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Record W4394498729 · doi:10.6084/m9.figshare.16589867

Data for Slow Light Nanocoatings for Ultrashort Pulse Compression

2023· dataset· en· W4394498729 on OpenAlexaboutno aff
Marcus Ossiander

Bibliographic record

VenueFigshare · 2023
Typedataset
Languageen
FieldPhysics and Astronomy
TopicQuantum optics and atomic interactions
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceUltrashort pulseCompression (physics)Pulse compressionPulse (music)OptoelectronicsOpticsComputer scienceComposite materialPhysicsTelecommunicationsLaser

Abstract

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<b>Data for </b><b>Slow light nanocoatings for ultrashort pulse compression</b><br>M. Ossiander1,* Y.-W. Huang1,2, W. T. Chen1, Z. Wang3, X. Yin1, Y. A. Ibrahim1,4, M. Schultze3, F. Capasso1*1 John A. Paulson School of Engineering and Applied Sciences, Harvard University, 29 Oxford St, Cambridge, MA 02138, USA. <br>2 Department of Photonics, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan.<br>3 Institute of Experimental Physics, Graz University of Technology, Petersgasse 16, 8010 Graz, Austria.<br>4 University of Waterloo, Waterloo, ON N2L 3G1, Canada.<br>* Corresponding Authors: mossiander@g.harvard.edu, capasso@seas.harvard.edu<br>Manuscript published in <b>Nature Communications 12, 6518 (2021),</b> https://www.nature.com/articles/s41467-021-26920-6Details of the data files are described below and in the description.txt files. Methods are described in the publication.-- <br><b>Folder frog_data: </b><br>This folder contains the frequency resolved optical gating data for the 162 nm nanopillar diameter coating.<br>Reference data for the incoming femtosecond laser pulses and the incoming laser pulses transmitted through the uncoated substrate only are also provided.The variables in the files are:<br>wavelength_nm: wavelength axis for frequency resolved optical gating spectrogram in nanometers.<br>delay_fs: delay axis for the frequency resolved optical gating spectrogram in femtoseconds.<br>spectrogram: the raw frequency resolved optical gating spectrogram in arbitrary units.<b>Folder white_light_data: </b><br>This folder contains the raw white light interferometer data.<br>Folders are named according to the nanopillar diameter of the examined compressor coating.<br>For each coating, reference data of the empty interferometer, and reference data of the substrate in one interferometer arm (double pass) is also provided.The variables in the files are:<br>wavelength: wavelength axis for the recorded spectral intensities in nanometers.<br>background: Spectral intensity after the interferometer with both interferometer arms blocked in arbitrary units.<br>A: Spectral intensity after the interferometer with sample arm blocked in arbitrary units.<br>B: Spectral intensity after the interferometer with reference arm blocked in arbitrary units.<br>AB: Spectral intensity after the interferometer in arbitrary units.<br>wavelengthGD: wavelength axis for the calculated group delay in nanometers.<br>frequencyGD: frequency axis for the calculated group delay in petahertz.<br>GDnm: calculated group delay in femtoseconds (plot versus wavelengthGD).<br>GDPHz: calculated group delay in femtoseconds (plot versus frequencyGD).

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.023
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0260.003

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 head0.078
GPT teacher head0.349
Teacher spread0.271 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2023
Admission routes1
Has abstractyes

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