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

The km3 code

C.W.James, Bologna, April 25th 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 26th-28th, 2012

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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.


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Gen geometry

C.W.James, ANTARES collaboration meeting Strasbourg, Nov 21st-24th 2011.

L = 1 m

r1 = 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 photonsthat get here

Record a fraction ofphotons 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.


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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)


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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 26th-28th, 2012.

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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/energyC.W.James, ANTARES Monte-Carlo group workshop, Bologna, April 26th-28th, 2012

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 (102, 103, 104, 105 MeV)

- 1 muon energy (105 MeV)


Again – thanks Claudio for the figure!

+ binning scattered photons by hit

‘low’ bins‘high’ bins

θC

• OLD distribution: new distribution has a greater weighting towards the Cherenkov peak


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Inverse cumulative distributions…


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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)


Example of gen output

These are scattered photons!(most scatters are small)

Wavelength and directional information not shown)


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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


e-,100 MeV

e-,1

GeV

e-,10 GeV

μ,100 GeV

e-,100 GeV

μ

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km3mc

• A program to determine photon arrival times at optical modules from muon tracks.


Tables of hit probabilities & times(function of relative photon/OM geometry)

e-,100 MeV

e-,1 GeV

Source & Detectors - Incident muon (e.g. genhen) - Detector geometry (ANTARES)

e-,10

GeV

μ,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~106) identical muon tracks

• Plot time-distribution of photon hits

d = 50 m

l = 1

00 m

Direct Cherenkov photon path (430 nm)

74 m

θC

45 m

PMT


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Example of toy-experiment

• Red: what you get when histogramming goes wrong

• Green/blue: (more) correct time-distribution


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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


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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


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’


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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

- vl and vs are the ppm concentrations: ANTARES uses 0.0075 ppm


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 26th-28th, 2012

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 vs and vl 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)


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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)


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

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