Instrumental effects on HED anisotropy measurements

1. Instrumental effects on HED anisotropy measurements Oskari Saloniemi, SRL workshop 14.8.2007

2. particle detector HED • Basic data products are: • proton spectra from 10-140 MeV • with 1 minute time resolution. • directional distributions of protons • (3-5 channels) and Helium (3-1 • channels) • pulse height data from the heavier • nuclei • directional measurements provide • THE best view of the particle flux • intensity environment the detector • was in. • Particle detectors count particles. • It is the user’s responsibility to • remove the instrument’s effects • from the data to deduce the particle • intensities • - Could the directional measure- • ments also give the best view of • the instrument effects?

3. Main instrument effects affecting directional measurements • The (directional) geometric factor • function of energy (stopping layer) and direction • broad energy channels or very steep spectrum induce spectral variations of geometric factor and geometrical midpoint of angular bins • wide angular bins induce dynamic variations as a function of anisotropy • On board software errors and rejection logics • uppermost detection layer susceptible for double hits caused by high ”noise” from energetic electrons and protons. • hardware failure

5. ERNE/HEDviewcone

6. correction coefficient due to anisotropy 2nd of May 1998 Protons 17-22 MeV

7. Binning error correction particles from sectors 1,7,13 and 19 are saved in the next sectors

13. approach 1 • Calculate the ”acceptance” of each directional bin from the data itself -> sum up huge amounts of measurements from long enough periods and normalize the result to form a probability distribution. • consistent anisotropy will be lost, but short term anisotropy should be unaffected. • acceptance should contain all instrumental effects, since it is determined from the data itself. • the first approach was to exclude all anisotropic measurements and to define acceptance to 90 different spectral indeces. -> decent results and one doctoral thesis

14. approach 2 • Not all dynamic effects could be explained by the spectral differences. • New acceptance matrices were formed as a function of total intensity in the anisotropy channels. All measurements were accepted. • works well on most events. • still used today.

15. acceptance approach

16. approach 3 • Acceptance matrices formed as a function of sample rate divider (SRD) value • SRD [1-128] is used by the hardware to restrict (divide) the amount of lower priority (3) protons (and electrons) further in the data analysis. • SRD can indicate situations where the instrument is susceptible to double hits, which eventually are suspected of causing the sometimes observed overload situation

21. Solution • define a total intensity correction coefficient for each ring. • define 90 degree and 180 degree symmetry from the matrices and cancel them out with proper periodic functions.

23. after the corrections original acceptance matrix correction matrix factor of the previos two

24. after the corrections original acceptance matrix correction matrix factor of the previos two

25. but OSS 2.50 (4.7.2001->)... original acceptance matrix correction matrix factor of the previos two

26. but OSS 2.50 (4.7.2001->)... original acceptance matrix correction matrix factor of the previos two

29. open questions future work • What situations (spectral and intensity) most cause the phenomena seen in the instrument response? • What is the nature of the response change for the underlying anisotropy? Can it be recovered using simple statistical correction factor? • instrumental response to high background intensities through simulations. • to study the instrument behaviour as a function of high background (SRD?) and spectra by factoring out a more realistic geometrical factor determined by the GEANT simulations from the acceptance matrices. • proper acceptance determined for all periods of measurements