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Record W4293282717 · doi:10.1117/12.2630159

GPI 2.0: upgrade status of the Gemini Planet Imager

2022· article· en· W4293282717 on OpenAlexaff
Jeffrey Chilcote, Quinn Konopacky, Joeleff Fitzsimmons, Randall Hamper, Bruce Macintosh, Christian Marois, Dmitry Savransky, Rémi Soummer, Jean‐Pierre Véran, Guido Agapito, Arlene Aleman, S. Mark Ammons, Marco Bonaglia, Marc-André Boucher, Maeve Curliss, Robert J. De Rosa, Clarissa R. Do Ó, Jennifer Dunn, Simone Esposito, Guillaume Filion, Daniel A. Kerley, Jean-Thomas Landry, Olivier Lardière, Daniel Levinstein, Duan Li, Mary Anne Limbach, Alex Madurowicz, Jérôme Maîre, Maxwell A. Millar‐Blanchaer, Bryony Nickson, E. Nielsen, Jayke S. Nguyen, Meiji M. Nguyen, Dillon Peng, Saavidra Perera, Marshall D. Perrin, Emiel H. Por, Lisa Poyneer, Laurent Pueyo, Fredrik T. Rantakyrö, Brian Sands, Eckhart Spalding, Kaitlyn Summey

Bibliographic record

VenueGround-based and Airborne Instrumentation for Astronomy IX · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of VictoriaHerzberg Institute of Astrophysics
Fundersnot available
KeywordsUpgradeExoplanetPlanetCoronagraphWavefrontOperabilityApodizationComputer scienceJovianPhysicsOpticsBroadbandRemote sensingAerospace engineeringAstronomyGeologyEngineeringOperating system

Abstract

fetched live from OpenAlex

GPI is a facility instrument designed for the direct detection and characterization of young Jupiter mass exoplanets. GPI has helped establish that the occurrence rate of Jovian planets peaks near the snow line (~3 AU), and falls off toward larger separations. This motivates an upgrade of GPI 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, all while leveraging its historical success. GPI was packed and shipped in 2022, and is undergoing a major science-driven upgrade. We present the status and purpose of the upgrades including an EMCCD-based pyramid wavefront sensor, broadband low spectral resolution prisms, new apodized-pupil Lyot coronagraph designs, upgrades of the calibration wavefront sensor and increased queue operability. We discuss the expected performance improvements and enhanced science capabilities to be made available in 2024.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.624

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)0.0010.000

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 head0.011
GPT teacher head0.225
Teacher spread0.215 · 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 designObservational
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

Explore more

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