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Record W4401568570 · doi:10.1109/pn62551.2024.10621782

Compressed Ultrafast Femtography by Coded-Aperture Sweeping

2024· article· en· W4401568570 on OpenAlexaff
Miguel Márquez, Jingdan Liu, Yingming Lai, Heide Ibrahim, Katherine Légaré, Philippe Lassonde, Xianglei Liu, M. Hehn, S. Mangin, G. Malinowski, Zhengyan Li, François Légaré, Jinyang Liang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Optical Sensing Technologies
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsUltrashort pulseComputer scienceComputer visionComputer graphics (images)OpticsPhysicsLaser

Abstract

fetched live from OpenAlex

Single-shot real-time femtophotography has surged as a crucial tool for imaging ultrafast dynamics during their times of occurrence. However, most existing methods limit imaging speed or degraded data quality by the deployed optoelectronic devices. To overcome these limitations, we propose swept-coded aperture real-time femtophotography (SCARF) that enables, in an all-optical fashion, records of ultrafast events with a full-sequence encoding of up to 156.3 THz and a sequence depth of up to 132. We use SCARF to image ultrashort pulses through transparencies and ultrafast absorption in a semiconductor.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.953
Threshold uncertainty score0.431

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 head0.005
GPT teacher head0.238
Teacher spread0.233 · 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 designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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