# Presentation: 184410

## understanding the systematicsa starting point for a discussion on assessing theoretical and experimental uncertainties and improve data interpretationPaolo Desiati & Teresa MontaruliUW - Madison

**IceCube Collaboration Meeting**
**Berkeley – 19-23 March 2005**

**understanding the systematics****a starting point for a discussion on assessing theoretical and experimental uncertainties and improve data interpretation****Paolo Desiati & Teresa Montaruli****UW - Madison**

## AMANDA is a mature experiment providing results to the scientific community with higher and higher statistics
primary scope of AMANDA is detect HE neutrinos from astrophysical objects
need to well understand measurements outcome with controlled conditions
use of natural atmospheric muon and neutrino flux; but these calibration sources (our main background) are known only to a certain degree
our interest is the high energy response !

Important the understanding of background
reproduce observables within the whole range of values
use consistent simulations for different event types
conditions to separate experimental response from physics input (primary CR spectrum and interaction models - see Teresa’s talk)

Possibily contribute to constrain standard physics to access the unknown sources of HE astrophysics

- motivation

- AMANDA is a mature experiment providing results to the scientific community with higher and higher statistics
- primary scope of AMANDA is detect HE neutrinos from astrophysical objects
- need to well understand measurements outcome with controlled conditions
- use of natural atmospheric muon and neutrino flux; but these *calibration** *sources (our main background) are known only to a certain degree
- our interest is the high energy response !
- Important the understanding of background
- reproduce observables within the whole range of values
- use consistent simulations for different event types
- conditions to separate experimental response from physics input (primary CR spectrum and interaction models - see Teresa’s talk)
- Possibily contribute to constrain *standard* physics to access the *unknown *sources of HE astrophysics

## Theoretical uncertainties (Teresa’s talk)
dominated by primary cosmic ray spectrum and mass composition
influenced by hadronic interaction models
increase with energy

Experimental uncertainties (what usually we quote)
absolute OM sensitivity
ice optical properties
trigger efficiency
reconstruction effects (??)

- A base to start the discussion

- Theoretical uncertainties (Teresa’s talk)
- dominated by primary cosmic ray spectrum and mass composition
- influenced by hadronic interaction models
- increase with energy
- Experimental uncertainties (what usually we quote)
- absolute OM sensitivity
- ice optical properties
- trigger efficiency
*reconstruction effects (??)*

*Use of consistent simulation*

## down-going muon flux

- point-to-point correction:

-  Trigger rate ~ - 25:30% of exp
-  Corrected flux ~ + 30%

- Normalized to first point

- Angular resolution ~2.5o

- Slope ~ muon energy spectrum
-           ~ primary spectrum
-           ~ muon energy loss
-           ~ *detector *(ICRC 2001/03)

## down-going muon flux

- from Dima’s thesis:

- fit CORSIKA with         and using
-  Hörandel primary spectrum (Astrop. Phys. 19(2003),193)
-  QGSJET interaction model

- measurement of primary CR spectral index γ
-  robust measurement against interaction models (DPMJET, HDPM, NEXUS, QJSGET, SIBYLL, VENUS), primary spectra (Wiebel-Sooth, Hörandel) and ice models
-  not strong dependence to primary spectrum and hadronic interaction from muon channel
-  proper choice of experimental conditions
-  *robust* measurement for detector calibration

- γ   = 2.70  0.02
- Φo = 0.106  0.007 cm-2 s-1 sr-1

*****

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## uncertainties from hadronic interactions

- Log10(Eν)

- Fraction

-  K physics higher uncertainties
-  competition between K and π
-  E>100GeV K start dominate
-  importance of K enhanced for νμ
-  muon not strongly affected by K uncertainties

-  prompt physics uncertainties
-  models different by orders of magnitude
-  could be the highest neutrino background for E > 0.1 - 1 PeV

## atmospheric neutrinos

- can we use AMANDA-II atmospheric neutrino data to probe these uncertainties ?

- Log10(Eν)

- E3·dN/dE (cm-2 s-1 sr-1GeV2)

- CORSIKA ~ - 30:50% than NUSIM/Lipari

## the charm of atmospheric neutrinos

- vertical fluxes

- Lipari

- Bartol

- Honda

- fit to CORSIKA

- Vertical neutrino flux

- Log10(Eν)

- fit to Corsika + prompts

- E3·dN/dE (cm-2 s-1 sr-1GeV2)

-  improve energy reconstruction – linearity – resolution (?)
-  extend energy reconstruction at higher energies

-  unfolding uses detector response for a given energy spectrum (Lipari - NUSIM)
-  how robust is the measurement ?
-  energy resolution ~ 0.3 in LogE

*errors (statistics+unfold) still too big, can reduce them with*
-  increase statistics (on the way)
-  use energy bin ~ energy resolution (unfolded error smaller)
-  spectrum unfolded @ different zenith angles

## understanding background
down-going muons as relatively robust probe of detector response
relative rate measurements (seasonal variations, K fraction)
atmospheric neutrino measurement as probe to physics
needs high statistics of high quality data

ice properties
affects hit timing
affects energy estimation for tracks (nhits)
could be main cause of irreproducibility of mis-reconstructed muon tracks

reconstruction algorithms
better reconstruction makes background rejection less dependent on cuts

measure under stable conditions
through-going tracks
maximum distance of OM from track

- understanding background
- down-going muons as relatively robust probe of detector response
- relative rate measurements (seasonal variations, K fraction)
- atmospheric neutrino measurement as probe to physics
- needs high statistics of high quality data
- ice properties
- affects hit timing
- affects energy estimation for tracks (nhits)
- could be main cause of irreproducibility of mis-reconstructed muon tracks
- reconstruction algorithms
- better reconstruction makes background rejection less dependent on cuts
- measure under stable conditions
- through-going tracks
- maximum distance of OM from track

- improve systematics