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Record W4399658220 · doi:10.1117/12.3020440

Small-ELF Telescope opto-mechanical system: progress on design, manufacturing, and tensegrity prototyping

2024· article· en· W4399658220 on OpenAlexaff
Ye Zhou, Timothy K. O. Lee, J. R. Kuhn, M de Oliveira, Ian Cunnyngham, S. M. Jefferies, M. Langlois, K. W. Lewis, N. Lodieu, Gil Moretto, R. Rébolo, Joe Ritter, Ryan Swindle, Sergio Salata, Ricardo Diego

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsDynamic Systems Analysis (Canada)
Fundersnot available
KeywordsRapid prototypingTensegrityTelescopeComputer scienceEngineeringAerospace engineeringMechanical engineeringPhysicsStructural engineeringOptics

Abstract

fetched live from OpenAlex

Small-ELF (SELF) is a 3.5-meter telescope currently entering the manufacturing phase and will serve as a technology precursor for the much larger telescope named ELF (Exo-Life Finder). The primary objective of the proposed design approach is to to radically improve the system’s capabilities for the detection of biomarkers and life in the atmospheres of exoplanets while keeping costs well below the current flagship observatories and thus maintaining cost-effectiveness. This is achieved through innovative approaches in motion and shape control, machine learning, and the integration of tensegrity techniques. SELF's manufacturing phase will commence in 2024-2025, with detailed design and manufacturing specifics outlined in this paper. To further mitigate technical risks, a small 0.25-meter prototype named MicroELF is also being designed and built in 2024. MicroELF incorporates the proposed optical and mechanical design to allow varying degrees of freedom for each component and utilizes distributed aperture principles akin to SELF. The degrees of freedom in MicroELF are controllable based on optical image feedback and a machine learning model. The paper details the optomechanical complexity of MicroELF, designed for successful construction and demonstration within 2024. SELF and MicroELF, as technology demonstrators, address prevalent cost and scalability challenges in existing telescopes, intending to introduce a novel paradigm in large telescope structural design.

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 score0.611
Threshold uncertainty score0.673

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 head0.032
GPT teacher head0.252
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.

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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