Kate Husband Cambridge University UK Development of an

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Kate Husband Cambridge University, UK Development of an Online Filter for Selection of Cascade-like

Kate Husband Cambridge University, UK Development of an Online Filter for Selection of Cascade-like Events in Ice. Cube Supervisor: Eike Middell

Signals • Ice. Cube looks for high-energy astrophysical n • E. g. from supernova

Signals • Ice. Cube looks for high-energy astrophysical n • E. g. from supernova remnants • Also detects atmospheric n’s • Primary cosmic rays produce muons which is the main background to Ice. Cube.

Ice. Cube • 1 km 3 high energy, n telescope at S Pole •

Ice. Cube • 1 km 3 high energy, n telescope at S Pole • Contains DOMs with PMT which record amp. & time of photons • Ice contains dust particles and air bubbles so photons scatter

Events: Cascade-like • n interact through weak force only • Quarks produce cascade of

Events: Cascade-like • n interact through weak force only • Quarks produce cascade of Cherenkov photons • Photon intensity decays rapidly • Muons can also knock out e- resulting in em cascade

Events: Track-like • Muons move close to c • Don’t lose much energy in

Events: Track-like • Muons move close to c • Don’t lose much energy in producing Cherenkov light • Only arrive from above detector as decay quickly • Hence long straight downwards tracks

Multi- Vs. Single-Peak • If triggered, DOM records continuous waveform 1. Try and fit

Multi- Vs. Single-Peak • If triggered, DOM records continuous waveform 1. Try and fit pulses of different times and amp. into waveform = MULTI-PEAK (mp) OR 2. Find no. of photons from total amplitude and give all photons the same time = SINGLEPEAK (sp)

AIMs • Online filter must separate multiple background events from signal within constraints. •

AIMs • Online filter must separate multiple background events from signal within constraints. • Constraints: limited bandwidth & CPU power • Aim to improve efficiency by looking at possible new singlepeak cut variables

A. To. I • Each DOM is given a mass proportional to amount of

A. To. I • Each DOM is given a mass proportional to amount of charge it records • Centre of gravity of distribution is used as approx. to interaction vertex • Good cut variable as spherical n ~0. 3, tracks ~0.

B. Line. Fit Velocity • Fits a straight line through triggered DOMs • Var(time)

B. Line. Fit Velocity • Fits a straight line through triggered DOMs • Var(time) is not a good cut variable

 • Charge weighting doesn’t increase separation

• Charge weighting doesn’t increase separation

C: Cumulative Charge • Cumulative sum of charge of each DOM over time •

C: Cumulative Charge • Cumulative sum of charge of each DOM over time • Take time at x% of total charge to get tx • Single-peak

 • ~t 75 found to give largest separation

• ~t 75 found to give largest separation

D: Charge Propagation • Decay of chargeenergy ratio different • Total charge ≈energy and

D: Charge Propagation • Decay of chargeenergy ratio different • Total charge ≈energy and centre of gravity ≈ interaction vertex • Single-peak

 • Mean on new axis for each event weighted with distance is new

• Mean on new axis for each event weighted with distance is new variable: MCD

Optimization • Previous filter: vel+To. I (mp): 71. 7% ne (smaller detector) • New

Optimization • Previous filter: vel+To. I (mp): 71. 7% ne (smaller detector) • New filter: MCD+To. I (sp): 73% ne

Energy Efficiency • New filter is slightly better at low energies • Blue: vel

Energy Efficiency • New filter is slightly better at low energies • Blue: vel +To. I (mp), Red: MCD+To. I (sp)

Summary • Line. Fit velocity cannot be replaced by variance of time • New

Summary • Line. Fit velocity cannot be replaced by variance of time • New single-peak cut variables: t 75 and MCD • New filter suggested with MCD>61. 4, To. I>0. 14 passing 73. 0% sig. for 1% bkd. • New filter has slightly better low energy efficiency.