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Measurement of complex ultrashort laser pulses using frequency-resolved optical gating.

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This thesis contains three components of research: a detailed study of the performance of Frequency-Resolved Optical Gating (FROG) for measuring complex ultrashort laser pulses, a new method for measuring the arbitrary polarization state of an ultrashort laser pulse using Tomographic Ultrafast Retrieval of Transverse Light E-fields (TURTL...
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Measurement of complex ultrashort laser pulses using frequency-resolved optical gating.

This thesis contains three components of research: a detailed study of the performance of Frequency-Resolved Optical Gating (FROG) for measuring complex ultrashort laser pulses, a new method for measuring the arbitrary polarization state of an ultrashort laser pulse using Tomographic Ultrafast Retrieval of Transverse Light E-fields (TURTLE) technique, and new approach for measuring two complex pulses simultaneously using PG blind FROG.;In recent decades, many techniques for measuring the full intensity and phase of ultrashort laser pulses have been proposed. These techniques include: Spectral Interferometry (SI)[1], Temporal Analysis by Dispersing a Pair of Light E-Field (TADPOLE)[2], Spectral Phase Interferometry for direct electric-field reconstruction (SPIDER)[3], and Frequency-Resolved Optical Gating (FROG)[4]. Each technique is actually a class of techniques that includes different variations on the original idea, such as SEA-SPIDER[5], ZAP SPIDER[6] are two variations of SPIDER. But most of these techniques for measuring ultrashort laser pulses either do not yield the complete time-dependent intensity and phase (e.g., autocorrelation), can at best only measure simple pulses (e.g., SPIDER), or need well characterized reference pulse.;In this thesis, we compare the performance of three versions of FROG: second-harmonic-generation (SHG) FROG, polarization-gate (PG) FROG, and cross-correlation FROG (XFROG), the last of which requires a well-characterized reference pulse. We found that the XFROG algorithm converged in all cases and required only one initial guess. The PG FROG algorithm converged for 99% of the moderately complex pulses that we tried, and for over 95% of the most complex pulses (TBP ∼ 100). And the SHG FROG algorithm converged for 95% of the pulses that we tried and for over 80% of the most complex pulses. After some analysis, we found that noise filtering and adding more sampling points to the FROG trace solved the non-converging problems and

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