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The km3 code C.W.James, Bologna, April 25 th 2012
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The km3 package Used in ANTARES to simulate the photon detection from muons Code: Fortran77 (I hate it) Written in the late 90s Documentation: various ANTARES internal notes Numerous updates by various authors – v2: David Bailey; v3- v4r2 Goulven Guillard, v4r3+ myself) v4r3 documented, v4r4 development version Gen, hit, km3mc: Three separate programs Many interdependencies (explicit and implicit) Incorporate GEANT 3.21 and MUSIC C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 2
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Gen (physics lives here) Uses GEANT 3.21 to model particle interactions from an initial input (e.g. a muon) Generates Cherenkov photons from GEANT tracks. Propagates photons using (wavelength- dependent) scattering and absorption. Records photon properties to disk at each of several spheres. C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 3
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Gen geometry C.W.James, ANTARES collaboration meeting Strasbourg, Nov 21st-24 th 2011. 4 L = 1 m r 1 = 2 m r 20 = 200 m 20 radial bins ~ log-spaced * * * record photon properties at sphere 1 record new photon properties at sphere 2 … Problem: Few photons make it to the outer shells: generate many photons Excess of photons on inner shells Solution: record a random fraction of photons, with p increasing with r record all photons that get here Record a fraction of photons crossing here
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Gen output: Writes photon information at each shell: Writes only a fraction of the photons generated. Fraction increases with distance (less photons make it to outer shells) Major disk-space requirement! Photon statistics limited by 1 GB output file size of f77 Currently more annoyance than a limitation: but may need to be overcome in the future. C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 5
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Tables: electrons and muons Muons Simulates 1 m of 100 GeV muon track Includes secondary electrons below 200 MeV Generates photons using Frank-Tamm formula Electrons Photons from electron (sub) showers Tracks particles to Cherenkov threshold 4 runs: 100 Mev, 1 GeV, 10 GeV, 100 GeV Output: 5 x 1 GB files Run-time: O ~ 10 hr on a single CPU (=nothing) C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 6
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Major limitations to gen Only used to generate electron and muon tables (what about hadronic showers from neutrino interactions in the detector?) i/o (=f77) currently limits statistics Scattering and absorption models are imperfect – in situ measurements are often inconclusive. C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012. 7
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Hit (the boring program) Photon list -> summary histograms Reads photon data from Gen. Creates histograms as function of distance, angles to the track segment. Folds in OM response (e.g. quantum efficiency of PMTs). Generates tables of photon-hit probabilities and hit-time distributions. Summary tables -> file. Inverse cumulative time distributions & hit probabilities. All tables for given [gen] particle type/energy C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 8 e -, 100 GeV e -, 100 GeV
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Histogramming (in gen and hit) Hit times (t) 50 bins in time OM orientation (in angles θ, ϕ ) Direct: 10x1 Scattered: 5x3 Distance from track segment 20 log-spaced bins in r for all photons Angle from track segment 1 bin for direct photons from muons 20 bins for all other cases Emitting particle type/energy 4 electron energies (10 2, 10 3, 10 4, 10 5 MeV) 1 muon energy (10 5 MeV) C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 9 Again – thanks Claudio for the figure!
