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Record W2891149728 · doi:10.1364/oe.395185

Mechanism of laser induced filamentation in dielectrics

2020· preprint· en· W2891149728 on OpenAlexafffund
Neda Naseri, Gabriel Dupras, Lora Ramunno

Bibliographic record

VenueOptics Express · 2020
Typepreprint
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsUniversity of Ottawa
FundersAir Force Office of Scientific ResearchCanada Research ChairsCanada Foundation for Innovation
KeywordsFilamentationFemtosecondLaserFinite-difference time-domain methodOpticsKerr effectPulse (music)Nonlinear systemMaterials sciencePhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

Femtosecond laser filamentation in transparent media has a wide range of applications, from three dimensional manufacturing to biological technologies to supercontinuum generation. While there has been extensive investigations over the last two decades, there remain aspects that are not understood, owing to the complexity of the interaction. We revisit intense femtosecond laser interaction with dielectric materials at 800nm under tight focusing via high resolution three dimensional simulations, where the complete set of Maxwell's equations is solved. We simulate filament formation for a range of tight focusing conditions and laser energies, and through this are able to shed new insight on the dynamics. We find that the role of the Kerr effect is very different depending upon the degree of tight focusing. We are also able to observe the formation of two distinct damage zones for intermediate tight focusing, similar to what was seen but not fully understood almost two decades ago.

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 score0.061
Threshold uncertainty score0.919

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 integrity0.0000.000
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 head0.028
GPT teacher head0.257
Teacher spread0.230 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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