Predetermining acceptable noise limits of EXAFS spectra in the limit of stochastic noise

Abstract

Abstract.The effect of stochastic noise on Extended X-ray Absorption Fine Structure (EXAFS) data measurement, analysis, and fitting is discussed. Stochastic noise reduces the ability to uniquely fit a calculated model to measured EXAFS data. Such noise can be reduced by common methods that increase the signal-to-noise ratio; however, these methods are not always practical. Therefore, predetermined, quantitative knowledge of the level of acceptable stochastic noise when fitting for a particular model system is essential in maximizing the chances of a successful EXAFS experiment and minimizing wasted beamtime. This paper outlines a method to estimate, through simulation, the acceptable level of stochastic noise in EXAFS spectra that still allows a successful test of a proposed model compound.1. Introduction EXAFS measurements are used to probe a variety of experimental systems, but excel at elucidating local structure in samples which have slight disorder or no long-range crystalline order. Of special interest to the authors is the use of EXAFS in understanding the molecularlevel binding structure and characteristics of actinides on the surface of environmental minerals and model mineral analogs [1]. In environmental systems the element of interest can be on the order of 10 −7 % by weight of the total sample. Obviously such samples would be impossible to measure using EXAFS techniques. It is therefore essential to increase the concentration of the element of interest while still preserving a sample's ability to represent environmental conditions. Under such low concentration limits it is expected that the collected data is countrate, or stochastically limited. This condition occurs as we approach the signal-to-noise (S/N) limit of the technique where the random noise of the measurement process dominates over possible systematic errors [2,3]. When stochastic error is expected to dominate systematic error, it is possible to predict, with the use of simulations, the ability of model fits to tolerate a certain level of stochastic noise. Elsewhere in these proceedings, we discuss how to tell when systematic errors dominate in measured EXAFS spectrum [4].Here, we outline a technique for determining the number of EXAFS scans necessary to test the relevance of a given structural model. Appropriate stochastic noise levels are determined for each point in r-space by collecting data on a real system. These noise levels are then applied to EXAFS simulations using a test model. In this way, all significant systematic error sources

Interstitial Incorporation of Plutonium into a Low-Dimensional Potassium Borate

“…The degree of freedom of the fit is estimated to be 11.7 . Error estimates use a Monte Carlo method . The amplitude reduction factor for these fits is determined to be S 0 2 = 1.14 ± 0.14, and the edge shift is Δ E 0 = −11.0 ± 0.9 eV.…”

“…68 Error estimates use a Monte Carlo method. 69 The amplitude reduction factor for these fits is determined to be S 0 2 = 1.14 ( 0.14, and the edge shift is ΔE 0 = À11.0 ( 0.9 eV.…”

Using XAS to monitor radiation damage in real time and post-analysis, and investigation of systematic errors of fluorescence XAS for Cu-bound amyloid-β

“…Usually, fluorescence XAS measurements are limited to k = 12 A ˚À 1 or less for dilute samples due to noise at high k (Penner-Hahn, 1999). Fluctuations due to stochastic noise (Hu & Booth, 2009) and electric noise (Abe et al, 2018) in the �(k) spectrum at high k will distort determined bond lengths and parameters. The unwanted noisy measurements were trimmed to achieve accurate spectral data.…”