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Record W4220797045 · doi:10.1117/12.2607894

A cryogenic FMCW range-resolved laser interferometer: challenges and applications

2022· article· en· W4220797045 on OpenAlexaff
Adam J. Christiansen, David A. Naylor, Alicia M. Anderson, Brad G. Gom

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsInterferometryOpticsAstronomical interferometerLaserPhysicsInstrumentation (computer programming)CryogenicsContinuous waveComputer science

Abstract

fetched live from OpenAlex

The continually increasing sensitivity required for the advancement of far-infrared astronomy dictates that the next generation of space-based observatories must employ cryogenically cooled telescopes and instrumentation. Operating cryogenic instrumentation in orbit poses several challenges, including the need for extremely low power dissipation and precise position measurement and control. In prior work, we reported on the development of a homodyne three-phase range-resolved laser interferometer, which demonstrated a displacement measurement uncertainty of 2:3nmrms at &lt;4K.<sup>1</sup> Effects of low frequency noise (1=f) in the electrical signals at low velocities were performance limiting due to the interpretation of noise as interference fringes. To avoid 1=f noise, a frequency-modulated continuous-wave (FMCW) heterodyne approach was adopted. An FMCW prototype was developed, and the preliminary results yielded an uncertainty of 29nmrms at &lt;4K.<sup>2</sup> In this paper we present the design of an integrated cryogenic FMCW range-resolved laser interferometer which features real time data processing for simultaneous displacement measurements of up to 8 axes. The performance of fibers and their coupling under ultra-high vacuum at cryogenic temperatures is largely unexplored, and we present the cryogenic characterization results of several key variables, including fiber type, termination, and mating, along with alignment effects due to the thermal contraction of fiber components. These results have been incorporated into the design of our cryogenic FMCW interferometer. Applications of cryogenic range resolved interferometry are discussed, with a focus on the integration of the FMCW interferometer with a custom 3-axis cryogenic accelerometer.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score0.999

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)0.0020.000

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 head0.244
Teacher spread0.220 · 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.

Study designOther design
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

Citations3
Published2022
Admission routes1
Has abstractyes

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