The km3 code C.W.James, Bologna, April 25 th 2012

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,

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,

Gen geometry C.W.James, ANTARES collaboration meeting Strasbourg, Nov 21st-24 th 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

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,

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,

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,

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, e -, 100 GeV e -, 100 GeV

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, Again – thanks Claudio for the figure!

+ 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,

Inverse cumulative distributions… C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th,

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,

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,

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, 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

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, 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

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,

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,

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,

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, 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

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,

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 ppm C.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26 th -28 th, Water molecules not spherical (otherwise =1) (otherwise = 4)

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, Scattering due to turbulence: what is the wavelength- dependence of this??? (figure shamelessly plagiarised from Mobley

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 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,

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,