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Simulation Issues for Radio Detection in Ice and Salt

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

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Simulation Issues for Radio Detection in Ice and Salt

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

  2. 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

  3. Simulations - Overview • Complementary simulation programs are being developed – this is essential • Interactions occur uniformly and isotropically in medium – followed by weighting • 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. [P. Gorham]

  4. n ice 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 [S. Barwick]

  5. Anita – Ice Properties Use measured ice and crust layer thicknesses (model is Crust 2.0 based on seismic data) n(z): 1.8 in deep ice 1.3 at surface [D. Besson] Rays traced in ice with depth-dependent index of refraction. [P. Gorham] Use measured attenuation lengths (frequency dependent) Temperature-dependence also included: ~few hundred m in warmest ice (in firn and near bedrock) ~1300 m at mid-depth

  6. 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.

  7. n TIR Reflected RaysWork by: S. Barwick, F. Wu from University of California at Irvine • ANITA could (possibly) detect events where a signal is reflected from ice-bedrock interface • At large cross-sections, short pathlengths → down-going neutrinos dominate ! reflected rays important [S. Barwick & F. Wu] Micro-black holes at ANITA Energies [S. Barwick] • Signals suffer from extra attenuation through ice and losses at reflection • At SM  ’s, reflected rays not significant 1 100 10 1000 /SM • Could measure cross section from relative rates of direct (far) to reflected (near).

  8. View more sky! Reflected RaysWork by: S. Barwick, F. Wu from University of California at Irvine With reflected rays, we could observe a large portion of the sky that we could not otherwise. • 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

  9. 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)

  10. Angular ResolutionWork by: P. Gorham, University of Hawaii • 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 [P. Gorham]

  11. SalSA Cross Section Measurement N cross section can be measured from distribution cos  Generate distribution from simulation and throw dice for many pseudo-experiments Binning: ~2± @1018 eV, For experiments w/ 100 events <Lmeasint>=400 § 130 km With 300 events At SM  , only 10% of events in sensitive region Use Poisson likelihood

  12. Comparing Sensitivities • 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 RICE: 333 hrs GLUE: 120 hrs SalSA (1 year) ANITA: 45 days ES&S “baseline”

  13. How Do We Know Our Simulations Are Correct? Even if two independent simulations give the same answer, we should assume it is a coincidence until we compare many, many intermediate plots. ANITA Resolving disagreement in peak at 1£1020 eV Depth of Interaction (m) Balloon-to-Interaction Distance (km)

  14. Validating our Simulations (cont) ANITA Projection of Askaryan signal onto the sky: [S. Hoover] [P. Gorham]

  15. 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

  16. Backup Slides

  17. ANITA SalSA GLUE RICE

  18. Impact of Salt Properties • Track length L • X0ice=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

  19. 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

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