield direct + scattered E [GeV] km3 (V4.3) Sirene In km3 V4.3 direct light from EM-showers is tabulated together with scattered light from EM-showers light yield [n.p.e]

EM-shower PDF  t [ns] direct + scattered km3 (V4.3) Sirene light yield [n.p.e] In km3 V4.3 direct light from EM-showers is tabulated together with scattered light from EM-showers

Performance E [GeV] time [ms] ¶ Events with ≥ 1 hits Average time per event ¶

Summary & Outlook  Sirene is a new program that simulates detector response to muons and showers  Antares ‒trigger effective volume is similar ‒distributions of arrival times are slightly different ¶ ‒Sirene is ready for use...  KM3NeT ‒distributions of arrival times in km3 V4.3 seem to be more reliable than V3.7 (thanks to Clancy James) ‒Sirene is ready for tests... ¶ problem in Sirene with light from EM-showers fixed (shower energy)

Summary & Outlook (II)  Possible improvements – include photo-nuclear cross sections – include [multiple] scattering of muon  Possible enhancements ‒generation of neutrino vertex and simulation of detector response, possibly including real-time trigger, could operate in a single step for the run- by-run Monte Carlo simulation