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Review of Ice Models

16-layer. stdkurt. asens. Review of Ice Models. bulk. sudkurt. Kurt Woschnagg, UCB AMANDA Collaboration Meeting Madison, June 29, 2003. mam. f125. kgm. photonics. What is an “ice model”? PTD vs. photonics What models are out there? Which one(s) should/n’t we use?.

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Review of Ice Models

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  1. 16-layer stdkurt asens Review of Ice Models bulk sudkurt Kurt Woschnagg, UCB AMANDA Collaboration Meeting Madison, June 29, 2003 mam f125 kgm photonics What is an “ice model”? PTD vs. photonics What models are out there? Which one(s) should/n’t we use? "Is the ice wrong?"

  2. Ice Model Basics • Need to describe Fphoton(A,t) around light sources (muon tracks, cascades) for simulations of AMANDA events • Tables of Fphoton(A,t) are calculated using Monte Carlo propagation of photons through scattering and absorbing medium (ice) • Dependence on distance, OM orientation, ice properties, etc • Prefer to have simplifications (symmetries, averages, approximations) but must pay price for these

  3. PTD Photons propagated through ice with homogeneous prop. Uses average scattering No intrinsic layering: each OM sees homogeneous ice, different OMs may see different ice Fewer tables Faster Approximations Photonics Photons propagated through ice with varying properties All wavelength dependencies included Layering of ice itself: each OM sees real ice layers More tables Slower Detailed Light propagation codes: two approaches

  4. PTD vs. photonics: layering Bulk PTD Layered PTD photonics 2 3 2 1 2 3 2 1 2 3 2 average ice type 1 type 2 type 3 “real” ice

  5. PTD vs. photonics: wavelength dependence • PTD • Create scattering tables with colorless photons of infinite lifetime propagated through average scattering • Apply absorption on tables assuming Cherenkov spectrum • Photonics • Generate photons from Cherenkov spectrum • Scattering depends on wavelength • Absorption depends on wavelength and is applied during propagation as weight

  6. PTD vs. photonics: light yield Too many photons surviving at larger distances in PTD. Caused by applying absorption to scattering tables assuming Cherenkov spectrum at all distances.

  7. Bulk Ice PTD • Assume homogeneous optical properties • Average scattering and absorption (F) over wavelength • Sometimes referred to by it’s F value (100): f125, f096 + simple model, fast – does not have layering

  8. F value for dust absorption Definition (from 20th century): adust = 0.01 F (l/337)-1.16 used in PTD Compare to adust = CMdustl-1.08 used in photonics

  9. The “kurt” Model(S. Hundertmark) PTD • Use measured ice properties available at the time* (532 nm, DC data) • Introduce vertical ice profile – layers (16-layer model) • Average scattering over wavelength by scaling: 0.9·le(532) • Take absorption at 420 nm and apply scaling: 0.85·la(420) • Assume linear correlation between absorption (dust) and scattering • Flavors: ►standard kurt (stdkurt) – uses Goobar glass measurements ►Sudhoff kurt (sudkurt) – uses Sudhoff glass measurements ►asens – uses angsens modification of angular OM acceptance + based on measured ice properties with layers – measured ice does not work well with PTD – averaging incorrect – abs/scat correlation incorrect (not known at the time) * May 2000

  10. The Kurt-Gary Model (KGM)(Gary, Kurt) PTD • Use same measurements as for “kurt” plus additional wavelengths = best measured properties as of Fall 2001 • Recalculate averages over wavelength: 0.9 → 0.7-0.8 for absorption/scattering length scaling • Reoptimize depth layers + based on measured ice properties with layers + more realistic averaging + dirtier ice consistent with data/MC disagreement – measured ice does not work well with PTD – abs/scat correlation still incorrect

  11. Effective Wavelength Spectrum Cherenkov spectrum + glass + gel + PMT But… 1/l2 only at source, so not really correct

  12. “kurt”-KGM comparison

  13. PTD The Muon Absorption Model (MAM)(Gary, Albrecht, Paolo) • Look at time residuals for downgoing muons → too many late hits in MC • Increase absorption to make time residuals match between data & MC • Use same depth layering as in KGM • Modified absorption independent of input model + Downgoing muons “fit” + Better MC/data agreement – Tuning … Does not use measured absorption

  14. Absorption in Old Photonics Old photonics KGM Data Better dust/be(532) correlation Incorrect correlation between dust concentration and scattering at 532 nm lead to too little absorption in 1st generation (= old) photonics tables

  15. Old vs. New Photonics ~20% less light for new ice model* (*see previous talk for details) From Ped’s talk

  16. Summary & Recommendations • The commonly used ice models (“kurt”, KGM, MAM, bulk, asens) are all based on PTD tables • There’s nothing wrong with that – but know what you’re using • Due to (justified) simplifications in the treatment of wavelength dependence and layering in PTD-based models certain features in the data are not reproduced (e.g. cogz structure*), especially when actual ice properties are used ► Make effort to transition to photonics! ► Still ~OK to use MAM/KGM/bulk for certain cases (i.e. when the MC does describe the specific class of data) while we wait for photonics ► Do not use “kurt” model ► Do not use 1st generation photonics tables Next time: hole ice *See Marek’s study introducing thin layers of infinite absorption as a fix

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