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Record W2508994082 · doi:10.1103/physreva.94.023825

<i>In situ</i>attosecond pulse characterization techniques to measure the electromagnetic phase

2016· article· en· W2508994082 on OpenAlexaff
M. Spanner, J. B. Bertrand, D. M. Villeneuve

Bibliographic record

VenuePhysical review. A/Physical review, A · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsAttosecondMeasure (data warehouse)Characterization (materials science)Phase (matter)Electromagnetic pulsePhysicsPulse (music)In situOpticsAtomic physicsUltrashort pulseLaserQuantum mechanicsComputer science

Abstract

fetched live from OpenAlex

A number of techniques have been developed to characterize the attosecond emission from high-order-harmonic sources. These techniques are broadly classified as ex situ, where the attosecond pulse train photoionizes a target gas in the presence of an infrared field, and in situ, where the measurement takes place in the medium in which the attosecond pulses are generated. It is accepted that ex situ techniques measure the characteristics of the electromagnetic field, including the phase of the recombination transition moment of the emitting atom or molecule, when the phase of the second medium is known. However, there is debate about whether in situ techniques measure the electromagnetic field, or only the characteristics of the recolliding electron before recombination occurs. We show numerically that in situ measurements are not sensitive to the recombination phase, when implemented in the perturbative regime as originally envisioned, and that they do not measure the electromagnetic phase of the emission.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.351
Teacher spread0.339 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations15
Published2016
Admission routes1
Has abstractyes

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