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Record W4399663344 · doi:10.1117/12.3020642

GPI 2.0: upgrade status of the Gemini Planet Imager

2024· article· en· W4399663344 on OpenAlexaff
Jeffrey Chilcote, Quinn Konopacky, Randall Hamper, Bruce Macintosh, Christian Marois, Dmitry Savransky, Rémi Soummer, Jean‐Pierre Véran, Guido Agapito, Arlene Aleman, Marco Bonaglia, Marc-André Boucher, Joel Burke, Vincent Chambouleyron, Robert J. De Rosa, Clarissa Do Ó, Jennifer Dunn, Matthew Engstrom, Simone Esposito, Guillaume Filion, Joeleff Fitzsimmons, Oyku Galvan, Daniel A. Kerley, Jean-Thomas Landry, Olivier Lardière, Daniel Levinstein, Mary Anne Limbach, Jérôme Maîre, Anna Matzner, Teo Močnik, Bryony Nickson, E. Nielsen, Jayke S. Nguyen, Meiji M. Nguyen, Saavidra Perera, Dillon Peng, Marshall D. Perrin, Emiel H. Por, Laurent Pueyo, Carlos Quiroz, Fredrik T. Rantakyrö, Brian Sands, Andreas Seifahrt, Garima Singh, Ed Wolf

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAstronomical Observations and Instrumentation
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsUpgradePlanetAstrobiologyComputer scienceAstronomyPhysicsOperating system

Abstract

fetched live from OpenAlex

The Gemini Planet Imager (GPI) is a dedicated high-contrast imaging facility instrument. After six years, GPI has helped establish that the occurrence rate of Jovian planets peaks near the snow. GPI 2.0 is expected to achieve deeper contrasts, especially at small inner working angles, to extend GPI’s operating range to fainter stars, and to broaden its scientific capabilities. GPI shipped from Gemini South in 2022 and is undergoing an upgrade as part of a relocation to Gemini North. We present the status of the upgrades including replacing the current wavefront sensor with an EMCCD-based pyramid wavefront sensor, adding a broadband low spectral resolution prism, new apodized-pupil Lyot coronagraph designs, upgrades of the calibration wavefront sensor and increased queue operability. Further we discuss the progress of reintegrating these components into the new system and the expected performance improvements in the context of GPI 2.0’s enhanced science capabilities.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.005
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.009

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 head0.007
GPT teacher head0.194
Teacher spread0.187 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations4
Published2024
Admission routes1
Has abstractyes

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Same topicAstronomical Observations and InstrumentationFrench-language works237,207