Simulation Issues for Radio Detection in Ice and Salt Amy Connolly UCLA May 18 th, 2005.

19
Simulation Issues for Radio Detection in Ice and Salt Amy Connolly UCLA May 18 th , 2005

Transcript of Simulation Issues for Radio Detection in Ice and Salt Amy Connolly UCLA May 18 th, 2005.

Simulation Issues for Radio Detection in Ice and Salt

Amy Connolly

UCLA

May 18th, 2005

Overview

• During the past few years, simulations of Askaryan pulses and detection systems have become mature

• Large overlap in people working on simulations from GLUE, ANITA, SalSA

• This talk focuses on the status of simulations developed for ANITA, SalSA

• Lessons learned

Simulations - Overview

• Flavors treated separately

• EM, Had components of shower treated separately for simulating Askaryan signal, proper dN/dy used

• Secondary interactions included

• Weighting accounts for neutrino attenuation through Earth, etc.

• Complementary simulation programs are being developed – this is essential

• Interactions occur uniformly and isotropically in medium – followed by weighting

[P. Gorham]

Anita Simulation• Ray tracing through ice, firn• Fresnel coefficients• Attenuation lengths are depth and

frequency dependent• Include surface slope and roughness• 40 quad ridged horn antennas arranged

in 3 layers: 8,8,16• Bandwidth: 200 MHz-1200 MHz• For now, signal in frequency domain• Measured antenna response

ice

[S. Barwick]

Anita – Ice PropertiesUse measured ice and crust layer thicknesses (model is Crust 2.0 based on seismic data)

Use measured attenuation lengths (frequency dependent)

Rays traced in ice with depth-dependentindex of refraction.

n(z): 1.8 in deep ice 1.3 at surface

Temperature-dependence also included: ~few hundred m in warmest ice (in firn and near bedrock) ~1300 m at mid-depth

[D. Besson]

[P. Gorham]

ANITA - Skymap

For a fixed balloon position, sensitivity on sky takes a sinusoidal shape.A source between -5 and +15 declination would be observable for 5 hrs/day

Over the entire balloon flight, sensitive to entire band between -10 and +15 declination.

Reflected RaysWork by: S. Barwick, F. Wu from University of California at Irvine

TIR

Micro-black holes at ANITA Energies

• Could measure cross section from relative rates of direct (far) to reflected (near).

[S. Barwick]

[S. Barwick &F. Wu]

• ANITA could (possibly) detect events where a signal is reflected from ice-bedrock interface

• Signals suffer from extra attenuation through ice and losses at reflection • At SM ’s, reflected rays not significant

• At large cross-sections, short pathlengths → down-going neutrinos dominate ! reflected rays important

SM

10 100 10001

View more sky!

• HOWEVER, more uncertainty at ice-bedrock interface• For now, assuming 10% attenuation in power at interface• Collaborating with UT group to understand under-ice topologies,

radar reflectivities• Use Brealt code to study interfaces quantitatively

With reflected rays, we could observe a large portion of the sky that we could not otherwise.

Reflected RaysWork by: S. Barwick, F. Wu from University of California at Irvine

SalSA: Benchmark Detector Parameters

• Overburden: 500 m • Detector

– Array starts at 750 m below surface – 10 x 10 string square array, 250 m horiz. separation – 2000 m deep, 12 “nodes”/string, 182 m vert. separation– 12 antennas/node

• Salt extends many atten. lengths from detector walls• Attenuation length: 250 m• Alternating vert., horiz. polarization antennas• Bandwidth: 100-300 MHz• Trigger requires 5/12 antennas on node, 5 nodes to fire:

Vsignal>2.8 £ VRMS

• Index of refraction=2.45• Syst. Temp=450K=300K (salt) + 150K (receiver)

Angular ResolutionWork by: P. Gorham, University of Hawaii

[P. Gorham]

• Performed chi-squared analysis from two hadronic shower event types – Fully contained – Parallel to a face 250 m

outside array• Fit to

– Amplitude of Cerenkov signal

– Polarization• At 8£1016 eV:

– Contained: fraction of deg.– Non-contained: ~1 deg.

• Improves with energy

SalSA Cross Section Measurement

Use Poisson likelihood

cross section can be measured

from distribution

At SM , only 10% of events in sensitive region

Generate distribution from simulation and throw dice for many pseudo-experiments

For experiments w/ 100 events

With 300 events

@1018 eV,

Binning: ~2±

N

cos

<Lmeasint>=400 § 130 km

Comparing Sensitivities

ANITA:45 days

GLUE:120 hrs

RICE: 333 hrs

SalSA(1 year)

• SalSA & ANITA– SalSA lower threshold – ANITA higher V, shorter livetime

• Two independent simulations for each experiment give similar results for ES&S “baseline”– ANITA: handful of events – SalSA: 20 events/year

• Having two MC’s has been essential to:– Learn about the physics of these

systems– Spot bugs– Gain confidence in our results

ES&S “baseline”

How Do We Know Our Simulations Are Correct?

Resolving disagreement in peak at 1£1020 eV

Even if two independent simulations give the same answer, we should assume it is a coincidence until we compare many, many intermediate plots.

ANITA

Depth of Interaction (m) Balloon-to-Interaction Distance (km)

Validating our Simulations (cont)

[P. Gorham]

[S. Hoover]

ANITAProjection of Askaryan signal onto the sky:

Summary

• Simulations of radio detection systems are becoming sophisticated

• ANITA– Reflected rays show promise for detecting high cross

sections, opening up large part of the sky if ice-bedrock interface can be understood

• SALSA– Angular resolution ~fraction of degree for contained

events, 1-2 degrees for external events– Cross section measured at 30% level with 100 events

• Independent simulations are essential • Many intermediate plots necessary to verify

simulation performance

Backup Slides

ANITA

SalSA

GLUE

RICE

Impact of Salt Properties

• Track length L– X0

ice=43 cm, X0salt=10.3 cm ! Expect

Lsalt/Lice=0.26. Simulations show 0.34.

• Cerenkov index of refraction factor

• Cerenkov threshold

• Critical energy

• Coherence

• Angular scaling

Secondary Interactions• Generate from

MMC for each flavor, interaction type

• From MMC, also retrieve multiplicity of each type of sec. interaction

• Force neutrinos in our simulation to obey these distributions

• For now, consider interaction (primary or secondary) which contributes the strongest signal

• Critical for flavor ID

Example Probability Distribution from MMC for muon brem. showers

P. Miocinovic