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FDS: parameter space searches B. Allen, Y. Itoh, M.A. Papa, X. Siemens AEI , UWM

FDS: parameter space searches B. Allen, Y. Itoh, M.A. Papa, X. Siemens AEI , UWM. Moving towards a hierarchical search. We now expand the coherent search to inspect a larger parameter space. (At the same time the incoherent stage is being developed and tested).

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FDS: parameter space searches B. Allen, Y. Itoh, M.A. Papa, X. Siemens AEI , UWM

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  1. FDS: parameter space searches B. Allen, Y. Itoh, M.A. Papa, X. Siemens AEI , UWM • Moving towards a hierarchical search. We now expand the coherent search to inspect a larger parameter space. (At the same time the incoherent stage is being developed and tested). • We will pursue two types of searches: • short observation time (~1/2 day), no spin-down params, wide band (~300 Hz) centered at ~ 300 Hz, all sky search • perhaps longer observation time, 1 spin-down param, small area search (galactic plane/SNRs), small bands. There is a delicate trade-off between sensitivity, observation time (spanned and effective), resolution in parameter space and class of sources that one chooses to target. Calibration info needed to finalize choice  SC03 demo. 1000CPUs across the grid for ~ 1 month. Note: different choices could be made in order to produce the best ULs. • entire S2 observation time, wide frequency band (200 Hz), in the vicinity of the galactic center. 1000 CPUs across the LSC grid for ~ 1 month: • www.lsc-group.phys.uwm.edu/lscdatagrid/details.html • AEI (Merlin, 360 CPUs), Birmingham (Tsunami, 200 CPUs), • Caltech (200 CPUs), Cardiff (120 CPUs), ISI (35 CPUs), • UWM (Medusa, 300 CPUs) LSC meeting, Hannover, Aug 2003

  2. Modifications wrt the S1 analysis • inserted loop to search over different sky locations and spin-down parameters • introduced more robust Sn estimation technique, based on running median (running median code by S. Mohanty) • found the bias correction factor for the expectation value of a running median from an exponential distribution as a function of window size (B. Krishnan) LSC meeting, Hannover, Aug 2003

  3. Outlier due to large disturbance

  4. Large outliers The good news: this, like all of the large outliers that we have seen, does not have the F(f0) shape that one would expect from a real signal. The half-height width from a signal is no more than ~ 7 bins wide and the peak is very sharp – no structure like this. So we will implement a test (chi-square test) to discard large outliers based on this principle.

  5. threshold Df0 Large outliers • Identify large outlier clusters For every significant cluster that is identified a line is written to a file (eventually to a DB): f0 maxa d N m s 2Fmax • Test whether they can be discarded

  6. Pipeline

  7. Fstat shape test example

  8. First results of c2 test (Y. Itoh)

  9. Pipeline

  10. consistent with expectations. h095% ~ few 10-23 2Fmax values in 0.5 Hz bands • 2Fmax value in a 0.5 Hz and searching ~ 15*15 deg around GC, 10h (H1 data) • after c2 test these most of these values will become smaller • from each of these values an h095% UL will be derived

  11. Schedule • We could not produce complete the analysis due to severe failures of our computing facilities in the past month. • Expect to have these within the next month – at GWDAW we would like to present methods rather than preliminary results.

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