ITERATIVE REDUCTION OF GAIN VARIATIONS IN PARALLEL ELECTRON-ENERGY LOSS SPECTROMETRY

We discuss a method of reducing intrinsic gain variations of the detector array in parallel electron energy loss spectrometry (PEELS). Two or more spectra are acquired independently, but under the same experimental conditions, except that the spectra are shifted over the array with respect to each other by a certain amount. For stochastic gain variations the problem is solved in closed form. It is shown that the reduction of the variance of gain variations increases with the squareroot of number of iterations. Simulations for a purely stochastic gain spectrum prove the predictions. Experimental gain spectra turn out to be non-random. The consequence of non-stochasticity (correlations between channels in the array) can be understood within the theory. The proposed method is useful for any experiment involving a linear or two-dimensional detector array where it is not possible to obtain a ''flat field'' spectrum.