Statistical description of high-harmonic generation
Statistical description of high-harmonic generation
Here, we present a novel method for estimation of harmonic spectrum features generated from ultrashort high-intensity laser pulses propagating through gas-filled capillaries, based on pump pulse decomposition and statistical considerations.
Because of the strong optical nonlinearity, a high-intensity pump pulse launched with a simple, e.g. Gaussian, temporal profile develops a highly complex structure during propagation. We show how such complex propagating ultrashort infrared pulses can be decomposed and subdivided to provide more in-depth analysis of each of their intense regions, leading to a complete diagnostic view of the relevant features of ultrashort pulses for nonlinear optics, e.g. the number, peak intensities, and temporal widths of these individual pulse components within the complex structure. This analysis provides more insight into the collective action of all pulse components as opposed to traditional means which focus on a single feature, and allows diagnosis of the evolution of the large ensemble of features found in such intense ultrashort pulses.
This analysis is then used to inform an approximation of the high harmonic spectrum generated from such a pulse based on the cumulative harmonic generation of each of the propagating pulse components. We show that this method is 57 times faster than explicit simulation, requires significantly less computational power, and provides good approximations to many features of the generated high harmonic spectra. We see that this method provides a strong complementary approach to finding optimal conditions for generating the highest harmonics, and provides an intuitive system for identifying the root of certain harmonic pulse features and potentially for predicting the conditions for generating them.
University of Southampton
Degen-Knifton, Arthur
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September 2016
Degen-Knifton, Arthur
b5263cbb-0a09-406b-bd74-2b4180c31a39
Horak, Peter
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Degen-Knifton, Arthur
(2016)
Statistical description of high-harmonic generation.
University of Southampton, Doctoral Thesis, 84pp.
Record type:
Thesis
(Doctoral)
Abstract
Here, we present a novel method for estimation of harmonic spectrum features generated from ultrashort high-intensity laser pulses propagating through gas-filled capillaries, based on pump pulse decomposition and statistical considerations.
Because of the strong optical nonlinearity, a high-intensity pump pulse launched with a simple, e.g. Gaussian, temporal profile develops a highly complex structure during propagation. We show how such complex propagating ultrashort infrared pulses can be decomposed and subdivided to provide more in-depth analysis of each of their intense regions, leading to a complete diagnostic view of the relevant features of ultrashort pulses for nonlinear optics, e.g. the number, peak intensities, and temporal widths of these individual pulse components within the complex structure. This analysis provides more insight into the collective action of all pulse components as opposed to traditional means which focus on a single feature, and allows diagnosis of the evolution of the large ensemble of features found in such intense ultrashort pulses.
This analysis is then used to inform an approximation of the high harmonic spectrum generated from such a pulse based on the cumulative harmonic generation of each of the propagating pulse components. We show that this method is 57 times faster than explicit simulation, requires significantly less computational power, and provides good approximations to many features of the generated high harmonic spectra. We see that this method provides a strong complementary approach to finding optimal conditions for generating the highest harmonics, and provides an intuitive system for identifying the root of certain harmonic pulse features and potentially for predicting the conditions for generating them.
Text
Final Thesis
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Published date: September 2016
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Local EPrints ID: 419403
URI: http://eprints.soton.ac.uk/id/eprint/419403
PURE UUID: a542c583-f727-40d6-ac72-78033adb7e51
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Date deposited: 11 Apr 2018 16:31
Last modified: 16 Mar 2024 03:27
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Contributors
Author:
Arthur Degen-Knifton
Thesis advisor:
Peter Horak
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