Photonics TablesBin Optimization

Kyle MandliPaolo Desiati

University of Wisconsin – Madison

Wuppertal AMANDA Collaboration Meeting

• Stephan: comparison between PTD bulk tables and Photonics bulk tables (muon, shower)– Check if Photonics bulk tables are consistent with PTD– New AMASIM release and bulk tables test

• Thomas: implement PSI interface for Photonics, PTD and NN-fit tables

• Johan: work with Thomas in PSI and produce Stephan’s test using PSI– Check results consistency with different interface (IceCube)

• Daan: working on NN-fit procedure of Photonics tables and produce comparison tests with tables

themselves– Check if NN fit are a good approximation to speedup

simulations

Where are we ?

• Ignacio: implement the zenith bin-wise production– Another simulation speed up possibility

• Adam,David H.: check memory map feasibility– Yet another simulation speed up possibility

• Kyle M.: Photonics tables bin optimization– Come up with a binning as a good compromise between good ice

description and an acceptable table size

Bin optimization is the topic of this talk

Where are we ?

• Light tracking binning:– Photons tracked using 6 parameters: ρ, φ , z, t, θe, θa

• This affects the table size

• Light source binning:– depth (z) & angle (θ) binning

• This affects the number of tables

• Table types:– Point-like ems and muon tables (differential or level1 tables)

– Infinite muon tables (extended source or level2 tables)

– Time-integrated amplitude PDF tables (.abs, smaller tables)

– Integral PDF time tables (.prob, full binning tables)

– Differential time probability table

http://amanda.wisc.edu/simulation/photoproduction/tables

1-slide tutorial

• Produce single tables @ given source locations (z=0): only ice propertiesonly ice properties• Produce this table with different tracking binning in ρ, φ, z, t, (θe,θa integrated)

– with statistical errors (interfaces do not read errors at the moment)

Bin optimization proposed procedure

Table ρ φ z t size/table

Ranges 0; 450 0; 180 -450; 450 0; 6000

Tab1 50 18 90 90 29.2 MB

Tab2 45 16 80 80 18.4 MB

Tab3 40 14 70 70 11.0 MB

Tab4 35 12 60 60 6.0 MB

Tab5 30 10 50 50 3.0 MB

Tab6 25 8 40 40 1.3 MB

Tab7 20 6 30 30 0.4 MB

Tab8 15 4 20 20 0.1 MB

• Use Time delay distribution @ given source-receiver dist d– Receiver at reference origin

– Light sources (10 GeV ems) on z=0, random in circle at a given d• Sampling different table projections as in a simulation

• Mean Amplitude & Mean Time Delay versus distance d– Light sources on z=0, random in disk up to ρmax

• Perform a statistical test on ems tables– Kolmogorov-Smirnov test between most dense table and the others

• Calculate max y distance of cumulative histo and the probability that the 2 histograms are generated by a random sampling of the same distribution

• Use of PSIUse of PSI => advantage of root

=> still in development (but new release now)

Optimization procedure

Time delay distribution

20,000 random samples

Time delay distribution

20,000 random samples

Time delay distribution

20,000 random samples

• Compare the most dense table with the others– Calculate the probability that tables in each pair is derived by random

sampling of the same distribution– Test statistic depends on K-S max distance and number of entries in each histo

K-S Test: what we expect

tab-pairs

Prob

Increase bins

Incr

ease

pro

b

K-S Test

K-S TestTab pair Rel Prob

Tab1-2 0.28 (1.00)

Tab1-3 1.00 (3.53)

Tab1-4 0.09 (0.33)

Tab1-5 0.03 (0.1)

Tab1-6 0.001

Tab1-7 1.9e-7

Tab1-8 9.7e-17

• Tab 5 seems to be ~10% consistent with the most dense table• Statistical errors from tables (not accessible) and MC simulation

