We introduce a novel in-situ strong field ionization tomography approach for characterizing the spatial density distribution of gas jets. We show that for typical intensities in high harmonic generation experiments, the strong field ionization mechanism used in our approach provides an improvement in the resolution close to factor of 2 (resolving about 8 times smaller voxel volume), when compared to linear/single-photon imaging modalities. We find, that while the depth of scan in linear tomography is limited by resolution loss due to the divergence of the driving laser beam, in the proposed approach the depth of focus is localized due to the inherent physical nature of strong-field interaction and discuss implications of these findings. We explore key aspects of the proposed method and compare it with commonly used single- and multi-photon imaging mechanisms. The proposed method will be particularly useful for strong field and attosecond science experiments.

Laser induced strong-field ionization gas jet tomography

STAGIRA, SALVATORE;Vozzi, Caterina;
2017-01-01

Abstract

We introduce a novel in-situ strong field ionization tomography approach for characterizing the spatial density distribution of gas jets. We show that for typical intensities in high harmonic generation experiments, the strong field ionization mechanism used in our approach provides an improvement in the resolution close to factor of 2 (resolving about 8 times smaller voxel volume), when compared to linear/single-photon imaging modalities. We find, that while the depth of scan in linear tomography is limited by resolution loss due to the divergence of the driving laser beam, in the proposed approach the depth of focus is localized due to the inherent physical nature of strong-field interaction and discuss implications of these findings. We explore key aspects of the proposed method and compare it with commonly used single- and multi-photon imaging mechanisms. The proposed method will be particularly useful for strong field and attosecond science experiments.
2017
Multidisciplinary
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1031952
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