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Removal of correlated background in a high-order harmonic transient absorption spectra with principal component regression
Author(s) -
Davide Faccialà,
Benjamin W. Toulson,
Oliver Geßner
Publication year - 2021
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.435008
Subject(s) - extreme ultraviolet , optics , physics , rydberg formula , femtosecond , high harmonic generation , spectroscopy , principal component analysis , absorption spectroscopy , atomic physics , materials science , laser , ionization , statistics , ion , mathematics , quantum mechanics
We demonstrate a 40x mean noise power reduction (NPR) in core-to-valence extreme ultraviolet (XUV) femtosecond transient absorption spectroscopy with a high harmonic generation (HHG) light source. An adaptive iteratively reweighted principal component regression (airPCR) is used to analyze and suppress spectrally correlated HHG intensity fluctuations. The technique requires significantly less user input and leads to a higher mean NPR than a previously introduced edge-pixel PCR method that relies on the manual identification of signal-free spectral regions. Both techniques are applied in a time-resolved XUV absorption study of the 2snp 1 P o (n ≥ 2) autoionizing Rydberg states of helium, demonstrating sub-10 -3 optical density sensitivity.

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