Sellmeier fits with linear regression; multiple data sets; dispersion formulas for helium
- 15 September 1983
- journal article
- Published by Optica Publishing Group in Applied Optics
- Vol. 22 (18) , 2906-2913
- https://doi.org/10.1364/ao.22.002906
Abstract
Linear regression, combined with search over nonlinear parameters, is useful in fitting Sellmeier formulas to dispersion data. A special advantage accrues in fitting several sets of data to one formula: linear regression permits systematic normalization to a common absolute value. Rational procedures are discussed also for weighting of data sets of unequal precision. The fitting of common formulas to six sets of data on helium, for wavelengths from 0.09 to 2 μm, illustrates the various procedures.Keywords
This publication has 10 references indexed in Scilit:
- Refractivities of , He, , CO, and Kr for nmPhysical Review A, 1976
- Refractive indices, Verdet constants, and Polarizabilities of the inert gasesAtomic Data and Nuclear Data Tables, 1974
- Refractive index of He in the region 920–1910 ÅJournal of the Optical Society of America, 1974
- Moment Theory Bounds for the Second-Order Optical Properties of Atoms and MoleculesThe Journal of Chemical Physics, 1972
- Continued Factorization Method for van der Waals InteractionsThe Journal of Chemical Physics, 1971
- Padé Summation of the Cauchy Dispersion Equation*Journal of the Optical Society of America, 1969
- Dispersion of HeliumJournal of the Optical Society of America, 1969
- Fitting Refractive Index Data by Least SquaresJournal of the Optical Society of America, 1961
- Rapid Method for Interpolating Refractive Index MeasurementsJournal of the Optical Society of America, 1961
- The refraction and dispersion of neon and heliumProceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character, 1932