A General Method of Time Correlation Retrieval for Quantum Interference in Strong-Field Ionization
ORAL
Abstract
In laser-induced strong-field ionization (SFI), photoelectrons escape the parent ion and oscillate on semi-classical trajectories within the laser field. These trajectories are determined primarily by the phase in the laser field at which ionization occurred and the shape of the laser field. As an electron travels along a trajectory it accumulates phase, which produces quantum interference structures when pairs of trajectories contribute to the final amplitude. When acquiring the photoelectron momentum distribution (PMD) through angle- and energy-resolved detection systems such as velocity map imaging, these quantum interferences manifest as intricate, overlapping patterns on the detector. Much study has focused on unraveling these patterns in order to understand the ultrafast electron dynamics integral to their formation. We introduce and apply a broadly applicable time correlation filtering technique which isolates interference structures formed by trajectory pairs whose ionization phases are separated by a specified time. By examining the time correlations at which structures are emphasized, we empirically corroborate predictions from a leading theoretical model of SFI. Based on the selected time correlation, interference patterns produced by specific pairs of trajectories can be isolated, allowing for in depth quantitative studies of rescattering orbits and the structure of the parent ion. As an analysis technique, this time resolution can be achieved for all angle- and energy-resolved PMDs, unlocking a powerful observable without requiring any changes in experimental schema. The generality of the filtering technique combined with its ability to disentangle complex experimental spectra will greatly augment the level of analysis that can be performed on this type of data.
*This work was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences (BES), Chemical Sciences, Geosciences, and Biosciences Division, AMOS Program.
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Presenters
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Nicholas Werby
- Stanford University