Group3: Difference between revisions

From canSAS
(Replaced content with "GROUP C NOTES")
No edit summary
 
(3 intermediate revisions by 2 users not shown)
Line 1: Line 1:
GROUP C NOTES
NOTES FOR GROUP C
 
Grethe Jensen Leading
 
 
We discussed approaches for considering multiple scattering effects. The following points were identified
 
1. A flag signalling significant multiple scattering would be good for both data reduction software (to allow for immediate action!) and data analysis/modelling software.
* Requires data on absolute scale, together with values for wavelength and sample path length – or a well-determined measured SAS transmission. Good example of a situation where wavelength and path length would be nice to have accessible in the final reduced data file.
* Could identify the maximum scattering order that should be included in the data analysis – or suggest a proper sample path length or wavelength that would be required to exclude significant multiple scattering effects.
* Could suggest measurements for a small series of wavelengths/path lengths/contrasts, to identify features influenced by multiple scattering. These data could/should (?) be published with the data to address/prove the presence/non-presence of these effects.
 
 
2. Including multiple scattering effects in the data analysis
* Relevant for both SAS in transmission geometry and for GISAS.
* Include calculation of higher order scattering functions in model calculations and parameter optimization loop? By 2D convolution or MC simulations?
* To speed calculations up, one might consider: Only include the relevant scattering orders, starting out with ‘just’ including second order scattering, only updating higher order scattering functions every N steps in the optimization, ...

Latest revision as of 22:44, 8 June 2017

NOTES FOR GROUP C

Grethe Jensen Leading


We discussed approaches for considering multiple scattering effects. The following points were identified

1. A flag signalling significant multiple scattering would be good for both data reduction software (to allow for immediate action!) and data analysis/modelling software.

  • Requires data on absolute scale, together with values for wavelength and sample path length – or a well-determined measured SAS transmission. Good example of a situation where wavelength and path length would be nice to have accessible in the final reduced data file.
  • Could identify the maximum scattering order that should be included in the data analysis – or suggest a proper sample path length or wavelength that would be required to exclude significant multiple scattering effects.
  • Could suggest measurements for a small series of wavelengths/path lengths/contrasts, to identify features influenced by multiple scattering. These data could/should (?) be published with the data to address/prove the presence/non-presence of these effects.


2. Including multiple scattering effects in the data analysis

  • Relevant for both SAS in transmission geometry and for GISAS.
  • Include calculation of higher order scattering functions in model calculations and parameter optimization loop? By 2D convolution or MC simulations?
  • To speed calculations up, one might consider: Only include the relevant scattering orders, starting out with ‘just’ including second order scattering, only updating higher order scattering functions every N steps in the optimization, ...