1 / 12

Rodín Porrata

New Vertex Location and Energy Reconstruction Techniques Using the Arrival Information of All Measured Photons. Rodín Porrata. UC Berkeley, Price Group. New Vertex and Energy Reconstruction Techniques for Cascades. Requirements: Self-contained (no external minimizer) -> usable online

cherie
Download Presentation

Rodín Porrata

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. New Vertex Location and Energy Reconstruction TechniquesUsing the Arrival Information of All Measured Photons Rodín Porrata UC Berkeley, Price Group

  2. New Vertex and Energy Reconstruction Techniques for Cascades • Requirements: • Self-contained (no external minimizer) -> usable online • Very accurate vertex and energy reco -> usable offline Some history: Spiesberger -> Vanderbrouke -> Porrata • Spiesberger: Passive acoustic location of marine fauna. • -> Basic SVD localization algorithm (assumes no delays). • Vanderbrouke: Use to locate EHE GZK acoustic signals? • Porrata: Adapt for use in environments where signal is scattered, i.e., photons from cascades scattered by dust in ice. • Energy reconstruction obvious: • if allowed to use all photon info, e.g., DOMs, TWR, • if have very good vertex location.

  3. Spiesberger’s SVD Porpoise Location Algorithm For each of N hit OMs define the following N spherical wave equations: Nonlinear in parameters. The ti are time differences. The ti are the measured times assuming no scattering. The Ti are unscattered light propagation times. Where: Subtract the first equation from the rest, get N-1 paraboloid equations: These equations are linear in the 4 unknowns.

  4. Spiesberger’s SVD Porpoise Location Algorithm Have N-1 linear paraboloid equations and 4 unknowns. Define: Where: Perform the singular value decomposition of A: Then the solution is given by: As is, must use time of first hit only, as estimate of unscattered light propagation time.

  5. Method of Energy Reconstruction Product of Poisson probabilities for seeing exactly n photoelectrons. mi = average number of photoelectrons expected. ni = measured number of photoelectrons. Take the derivative w.r.t. the energy. Set to zero. Solve. Do not need 4800 separate quantities to calculate. One scalar vs position only! The solution is trivial provided that (we can really count photoelectrons): DAQ response is linear. Feature extraction of waveforms is linear. Have a good model of photon propagation and through the ice. Have already obtained an accurate vertex location.

  6. Simulation Simulated 1000 isotropic point source events at 100 TeV in dusty ice with a 4800 OM Ice3 array. • Loop over events: • Obtain event position and energy • Loop over OMs: Calculate number of photoelectrons, m(d, q), according to diffusive approximation. Poisson distribute m to obtain nhits at OM. Distribute in time taking into account: • Un-scattered light propagation time, and • Gamma distribution provides time delays due to scattering. • Write out hits • Write out Event End loop • Vfid = 4.07 km3, • Vtrig (M=1) = 1.83 km3, These studies indicative only!

  7. Testing the Algorithm in Dust Free Ice • Cuts: • Ndir > 10 • Chi2 < 10 • Results (are ludicrous): • Veff = 1.5 km3 • sE = 0.011 in log(E) • Fom = 136.0

  8. Testing the Algorithm Blind Dusty ice. Cut: rfit < 1 km • Results (so-so): • Veff = 2.28 km3 • sE = 0.16 in log(E) • Fom = 14.25

  9. Taking into Account the Distribution of the Photon Arrival Times in Dusty Ice Weight rows of A with: Use variance of distribution and number of hits to estimate delay from direct time. Subtract off estimated delay from measured time of first hit. Require at least 4 photons to determine variance of the distribution.

  10. Taking into Account the Distribution of the Photon Arrival Times in Dusty Ice • Weighted A • Cuts: • Concentration > 25 • rfit < 600 m • Results: • Veff = 0.79 km3 • sE = 0.11 in log(E) • Fom = 7.18

  11. Taking into Account the Distribution of the Photon Arrival Times in Dusty Ice • Weighted A • Subtracted estimated delay time. • Ng > 4 • Concentration > 20 • rfit < 600 m Energy Resolution = 0.074 • Results: • Veff = 1.07 km3 • sE = 0.074 in log(E) • Fom = 14.5 R. Porrata, Berkeley, March 2005

  12. Conclusions, Caveats and Outlook • Will reach energy reconstruction specifications at “first guess”! • Have not yet taken into account direction. Working on this. • Method strongly depends on Ice3’s advertised ability to make sense of waveform information! Seckel’s method looks like it will produce the most physically meaningful photon times. • Plan to code into IceRec software. • Expect improvements as photon propagation is better modeled (see my earlier talk on photon propagation). • Expect improvements when method is iterated.

More Related