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# VesuvioAnalysis v1¶

## Properties¶

Name

Direction

Type

Default

Description

AnalysisMode

Input

string

In the first case, all the algorithm is run. In the second case, the data are not re-loaded, and only the TOF and y-scaling bits are run. In the third case, only the y-scaling final analysis is run. In the fourth case, the data is re-loaded and the TOF bits are run. In the fifth case, only the TOF bits are run. Allowed values: [‘LoadReduceAnalyse’, ‘ReduceAnalyse’, ‘Analyse’, ‘LoadReduce’, ‘Reduce’]

IPFile

Input

string

Mandatory

The instrument parameter file. Allowed values: [‘par’]

NumberOfIterations

Input

number

2

Number of time the reduction is reiterated. Allowed values: [‘0’, ‘1’, ‘2’, ‘3’, ‘4’]

OutputName

Input

string

polyethylene

The base name for the outputs.

Runs

Input

string

38898-38906

List of Vesuvio run numbers (e.g. 20934-20937, 30924)

Spectra

Input

long list

135,182

Range of spectra to be analysed (first, last). Please note that spectra with a number lower than 135 are treated as back scattering spectra and are therefore not considered valid input as this algorithm is only for forward scattering data.

TOFRangeVector

Input

dbl list

110,1.5,460

In micro seconds (lower bound, binning, upper bound).

TransmissionGuess

Input

number

0.9174

A number from 0 to 1 to represent the experimental transmission value of the sample for epithermal neutrons. This value is used for the multiple scattering corrections. If 1, the multiple scattering correction is not run.

MultipleScatteringOrder

Input

number

2

Order of multiple scattering events in MC simultation. Allowed values: [‘1’, ‘2’, ‘3’, ‘4’]

MonteCarloEvents

Input

number

1000000

Number of events for MC multiple scattering simulation.

ComptonProfile

Input

TableWorkspace

Mandatory

Table for Compton profiles

ConstraintsProfile

Input

TableWorkspace

Table with LHS and RHS element of constraint on intensities of element peaks. A constraint can only be set when there are at least two elements in the ComptonProfile. For each constraint the ratio of the first to second intensities, each equal to atom stoichiometry times bound scattering cross section is defined in the column ScatteringCrossSection. Simple arithmetic can be included but the result may be rounded. The column State allows the values ‘eq’ and ‘ineq’.

Input

long list

SubtractResonancesFunction

Input

string

Function for resonance subtraction. Empty means no subtraction.

YSpaceFitFunctionTies

Input

string

The TOF spectra are subtracted by all the fitted profiles about the first element specified in the elements string. Then such spectra are converted to the Y space of the first element (using the ConvertToYSPace algorithm). The spectra are summed together and symmetrised. A fit on the resulting spectrum is performed using a Gauss Hermite function up to the sixth order.

## Description¶

This algorithm allows the loading, reduction, and analysis of forward scattering data obtained using Deep Inelastic Neutron Scattering (DINS), also referred to as Neutron Compton Scattering (NCS), at the VESUVIO spectrometer. The algorithm has been developed by the VESUVIO Instrument Scientists, Giovanni Romanelli and Matthew Krzystyniak. A previous version of the algorithm was described in: G. Romanelli et al.; Journal of Physics: Conf. Series 1055 (2018) 012016.

DINS allows the direct measurements of nuclear kinetic energies and momentum distributions, thus accessing the importance of nuclear quantum effects in condensed-matter systems, as well as the degree of anisotropy and anharmonicity in the local potentials affecting nuclei. DINS data appear as a collection of mass-resolved peaks (Neutron Compton Profiles, NCPs), that are fitted independently in the time-of-flight spectra, using the formalism of the Impulse Approximation and the y-scaling introduced by G. B. West.

Additional information about DINS theory and applications can be found in the recent review: C. Andreani et al., Advances in Physics, 66 (2017) 1-73

Additional information on the geometry and operations of the VESUVIO spectrometer can be found in J. Mayers and G. Reiter, Measurement Science and Technology, 23 (2012) 045902 G. Romanelli et al., Measurement Science and Technology, 28 (2017), 095501

### Warning¶

This algorithm is still in development. If you encounter any problems please contact the Mantid team and the Vesuvio scientists.

## Usage:¶

Example: Analysis of polyethylene

# create table of elements
table = CreateEmptyTableWorkspace()
table.addRow(['H', 1.0079,  0.,1.,9.9e9,  3.,  4.5,  6.,  -1.5, 0., 0.5])
table.addRow(['C', 12.0,    0.,1.,9.9e9,  10., 15.5, 30., -1.5, 0., 0.5])

# create table of constraints
constraints = CreateEmptyTableWorkspace()

VesuvioAnalysis(IPFile = "ip2018.par", ComptonProfile = table, AnalysisMode = "LoadReduceAnalyse",
NumberOfIterations = 2, OutputName = "polyethylene", Runs = "38898-38906", TOFRangeVector = [110.,1.5,460.],
Spectra = [135,182], MonteCarloEvents = 1e3, ConstraintsProfile = constraints, SpectraToBeMasked = [173,174,181],
SubtractResonancesFunction = 'name=Voigt,LorentzAmp=1.,LorentzPos=284.131,LorentzFWHM=2,GaussianFWHM=3;',
YSpaceFitFunctionTies = "(c6=0., c4=0.)")

fit_results = mtd["polyethylene_H_JoY_sym_Parameters"]

print("variable", "value")
for row in range(fit_results.rowCount()):
print(fit_results.column(0)[row],"{:.3f}".format(fit_results.column(1)[row]))


Output:

variable value
f1.sigma1 4.939
f1.c4 0.000
f1.c6 0.000
f1.A 0.080
f1.B0 0.000
Cost function value ...


Categories: AlgorithmIndex | Inelastic\Indirect\Vesuvio

## Source¶

Python: VesuvioAnalysis.py