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+ binning scattered photons by hit ‘low’ bins ‘high’ bins θCθC OLD distribution: new distribution has a greater weighting towards the Cherenkov peak C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 10
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Inverse cumulative distributions… C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 11
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Output: 5 files of size ~32 MB 4 photon tables: Direct and scattered hit probabilities Direct and scattered hit times These are created once and used repeatedly for ANTARES simulation input Limitations: Histograms are sparse (wrong choice of spacing has caused problems in the past) Extremely memory-inefficient (by a factor of x30 or more) C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 12
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Example of gen output These are scattered photons! (most scatters are small) Wavelength and directional information not shown) C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 13
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km3mc Inputs: Hit tables PMT locations and orientations Incident particle (single muon) Step 1: run MUSIC Muon propagation code Simulates muon interactions: muon energy-loss, and secondary EM sub-showers above 100 MeV Step 2: get detector hits Interpolate between, and sample from, tables to get photon hit times for each (2m) track segment, and each EM sub- shower Outputs a list of OM hit magnitudes (nphtons) and times C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 14 e -, 100 Me V e -, 100 Me V e -, 1 Ge V e -, 1 Ge V e -, 10 Ge V e -, 10 Ge V μ, 100 Ge V μ, 100 Ge V e -, 100 Ge V e -, 100 Ge V μ
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km3mc A program to determine photon arrival times at optical modules from muon tracks. C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 15 Tables of hit probabilities & times (function of relative photon/OM geometry) e -, 100 MeV e -, 100 MeV e -, 1 GeV e -, 1 GeV Source & Detectors - Incident muon (e.g. genhen) - Detector geometry (ANTARES) e -, 10 GeV e -, 10 GeV μ, 100 GeV μ, 100 GeV e -, 100 GeV e -, 100 GeV INPUTS to km3 Detector hits 1: generate muon & secondary tracks (use MUSIC) 2: interpolate between, and sample from, tables to get photons hits from tracks. What km3 does
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Testing km3: toy experiments Use simple ‘detector’ to test performance of km3 Use a single PMT Fix muon energy, e.g. 1 TeV Use characteristic geometry Repeat for many (O~10 6 ) identical muon tracks Plot time-distribution of photon hits d = 50 m l = 100 m Direct Cherenkov photon path (430 nm) 74 m θCθCθCθC 45 m PMT C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 16
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Example of toy-experiment Red: what you get when histogramming goes wrong Green/blue: (more) correct time-distribution C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 17
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Desired improvements in km3mc Handling of hadronic cascades Current tables are only for EM showers and muons Require the geasim package to handle neutrino ‘shower’ events Potential fixes: Approximate cascades from recoil quark jet particles (mostly pions) with an effective electron cascade (‘one-particle approximation’ Produce pion tables in gen? More accurate histograms More bins in all dimensions for better interpolation Requires restructuring the i/o of gen & hit C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012. 18
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What is km3 really? Five functions, three programs, one package Simulation of particle tracks (gen) Creation, propagation, and detection of photons (gen) Histogramming (hit) Simulation of stochastic energy-loss (km3mc) Interpolation between and sampling from histograms (km3mc) Thinking of km3 as a single ‘thing’ is difficult – and some parts work better than others C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 19 Storing this information is prohibitive - keeping it as one package is sensible Storing this information is becoming difficult… merge into hit, or re-write i/o? Tables produced are km3mc-specific: separate this process? Generated information is small – processes could be separated
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Summary km3 handles photon production and detection from high-energy muons in ANTARES Consists of three sub-programs (gen, hit, km3mc) Implementation currently limits histogram precision (will be overcome… some time) Next set of modifications: test ‘one-particle approximation’ C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012. 20
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Light scattering and propagation ‘Rayleigh’ scattering (should be Einstein- Smoluchowski scattering): Consider this ~100% accurate (theory + measurements) Particulates (Kopelevich model): ‘Mie scattering’ Water = molecules + small + large particles v l and v s are the ppm concentrations: ANTARES uses 0.0075 ppm C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 21 Water molecules not spherical (otherwise =1) (otherwise = 4)
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Comparison with measurements Best (~only) measurements of angular-dependent volume- scattering function in actual seawater: Petzold (1972) Kopelevich model OK at angles >1 degree (~514 nm) C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 22 Scattering due to turbulence: what is the wavelength- dependence of this??? (figure shamelessly plagiarised from Mobley
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Antares approach Scattering probability: Onsite measurements of scattering + absorption (difficult to deconvolve) Fit to Kopelevich v s and v l for total scattering probability (2004) (get 0.0075 ppm) Scattered angle: Calculate ratio of ‘Rayleigh’ / ‘Mie’ scattering using Kopelevich ‘Rayleigh’: use analytic formula to get scattering angle ψ ‘Mie’: use the measurements of Petzold Ratio of Mie/Rayleigh was fixed until ~now (v4r4 of km3 separates them) C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 23
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Problems with current approach Petzold’s measurements not wavelength- dependent Wavelength-dependence of turbulent scattering probability unknown ‘Mie’ scattering will be time-dependent (mostly off biological material) Kopelevich theory fits Petzold’s measurements: does this mean it’s correct? … Does all of this really matter? (requires end-to- end MC study of errors) C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, 2012 24
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