Evidence map›Paper›PMID 38170749›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2024

Controlling laser-dressed resonance line shape using attosecond extreme-ultraviolet pulse with a spectral minimum.

Yong Fu, Bincheng Wang, Kan Wang, Xiangyu Tang, Baochang Li, Zhiming Yin, Jiaxin Han, C D Lin, Cheng Jin

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Yong FuDepartment of Applied Physics, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China.
Bincheng WangDepartment of Applied Physics, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China.ORCID 0000-0002-8471-5585
Kan WangDepartment of Applied Physics, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China.
Xiangyu TangDepartment of Applied Physics, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China.
Baochang LiDepartment of Applied Physics, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China.ORCID 0000-0001-9781-610X
Zhiming YinDepartment of Applied Physics, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China.
Jiaxin HanDepartment of Applied Physics, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China.
C D LinDepartment of Physics, James R. Macdonald Laboratory, Kansas State University, Manhattan, KS 66506.ORCID 0000-0003-4847-8938
Cheng JinDepartment of Applied Physics, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China.ORCID 0000-0001-8445-2378

Funding

Chemical Science Division, Office of Basic Energy Sciences, Office of Science, US Department of Energy DE-FG02-86ER13491Funding of Nanjing University of Science and Technology TSXK2022D005JST | Natural Science Foundation of Jiangsu Province (Jiangsu Natural Science Foundation) BK20220925MOST | National Natural Science Foundation of China (NSFC) 11834004MOST | National Natural Science Foundation of China (NSFC) 12204238MOST | National Natural Science Foundation of China (NSFC) 12274230
6 · The paper itself

Abstract

High-harmonic generation from a gas target exhibits sharp spectral features and rapid phase variation near the Cooper minimum. By applying spectral filtering, shaped isolated attosecond pulses can be generated where the pulse is split into two in the time domain. Using such shaped extreme-ultraviolet (XUV) pulses, we theoretically study attosecond transient absorption (ATA) spectra of helium [Formula: see text] autoionizing state which is resonantly coupled to the [Formula: see text] dark state by a time-delayed infrared laser. Our simulations show that the asymmetric [Formula: see text] Fano line shape can be readily tuned into symmetric Lorentzian within the time delay of a few tens of attoseconds. Such efficient control is due to the destructive interference in the generation of the [Formula: see text] state when it is excited by a strongly shaped XUV pulse. This is to be compared to prior experiments where tuning the line shape of a Fano resonance would take tens of femtoseconds. We also show that the predicted ATA spectral line shape can be observed experimentally after propagation in a gas medium. Our results suggest that strongly shaped attosecond XUV pulses offer the opportunity for controlling and probing fine features of narrow resonances on the few-ten attoseconds timescale.

Indexed as

attosecond transient absorptionCooper minimumdoubly excited stateFano resonance

Identifiers

PMID38170749
PMCPMC10786267

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.