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Record W2744216776 · doi:10.1103/physreva.93.043417

Nonsequential double ionization of helium in IR+XUV two-color laser fields: Collision-ionization process

2016· article· en· W2744216776 on OpenAlexafffund
Yuanye Tian, Jing Chen, Yujun Yang, Xiaojun Liu, Zong-Chao Yan, Bingbing Wang

Bibliographic record

VenuePhysical review. A/Physical review, A · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsDouble ionizationExtreme ultravioletIonizationAtomic physicsHeliumCollisionPhysicsLaserNuclear physicsOpticsIonQuantum mechanics

Abstract

fetched live from OpenAlex

We investigate the nonsequential double ionization (NSDI) process of an atom in IR+XUV two-color intense laser fields, where the photon energy of the XUV laser is higher than the atomic ionization threshold. By using the frequency-domain theory, we consider the NSDI as a process caused by the collision-ionization mechanism and obtain the NSDI spectrum that presents a multiplateau structure. With the help of channel analysis, we find that the height of a plateau in the NSDI spectrum is determined by the number of XUV photons absorbed by the electrons. Furthermore, to explain the interference structure in the NSDI spectrum, we also compare the contributions of forward and backward collisions to the NSDI probability. We find that the forward collision dominates the contributions to the NSDI when two electrons are ejected along the same direction and both forward and backward collisions make a comparable contribution to NSDI when the two electrons are ejected along opposite directions. By applying the saddle-point approximation, we obtain an energy-circle formula, which may illustrate the formation of the NSDI spectrum structure.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.921

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.013
GPT teacher head0.370
Teacher spread0.357 · 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

Citations21
Published2016
Admission routes2
Has abstractyes

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