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Record W4415830553 · doi:10.1364/prj.578988

Optical RF memory with an ultra-long storage time of 13  ms

2025· article· en· W4415830553 on OpenAlexaff
Guangying Wang, Chao Song, Guibin Zhang, Junyi Zhang, Yiran Guan, Jiejun Zhang, Jianping Yao

Bibliographic record

VenuePhotonics Research · 2025
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsUniversity of Ottawa
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsMicrowaveRadio frequencyBandwidth (computing)Computer data storageSIGNAL (programming language)Optical storageOptical fiberHigh fidelityAmplifier

Abstract

fetched live from OpenAlex

An optical RF memory (ORFM) based on a fiber acousto-optic frequency shifting loop (AO-FSL) for microwave signal storage with, to our knowledge, a record-long storage time of 13 ms is proposed and experimentally demonstrated. The key to achieving a long storage time is the use of a distributed Raman fiber amplifier (DRFA) that can compensate for the loop loss while maintaining an ultra-low noise figure (NF). An acousto-optic frequency shifter is employed in the loop to avoid lasing. To test the ORFM, a microsecond-long microwave signal is amplitude-modulated on an optical carrier and injected into the AO-FSL. Experimental results show that the ORFM enables the storage of microwave signals, including single-tone and linearly frequency modulated (LFM) microwave signals, with signal durations up to 10 μs and a record-long storage time of 13 ms. This corresponds to more than 300 circulations in the AO-FSL, representing the highest number ever reported to date. Compared with a digital RF memory, our proposed ORFM eliminates the need for the high-speed analog-to-digital converter (ADC) and digital-to-analog converter (DAC), offering a wide operational bandwidth and simplified system architecture. These advantages make it particularly well-suited for electronic warfare applications where an ORFM having a long storage time and a high signal fidelity is needed.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.311
Teacher spread0.287 · 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 designSimulation or modeling
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
Published2025
Admission routes1
Has abstractyes

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