Table bins reminder

Table ρ φ z t size/table

Tab1 50 18 90 90 29.2 MB

Tab2 45 16 80 80 18.4 MB

Tab3 40 14 70 70 11.0 MB

Tab4 35 12 60 60 6.0 MB

Tab5 30 10 50 50 3.0 MB

Tab6 25 8 40 40 1.3 MB

Tab7 20 6 30 30 0.4 MB

Tab8 15 4 20 20 0.1 MB

Mean Amplitude & Time Delay vs distance

Mean Amplitude & Time Delay vs distance

Mean Amplitude & Time Delay vs distance

K-S Test

K-S TestTab pair Rel Prob

Tab1-2 1.00

Tab1-3 0.19

Tab1-4 0.003

Tab1-5 0.005

Tab1-6 0.001

Tab1-7 7.2e-6

Tab1-8 3.1e-20

• Given statistical fluctuations and table size: Tab 5 good compromise

Table bins reminder

Table ρ φ z t size/table

Tab1 50 18 90 90 29.2 MB

Tab2 45 16 80 80 18.4 MB

Tab3 40 14 70 70 11.0 MB

Tab4 35 12 60 60 6.0 MB

Tab5 30 10 50 50 3.0 MB

Tab6 25 8 40 40 1.3 MB

Tab7 20 6 30 30 0.4 MB

Tab8 15 4 20 20 0.1 MB

• A set of tables where only one dimension tracking binning is varied– The test suggests that changing binning in one dimension does not

significantly affect the tables precision for a relatively wide range of binning.

• A set of infinite muon tables to perform the same test– This test was NOT done so far

– Would require other tables …

• The source location binning to be tested (= layers)– NEXT STEP : it requires the generation of whole set of tables

Other tests

• Suggested table with enough precision and reasonable size– We already used this. Not much improvement !

Conclusion on tracking binning

Table ρ φ z t size prob/diff size abs

Tab5 30 10 50 50 3.0 MB 0.06 MB

Range 450 180 +/- 450 6000 - -

• Infinite muon Tables• These tables have not been tested (educated guess so far)

l ρ φ t size prob/diff size abs

100 30 10 50 6.0 MB 0.12 MB

50 30 10 50 3.0 MB 0.06 MB

Range 1000 450 180 6000 - -

• What we used so far

Source location binning

z_low z_high z_step a_low a_high a_step #tables

-400 +400 20 (40) 0 180 10 (18) 779

• With these values we have• 779 ems.prob + 779 ems.abs = 1558 ems tables = 2.34 GB

• 779 mu.prob + 779 mu.abs = 1558 mu tables = 4.67 GB• 779 mu.prob + 779 mu.abs = 1558 mu tables = 2.34 GB

• Total size : ~ 7 GB (4.67 GB)

• Angular splitting in simulation– Load only the tables corresponding to all z-values and to only the

2 θ-values around the muon track zenith angle• Gain a factor 18/2=9 table size to load = 520 MB

• Use of NN fits of the tables– Do not load any table but use the fit function

• The function is complicated but <<< 1GB

• Speed seems to be very competitive versus tables

• Precision under extensive check

• Memory mapping– Load tables (or portion of tables) on disk and access them using

specific algorithm• Under investigation. More complicated than it seems.

Size and Speed

• Produce baseline tables (ems, muon diff tables)– Photon survival probability only with ice properties

– Binned in θa

• Store those tables : 86 GB but only once !– Different efficiencies can be included without re-generating tables

• Include efficiencies, and produce .prob, .abs and .diff

• Special tables:– UHE, monopole tables : wider ranges (up to 1000 m in z and ρ)

– .diff (dP/dt) tables for reconstruction with finer bins and less dimensions

– Propose to generate them separatelyPropose to generate them separately

Final Table Production

• Efficiencies to be included– Like in previous tables production ?

Final Table Production

Parameter Description What is it

GLASS_N Glass refraction index Borosilicate glass (P. Sudhoff)

GEL_N Gel refraction index “standard gel” n=1.41 (dada_attn.f)

QE Quantum Efficiency Hamamatsu 8” (R5912) from catalogue

GLASS Glass transmittance Benthos housing (P. Sudhoff)

GEL Gel transmittance “standard gel” 100% (dada_attn.f)

SENS Angular sensitivity Measurement by CHW (AIR 19960301)

HOLE Hole ice model 50cm scattering length

OM_CORR Curvature correction 13” benthos housing

DYNODE 1st dynode coll eff 0.7884

PMT Collection area (m^2) 0.0284

• Lots of progress recently and still on the way

• Waiting for layered tables: will be on disk next week– Still waiting for me ? I remind that we already have tables !

• Efficiencies can be changed faster

• Start simulation for further tests– Purely interface reading (i.e. PSI)

– AMASIM runs: speed

– Theta angle binning of muons

– NN testing

• NEED OF PEOPLE CURIOUS ABOUT THE SECRETS OF PHOTONICS

Conclusions

http://amanda.wisc.edu/simulation/photoproduction/tables

Conclusions