## Neutron scattering data analysis 1990: invited and contributed papers from the Conference on Neutron Scattering Data Analysis held at the Rutherford Appleton Laboratory, Chilton, 14-16 March 1990 |

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Page 48

We can summarise this inference with a conditional probability distribution; for

the case of a neutron scattering experiment, for example, this would be prob[

the ...

We can summarise this inference with a conditional probability distribution; for

the case of a neutron scattering experiment, for example, this would be prob[

**Scattering law**/ Data, Experimental setup], where "/" means "given". The largerthe ...

Page 49

In neutron scattering we may say that we wish to know the

sample, but how is the

that

In neutron scattering we may say that we wish to know the

**scattering law**of oursample, but how is the

**scattering law**to be described? If we know (or assume)that

**scattering law**consists of a single Lorentzian, for example, then we have a ...Page 53

The eigenfunctions define the natural hypothesis space for our problem because

they represent the properties of the

independently of each other. If we write the

of ...

The eigenfunctions define the natural hypothesis space for our problem because

they represent the properties of the

**scattering law**which can be estimatedindependently of each other. If we write the

**scattering law**as a linear combinationof ...

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Acta Cryst algorithm applications approach atoms Bayesian beam Bragg peaks calculated configuration constraints coordinates corresponding cost function cross-section crystallographic Data Anal data analysis data set defined detector bank determined diffraction data diffractometer elastic scattering energy error bars example experiment experimental Figure Fourier transform Gaussian GENIE GENIE-V3 histogram inelastic instrument intensity interpolation inverse ISIS least squares likelihood function magnetic structure magnetisation density Markov chain matrix MaxEnt Reconstruction Maximum Entropy McGreevy measured method molecular Monte Carlo neutron diffraction neutron scattering normalisation normalization obtained optimisation optimization problems parameters Patterson map performed Phys plot positive powder diffraction presented at Neutron prior probability procedure quasielastic refinement reflectivity data resolution function ROTAX Rutherford Appleton Laboratory sample scan scattering law shown simulated annealing single crystal solution spectra spectrometer spectrum statistical structure factor symmetry technique temperature time-of-flight UNIRAS unit cell vanadium vector wavelength workspace