Issue 35, 2022

Cumulant mapping as the basis of multi-dimensional spectrometry

Abstract

Cumulant mapping employs a statistical reconstruction of the whole by sampling its parts. The theory developed in this work formalises and extends ad hoc methods of ‘multi-fold’ or ‘multi-dimensional’ covariance mapping. Explicit formulae have been derived for the expected values of up to the 6th cumulant and the variance has been calculated for up to the 4th cumulant. A method of extending these formulae to higher cumulants has been described. The formulae take into account reduced fragment detection efficiency and a background from uncorrelated events. Number of samples needed for suppressing the statistical noise to a required level can be estimated using Matlab code included in Supplemental Material. The theory can be used to assess the experimental feasibility of studying molecular fragmentations induced by femtosecond or X-ray free-electron lasers. It is also relevant for extending the conventional mass spectrometry of biomolecules to multiple dimensions.

Graphical abstract: Cumulant mapping as the basis of multi-dimensional spectrometry

Associated articles

Supplementary files

Article information

Article type
Paper
Submitted
25 May 2022
Accepted
21 Jul 2022
First published
26 Jul 2022
This article is Open Access
Creative Commons BY-NC license

Phys. Chem. Chem. Phys., 2022,24, 20776-20787

Cumulant mapping as the basis of multi-dimensional spectrometry

L. J. Frasinski, Phys. Chem. Chem. Phys., 2022, 24, 20776 DOI: 10.1039/D2CP02365B

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