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Record W2954819644 · doi:10.1088/1367-2630/ab2f5c

The influence of x-ray pulse length on space-charge effects in optical pump/x-ray probe photoemission

2019· article· en· W2954819644 on OpenAlexaff
Danilo Kühn, Erika Giangrisostomi, Raphael M. Jay, F. Sorgenfrei, Alexander Föhlisch

Bibliographic record

VenueNew Journal of Physics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPhysicsAtomic physicsPicosecondExcited stateElectronSpectroscopySpace chargePhotoemission spectroscopySpectral lineLaserX-ray photoelectron spectroscopyOpticsNuclear magnetic resonance

Abstract

fetched live from OpenAlex

Abstract Pump-probe photoelectron spectroscopy (PES) is a versatile tool to investigate the dynamics of transient states of excited matter. Vacuum space-charge effects can mask these dynamics and complicate the interpretation of electron spectra. Here we report on space-charge effects in Au 4f photoemission from a polycrystalline gold surface, excited with moderately intense 90 ps (FWHM) soft x-ray probe pulses, under the influence of the Coulomb forces exerted by a pump electron cloud, which was produced by intense 40 fs laser pulses. The experimentally observed kinetic energy shift and spectral broadening of the Au 4f lines, measured with highly-efficient time-of-flight spectroscopy, are in good agreement with simulations utilizing a mean-field model of the electrostatic pump electron potential. This confirms that the line broadening is predominantly caused by variations in the take-off time of the probe electrons without appreciable influence of local scattering events. Our findings might be of general interest for pump-probe PES with picosecond-pulse-length sources.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.246
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2019
Admission routes1
Has abstractyes

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