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FlippingRatioCorrectionMD dialog.
Table of Contents
Creates MDEvent workspaces with polarization flipping ratio corrections.The polarization might be angle dependent.
| Name | Direction | Type | Default | Description |
|---|---|---|---|---|
| InputWorkspace | Input | MDEventWorkspace | Mandatory | An input MDEventWorkspace. |
| FlippingRatio | Input | string | Mandatory | Formula to define the flipping ratio. It can depend on the variables in the list of sample logs defined below |
| SampleLogs | Input | str list | Comma separated list of sample logs that can appear in the formula for flipping ratio | |
| OutputWorkspace1 | Output | Workspace | Mandatory | Output workspace 1. Equal to Input workspace multiplied by FR/(FR-1). |
| OutputWorkspace2 | Output | Workspace | Mandatory | Output workspace 2. Equal to Input workspace multiplied by 1/(FR-1). |
Measurements using polarized neutrons can be used to identify magnetic and nuclear contribution. In the case of coherent scattering, nuclear spins generally do not change the spin polarization of the neutrons (non spin flip scattering). For magnetic scattering, the magnetization parallel to the neutron spin direction produces non spin flip scattering, while magnetization perpendicular to the spin direction will flip the neutron spin.
When measuring spin flip and non spin flip cross sections, the finite capabilities of the instrument will allow a certain percentage of the other component to leak through. This is denoted by the flipping ratio \(F\). Using subscript “m” for measured and “c” for corrected, the corrected intensities for the spin flip (SF) and non spin flip (NSF) scattering are given by [1]:
Given a multidimensional event workspace, this algorithm will output the workspace where events
are multiplied by \(F/(F-1)\) (in OutputWorkspace1) and by \(1/(F-1)\) (in OutputWorkspace2).
Note however that the flipping ratio might be angle dependent. For example, in the case of
type II superconductors, the flux lattice will depolarize the neutrons differently, depending
on the orientation of the neutron beam with respect to the superconducting planes. In this case
one must use a formula that would use a different flipping ratio for each neutron, that
depends on a goniometer angle. Assuming that we have a log value omega for the sample rotation,
the flipping ratio might be described by something like [2]:
The MD event workspaces label each MDEvent with the experiment info number. The time averaged log
value for omega is read from each experiment info, the flipping ratio is calculated from the
user provided formula, and the corrected workspaces are computed.
For the parsing of the formula, the algorithm uses muparser. Once can use any of the implemented functions. The constant “pi” can be used in the formula. Use “_e” for the base of natural logarithms.
| [1] | O Schärpf, Experience with spin analysis on a time-of-flight multidetectorscatteringinstrument, In Neutron scattering in the nineties, Proceedings of the IAEA Conference, Jülich 85-97 (1985) https://inis.iaea.org/collection/NCLCollectionStore/_Public/16/076/16076003.pdf |
| [2] | Igor A Zaliznyak et al, Polarized neutron scattering on HYSPEC: the HYbrid SPECtrometer at SNS, J. Phys.: Conf. Ser. 862 012030 (2017) doi:10.1088/1742-6596/862/1/012030 |
Example - FlippingRatioCorrectionMD
# Fake an md workspace
CreateMDWorkspace(Dimensions=2, EventType='MDEvent', Extents='-5,5,-5,5', Names='A,B', Units='a,a' ,OutputWorkspace='mde1')
AddSampleLog(Workspace='mde1', LogName='param', LogText='0.', LogType='Number', NumberType='Double')
FakeMDEventData(InputWorkspace='mde1', PeakParams='100,-2,-2,0.1')
CreateMDWorkspace(Dimensions=2, EventType='MDEvent', Extents='-5,5,-5,5', Names='A,B', Units='a,a',OutputWorkspace='mde2')
AddSampleLog(Workspace='mde2', LogName='param', LogText='90.', LogType='Number', NumberType='Double')
FakeMDEventData(InputWorkspace='mde2', PeakParams='100,2,2,0.1')
MergeMD(InputWorkspaces='mde1,mde2', OutputWorkspace='merged')
# Calculate flipping ratio corrections
FlippingRatioCorrectionMD(InputWorkspace='merged',
FlippingRatio='10+5*sin(param*pi/180)',
SampleLogs='param',
OutputWorkspace1='correctionFoFm1',
OutputWorkspace2='correction1oFm1')
# Bin data and extract intensities
BinMD(InputWorkspace='correctionFoFm1', AlignedDim0='A,-5,5,2', AlignedDim1='B,-5,5,2', OutputWorkspace='correctionFoFm1_histo')
peak1_FoFm1=mtd['correctionFoFm1_histo'].getSignalArray()[0,0]
peak2_FoFm1=mtd['correctionFoFm1_histo'].getSignalArray()[1,1]
BinMD(InputWorkspace='correction1oFm1', AlignedDim0='A,-5,5,2', AlignedDim1='B,-5,5,2', OutputWorkspace='correction1oFm1_histo')
peak1_1oFm1=mtd['correction1oFm1_histo'].getSignalArray()[0,0]
peak2_1oFm1=mtd['correction1oFm1_histo'].getSignalArray()[1,1]
print("{:>17} Peak1 Peak2".format(' '))
print("{:>17} {:8.3f} {:8.3f}".format('Original',100,100))
print("{:>17} {:8.3f} {:8.3f}".format('F',10,15))
print("{:>17} {:8.3f} {:8.3f}".format('F/(F-1)',10./9.,15/14.))
print("{:>17} {:8.3f} {:8.3f}".format('Corrected F/(F-1)',peak1_FoFm1,peak2_FoFm1))
print("{:>17} {:8.3f} {:8.3f}".format('1/(F-1)',1./9.,1/14.))
print("{:>17} {:8.3f} {:8.3f}".format('Corrected 1/(F-1)',peak1_1oFm1,peak2_1oFm1))
Output:
Peak1 Peak2
Original 100.000 100.000
F 10.000 15.000
F/(F-1) 1.111 1.071
Corrected F/(F-1) 111.111 107.143
1/(F-1) 0.111 0.071
Corrected 1/(F-1) 11.111 7.143
Categories: AlgorithmIndex | MDAlgorithms\Transforms
C++ header: FlippingRatioCorrectionMD.h (last modified: 2021-03-31)
C++ source: FlippingRatioCorrectionMD.cpp (last modified: 2021-04-20)