A program to determine hyperfine tensors from EPR or ENDOR single crystal data is described. The variation of hyperfine interaction upon rotating the crystal with respect to the static field is studied by a least-squares algorithm which affords various weighting methods. These take into account the fact that the model equations are not linear in the variables, so that equal measurement errors affect the calculation to different extents. An iterative procedure is available which accounts for experimental uncertainty in both dependent and independent variables. Fitting parameters are then cast into a matrix form of tensors. These are diagonalized by a Householder transform followed by application of Sturm bisection algorithm. This procedure is very accurate and matrix inversion is not needed. Extensive error analysis is performed and error propagation is followed throughout the calculation. The standard error of tensor eigenvalues and eigenvectors is estimated. TENSOR features a friendly menu-guided user interface, a data editor, a file manager and routines for printing and plotting.
TENSOR: a program to extract hyperfine tensors from single crystal EPR and ENDOR data / A.Ponti, C.Oliva. - 16:3(1992), pp. 233-238.
TENSOR: a program to extract hyperfine tensors from single crystal EPR and ENDOR data
C.OlivaUltimo
1992
Abstract
A program to determine hyperfine tensors from EPR or ENDOR single crystal data is described. The variation of hyperfine interaction upon rotating the crystal with respect to the static field is studied by a least-squares algorithm which affords various weighting methods. These take into account the fact that the model equations are not linear in the variables, so that equal measurement errors affect the calculation to different extents. An iterative procedure is available which accounts for experimental uncertainty in both dependent and independent variables. Fitting parameters are then cast into a matrix form of tensors. These are diagonalized by a Householder transform followed by application of Sturm bisection algorithm. This procedure is very accurate and matrix inversion is not needed. Extensive error analysis is performed and error propagation is followed throughout the calculation. The standard error of tensor eigenvalues and eigenvectors is estimated. TENSOR features a friendly menu-guided user interface, a data editor, a file manager and routines for printing and plotting.Pubblicazioni consigliate
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