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Multiparticle cumulant mapping for Coulomb explosion imaging: Calculations and algorithm

  • Chuan Cheng
  • , Leszek J. Frasinski
  • , Gönenç Moǧol
  • , Felix Allum
  • , Andrew J. Howard
  • , Philip H. Bucksbaum
  • , Ruaridh Forbes
  • , Thomas Weinacht
  • Stony Brook University
  • SLAC National Accelerator Laboratory
  • Imperial College London
  • Stanford University

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

We present a versatile cumulant mapping algorithm for analyzing correlated particle emission, offering insights into complex electronic and nuclear dynamics. Recently, we have demonstrated the use of cumulant mapping to extract information-rich correlations between the momenta of multiple fragments produced in Coulomb explosion imaging experiments [C. Cheng, Phys. Rev. Lett. 130, 093001 (2023)0031-900710.1103/PhysRevLett.130.093001]. We define cumulant mapping in terms of histograms, enabling fast computation of linear (additive) observables. However, applying the same algorithm to nonlinear (nonadditive) observables poses challenges, as the computation time of conventional estimators scales nonlinearly with data size. To overcome this, we develop estimators and an accompanying algorithm to enable computationally efficient estimation of the cumulant of interest. Comparisons of computation times and signal-to-noise ratios reveal the superior performance of our approach. This method is demonstrated on the (D+, D+, C+, O+) dissociation channel of CD2O4+ produced in a strong-field ionization experiment. Additionally, Poisson statistics are used to simulate the two methods and provide insights into the efficiency of our algorithm. The proposed methodology unlocks efficient computation of cumulant mapping for a broader range of complex systems and observables, such as the laser pulse dependence of ionization dynamics.

Original languageEnglish
Article number042802
JournalPhysical Review A
Volume109
Issue number4
DOIs
StatePublished - Apr 2024

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