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Record W4399437884 · doi:10.1117/12.3021377

The LiteBIRD mission to explore cosmic inflation

2024· article· en· W4399437884 on OpenAlexfundno aff
T. Ghigna, Alexander Adler, Kosuke Aizawa, Hiroki Akamatsu, Ryosuke Akizawa, Erwan Allys, Avinash Anand, J. Aumont, Jason E. Austermann, S. Azzoni, C. Baccigalupi, M. Ballardini, A. J. Banday, R. B. Barreiro, Nicola Bartolo, S. Basak, A. Basyrov, Shawn Beckman, Marco Bersanelli, Marco Bortolami, F. R. Bouchet, T. Brinckmann, P. Campeti, E. Carinos, A. Carones, F. J. Casas, K. Cheung, Y. Chinone, Lionel Clermont, Fabio Columbro, A. Coppolecchia, D. Curtis, Paolo de Bernardis, T. de Haan, E. de la Hoz, M. De Petris, S. Della Torre, G. Delle Monache, E. Di Giorgi, C. Dickinson, P. Diego-Palazuelos, Jose Díaz García, M. Dobbs, Tadayasu Dotani, H. K. Eriksen, Josquin Errard, Thomas Essinger-Hileman, Nicole Farias, Elisa G. M. Ferreira, C. Franceschet, U. Fuskeland, G. Galloni, M. Galloway, K. Ganga, M. Gerbino, M. Gervasi, Ricardo Génova-Santos, S. Giardiello, C. Gimeno-Amo, Eirik Gjerløw, R. González González, L. Grandsire, A. Gruppuso, N. W. Halverson, Peter Hargrave, Stuart Harper, M. Hazumi, Sophie Henrot-Versillé, L. T. Hergt, D. Herranz, E. Hivon, Renée Hložek, Johannes Hubmayr, Kiyotomo Ichiki, Kiyoshi Ikuma, H. Ishino, Gregory Jaehnig, Baptiste Jost, Kazunori Kohri, Kuniaki Konishi, Luca Lamagna, M. Lattanzi, C. Leloup, François Levrier, Anto Lanoppan, Gemma Luzzi, J. F. Macías–Pérez, B. Maffei, Elisabetta Marchitelli, Enrique Martínez-González, S. Masi, S. Matarrese, T. Matsumura, S. Micheli, M. Migliaccio, M. Monelli, Ludovic Montier, G. Morgante, L. Mousset, Y. Nagano, Ryo Nagata, Paolo Natoli, Alessandro Novelli, F. Noviello, Ippei Obata, Andrea Occhiuzzi, Kimihide Odagiri, R. Omae, L. Pagano, A. Paiella, D. Paoletti, G Pascual-Cisneros, Guillaume Patanchon, V. Pavlidou, F. Piacentini, Michel Piat, G. Piccirilli, Michele Pinchera, G. Pisano, L. Porcelli, N. Raffuzzi, Christopher Raum, M. Remazeilles, A. Ritacco, J. A. Rubiño-Martín, M. Ruiz-Granda, Y. Sakurai, Giorgio Savini, D. Scott, Yutaro Sekímoto, Maresuke Shiraishi, G. Signorelli, S. L. Stever, R. M. Sullivan, Aritoki Suzuki, Ryota Takaku, Hayato Takakura, S. Takakura, Yusuke Takase, A. Tartari, Konstantinos Tassis, K. L. Thompson, Maurizio Tomasi, M. Tristram, C. Tucker, L. Vacher, B. Van Tent, P. Vielva, Kazuya Watanuki, I. K. Wehus, Benjamin Westbrook, G. Weymann-Despres, Berend Winter, Edward J. Wollack, A. Zacchei, M. Zannoni, Y. Zhou

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsnot available
FundersNuclear PhysicsAgencia Estatal de InvestigaciónScience and Technology Facilities CouncilCanadian Space AgencyJapan Society for the Promotion of ScienceNorges ForskningsrådIstituto Nazionale di AstrofisicaCentre National de la Recherche ScientifiqueMinistry of Education, Culture, Sports, Science and TechnologyCentre National d’Etudes SpatialesCentro para el Desarrollo Tecnológico IndustrialVetenskapsrådetSwedish National Space AgencyNational Aeronautics and Space AdministrationJapan Aerospace Exploration AgencyAbdus Salam International Centre for Theoretical PhysicsEuropean CommissionNuclear Safety and Security CommissionDeutsche Forschungsgemeinschaft
KeywordsCosmic microwave backgroundPhysicsSkyCosmologyAstrophysicsCosmic background radiationCOSMIC cancer databaseAstronomyAerospace engineeringOpticsEngineering

Abstract

fetched live from OpenAlex

LiteBIRD, the next-generation cosmic microwave background (CMB) experiment, aims for a launch in Japan's fiscal year 2032, marking a major advancement in the exploration of primordial cosmology and fundamental physics. Orbiting the Sun-Earth Lagrangian point L2, this JAXA-led strategic L-class mission will conduct a comprehensive mapping of the CMB polarization across the entire sky. During its 3-year mission, LiteBIRD will employ three telescopes within 15 unique frequency bands (ranging from 34 through 448 GHz), targeting a sensitivity of 2.2\,$μ$K-arcmin and a resolution of 0.5$^\circ$ at 100\,GHz. Its primary goal is to measure the tensor-to-scalar ratio $r$ with an uncertainty $δr = 0.001$, including systematic errors and margin. If $r \geq 0.01$, LiteBIRD expects to achieve a $>5σ$ detection in the $\ell=$2-10 and $\ell=$11-200 ranges separately, providing crucial insight into the early Universe. We describe LiteBIRD's scientific objectives, the application of systems engineering to mission requirements, the anticipated scientific impact, and the operations and scanning strategies vital to minimizing systematic effects. We will also highlight LiteBIRD's synergies with concurrent CMB projects.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.941
Threshold uncertainty score0.410

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 head0.027
GPT teacher head0.277
Teacher spread0.251 · 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 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

Citations5
Published2024
Admission routes1
Has abstractyes

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