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  1. Analysis of IMS Data By Ed Sittler CAPS Team Meeting #28 Marseille, France July 26-28, 2004

  2. Analysis of TOF Data • Purpose: • Determine ion composition • Revise calibration parameters for FM • Peak shifts • Peak Amplitudes and widths • Algorithm • Read routine which sums bcycle data in 2D arrays for ST & LEF. • Use highest data rate modes (I.e., 4, 8, 16 kbps). • Set start and stop times. • Store data in file. • Read file from previous step. • Make 2D color spectrograms. • Make line plots of TOF data for specific estep. • Perform non-linear least-squares fit to TOF data. • Can do up to 10 ions. Use line profile parameters as given. Only adjust ion counts. • Presently we can shift the ion peaks manually. We also fit simultaneously to the background. • First do manual fit. • Then do non-linear fit. Compute chisqr. • Plot Results. • Further generalizations being considered.

  3. ST TOF Spectrum 182(23:24) No Shift

  4. ST TOF Spectrum 182(23:24) Shifted

  5. LEF TOF Spectrum 182(23:24)

  6. ST TOF Spectrum 182(18:24) No Shift

  7. ST TOF Spectrum 182(18:24) Shifted

  8. LEF TOF Spectrum 182(18:24)

  9. ST TOF Spectrum 182(18:24) E = 30 eV

  10. LEF TOF Spectrum 182(18:24) E = 30 eV

  11. Summary of TOF Analysis Results • Composition of H+, N+, Water Group Ions & O2+. Detection of H2+ ? • Shift ~ 16 channels (2048) seems to be required. • With no shift H3O+ tends to dominate, C+ more important and N+ less important. • With shift H2O+ tends to dominate, N+ more important and C+ less important. • LEF data shows H+, N+ and Water Group Ions. No C+ seen. O2+ can produce peak near N+ peak, but to shorter TOF. Therefore, less favored by data. Although O2+ is present it is not sufficiently intense. • LEF data set ideal for detection of N+ since O+ has low sensitivity in LEF data (I.e., O+ tends to want electrons). • ST O- peak shoulder to lower TOF not understood. • Electronic peaks? Remove bad data (I.e., revise script pgm).

  12. Analysis of Ion Data • Purpose: • Determine ion composition. • Determine distribution functions of individual ion species. • Compute ion moments. • Study performance of SAM algorithm and Group Tables. • Incorporate revised FM cal parameters into ion analysis. Reconstruct ion counts from data. Required high rate data (4, 8 and 16 kbps) • Procedure • Read level0 data products for period 182(18:24). Sum data for various ion species as function of estep and angular sector. • Study statistical properties and search for systematic effects as function of estep and angular sector. • Plot data in appropriate format. • Apply non-linear fitting algorithm which uses revised FM cal data derived from analysis of TOF data. Reconstruct true ion counts for all ion species. Manually, we have already been doing this.

  13. Summary of Ion Data Analysis • Overall ion data looks good. • But, RTIU problem, especially within inner magnetosphere caused us to throw away a lot of the data. Script program helped but then bad data leaked into results. Localized spikes in data. Needs further work. • Definite anti-correlations with estep between OH+ & H2O+ • Interpolation between esteps may cause systematic effects. • If there were no systematic effects than anti-correlations would go away by summing over many spectra. • Adding nearby esteps may remove some of the problem. • Going to hardware binning should definitely fix the problem. • Summing water group ions together removes anti-correlations. This was expected. • Signal peaks in sector 2 as expected. Enhancement in sector 8 indicated pressure anisotropy effect? • We will next need to apply non-linear fitting algorithm to reconstruct ion counts. Here, we would use revised FM cal parameters from analysis of TOF data.