Electric-Field Modeling Toolkit for Type-II Pulsed Bessel-Gaussian Second-Harmonic Generation in KTP
Bibliographic record
Abstract
This toolkit addresses the computational modeling of three-dimensional time-dependent electric-field distributions in type-II pulsed Bessel-Gaussian second-harmonic generation within potassium titanyl phosphate (KTP) crystals, where depleted-wave dynamics dominate nonlinear optical conversion. The toolkit solves three coupled nonlinear wave equations for ordinary and extraordinary fundamental waves and extraordinary second-harmonic waves using finite difference methods in cylindrical coordinates. It accepts user-defined parameters including pulse energy, beam spot size, crystal dimensions, and optical properties as inputs, and produces spatiotemporal electric-field amplitude distributions and conversion efficiency profiles as outputs. A unified Fortran codebase provides reproducible simulation pipelines, parametric sweep capabilities for examining interaction length dependencies, and computational optimizations that enable execution on standard desktop systems despite the fine radial meshes required for Bessel-Gaussian beam fluctuations. The implementation reproduces previously published quantitative predictions, specifically confirming that for $\omega_f \approx 80~\mu$m spot sizes and $0.8$~J pulse energies, complete energy exchange occurs over approximately $5$~mm, which validates the necessity of depleted-wave formalism for crystals exceeding this interaction length. The toolkit is available as an open-source GitHub repository and is released as version v1.0.1 under the MIT License.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".