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Record W4413832791 · doi:10.3390/atoms13090075

Interfacing the B-Spline R-Matrix and R-Matrix with Time Dependence Computer Codes: An Update

2025· article· en· W4413832791 on OpenAlexaff
J. C. del Valle, Aaron Bondy, Soumyajit Saha, Kathryn R. Hamilton, Klaus Bartschat

Bibliographic record

VenueAtoms · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsUniversity of Windsor
FundersNational Science Foundation
KeywordsInterfacingMatrix (chemical analysis)Computer scienceComputational sciencePhysicsAlgorithmComputer hardwareMaterials science

Abstract

fetched live from OpenAlex

As a continuation of Schneider et al., Atoms 2022 10, 26, we report recent progress in the development and deployment of the interface between the computational codes B-Spline R-matrix (BSR) and R-Matrix with Time dependence (RMT). These advances have been achieved within the context of the LS-coupling scheme. In its current state, the interface handles atomic target states described by single configurations and supports the Fano–Racah phase convention, as required by RMT. As first example of an application, we use the interface to investigate multiphoton single ionization of helium exposed to a linearly polarized laser field with wavelengths between 280 and 316 nm and a peak intensity of 3×1014 W/cm2. As a second example, we consider high-order harmonic generation (HHG) in carbon, driven by an intense 30-cycle laser field at 800 nm and a peak intensity of 1×1012 W/cm2.

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)0.006
metaresearch head score (Gemma)0.020
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: Methods · Consensus signal: Methods
Teacher disagreement score0.030
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.020
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0040.007
Open science0.0070.004
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0300.027

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 head0.003
GPT teacher head0.248
Teacher spread0.244 · 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
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

Citations1
Published2025
Admission routes1
Has abstractyes

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