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New mechanism for the generation of electron-positron pairs in Laser-Matter Interaction: Resonantly Enhanced Pair Production in a molecular system

2013· article· en· W1981551617 on OpenAlexaff
François Fillion‐Gourdeau, Emmanuel Lorin, André D. Bandrauk

Bibliographic record

VenueJournal of Physics Conference Series · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsFields Institute for Research in Mathematical SciencesUniversité de SherbrookeUniversité de MontréalCarleton UniversityUniversity of Toronto
Fundersnot available
KeywordsPair productionPhysicsAtomic physicsElectric fieldElectronDiatomic moleculeLaserField (mathematics)PositronQuantum tunnellingResonance (particle physics)Quantum mechanicsMolecule

Abstract

fetched live from OpenAlex

A new mechanism for pair production from the interaction of a laser with two nuclei is presented. The latter takes advantage of the Stark effect in diatomic molecules and the presence of molecular resonances in the negative and positive energy continua. Both move in the complex energy plane as the interatomic distance and the electric field strength are varied. We demonstrate that there is an enhancement of pair production at the crossing of these resonances. This mechanism is studied in a very simple one-dimensional model where the nuclei are modeled by delta function potential wells and the laser by a constant electric field. The position of resonances is evaluated by using the Weyl-Titchmarch-Kodaira theory, which allows to treat singular boundary value problems and to compute the spectral density. The rate of producing pairs is also computed. It is shown that this process yields a positron production rate which is approximately an order of magnitude higher than in the single nucleus case and a few orders of magnitudes higher than Schwinger's tunneling result in a static field.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.251
Teacher spread0.235 · 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 designSimulation or modeling
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

Citations1
Published2013
Admission routes1
Has abstractyes

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