Details
| Original language | English |
|---|---|
| Pages (from-to) | 3992-3995 |
| Number of pages | 4 |
| Journal | Optics letters |
| Volume | 47 |
| Issue number | 16 |
| Early online date | 3 Aug 2022 |
| Publication status | Published - 15 Aug 2022 |
Abstract
The field of ultrafast spectroscopy is based on lasers being able to produce pulses that are as short as a few femtoseconds. Due to their broad bandwidth, these ultrashort light transients are strongly affected by propagation through materials. Therefore, a careful characterization of their temporal profile is required before any application. We propose a scheme for their characterization in situ, ensuring that the pulse parameters are measured in the region where the interaction with the sample takes place. Our method is based on first-principles calculations for strong-field ionization of rare-gas atoms and autocorrelation. We introduce a machine-learning algorithm, called vector space Newton interpolation cage (VSNIC), that uses the results from the first-principles calculations as input and reconstructs from a strong-field autocorrelation pattern for an unknown pulse the pulse length and spectral width by narrow margins.
ASJC Scopus subject areas
- Physics and Astronomy(all)
- Atomic and Molecular Physics, and Optics
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In: Optics letters, Vol. 47, No. 16, 15.08.2022, p. 3992-3995.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - In situ characterization of few-femtosecond laser pulses by learning from first-principles calculations
AU - Geffert, Otfried
AU - Kolbasova, Daria
AU - Trabattoni, Andrea
AU - Calegari, Francesca
AU - Santra, Robin
PY - 2022/8/15
Y1 - 2022/8/15
N2 - The field of ultrafast spectroscopy is based on lasers being able to produce pulses that are as short as a few femtoseconds. Due to their broad bandwidth, these ultrashort light transients are strongly affected by propagation through materials. Therefore, a careful characterization of their temporal profile is required before any application. We propose a scheme for their characterization in situ, ensuring that the pulse parameters are measured in the region where the interaction with the sample takes place. Our method is based on first-principles calculations for strong-field ionization of rare-gas atoms and autocorrelation. We introduce a machine-learning algorithm, called vector space Newton interpolation cage (VSNIC), that uses the results from the first-principles calculations as input and reconstructs from a strong-field autocorrelation pattern for an unknown pulse the pulse length and spectral width by narrow margins.
AB - The field of ultrafast spectroscopy is based on lasers being able to produce pulses that are as short as a few femtoseconds. Due to their broad bandwidth, these ultrashort light transients are strongly affected by propagation through materials. Therefore, a careful characterization of their temporal profile is required before any application. We propose a scheme for their characterization in situ, ensuring that the pulse parameters are measured in the region where the interaction with the sample takes place. Our method is based on first-principles calculations for strong-field ionization of rare-gas atoms and autocorrelation. We introduce a machine-learning algorithm, called vector space Newton interpolation cage (VSNIC), that uses the results from the first-principles calculations as input and reconstructs from a strong-field autocorrelation pattern for an unknown pulse the pulse length and spectral width by narrow margins.
UR - http://www.scopus.com/inward/record.url?scp=85137715242&partnerID=8YFLogxK
U2 - 10.1364/OL.460513
DO - 10.1364/OL.460513
M3 - Article
AN - SCOPUS:85137715242
VL - 47
SP - 3992
EP - 3995
JO - Optics letters
JF - Optics letters
SN - 0146-9592
IS - 16
ER -