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Record W2300893958 · doi:10.1038/srep23107

Ultra-high dynamic range electro-optic sampling for detecting millimeter and sub-millimeter radiation

2016· article· en· W2300893958 on OpenAlexafffund
Akram Ibrahim, Denis Férachou, Gargi Sharma, Kanwarpal Singh, Marie Kirouac-Turmel, T. Ozaki

Bibliographic record

VenueScientific Reports · 2016
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsInstitut National de la Recherche Scientifique
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsTerahertz radiationMillimeterDynamic rangeOpticsTerahertz spectroscopy and technologyHigh dynamic rangeTerahertz time-domain spectroscopyTerahertz gapOptoelectronicsSpectroscopyMaterials scienceRadiationPhysicsLaserFar-infrared laser

Abstract

fetched live from OpenAlex

Time-domain spectroscopy using coherent millimeter and sub-millimeter radiation (also known as terahertz radiation) is rapidly expanding its application, owing greatly to the remarkable advances in generating and detecting such radiation. However, many current techniques for coherent terahertz detection have limited dynamic range, thus making it difficult to perform some basic experiments that need to directly compare strong and weak terahertz signals. Here, we propose and demonstrate a novel technique based on cross-polarized spectral-domain interferometry to achieve ultra-high dynamic range electro-optic sampling measurement of coherent millimeter and sub-millimeter radiation. In our scheme, we exploit the birefringence in a single-mode polarization maintaining fiber in order to measure the phase change induced by the electric field of terahertz radiation in the detection crystal. With our new technique, we have achieved a dynamic range of 7 × 10(6), which is 4 orders of magnitude higher than conventional electro-optic sampling techniques, while maintaining comparable signal-to-noise ratio. The present technique is foreseen to have great impact on experiments such as linear terahertz spectroscopy of optically thick materials (such as aqueous samples) and nonlinear terahertz spectroscopy, where the higher dynamic range is crucial for proper interpretation of experimentally obtained results.

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 score0.138
Threshold uncertainty score0.409

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 head0.009
GPT teacher head0.224
Teacher spread0.215 · 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

Citations22
Published2016
Admission routes2
Has abstractyes

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