Phys Chem Chem Phys. 2022 Sep 1. doi: 10.1039/d2cp02365b. Online ahead of print.
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.
PMID:36047473 | DOI:10.1039/d2cp02365b
