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Record W4391514904 · doi:10.48550/arxiv.2401.17945

Euclid preparation XLVI. The Near-IR Background Dipole Experiment with Euclid

2024· preprint· en· W4391514904 on OpenAlexaff
Euclid Collaboration, A. Kashlinsky, Richard G. Arendt, M. L. N. Ashby, F. Atrio‐Barandela, R. Scaramella, Michael A. Strauss, B. Altieri, A. Amara, S. Andreon, N. Auricchio, Marco Baldi, S. Bardelli, R. Bender, C. Bodendorf, E. Branchini, M. Brescia, J. Brinchmann, S. Camera, V. Capobianco, C. Carbone, J. Carretero, Santiago Casas, M. Castellano, S. Cavuoti, A. Cimatti, G. Congedo, Christopher J. Conselice, L. Conversi, Y. Copin, L. Corcione, F. Courbin, H. M. Courtois, A. Da Silva, H. Degaudenzi, A. M. Di Giorgio, J. Dinis, F. Dubath, X. Dupac, S. Dusini, A. Ealet, M. Farina, S. Farrens, S. Ferriol, M. Frailis, E. Franceschi, S. Galeotta, B. Gillis, C. Giocoli, A. Grazian, F. Grupp, S. V. H. Haugan, I. Hook, F. Hormuth, A. Hornstrup, K. Jahnkę, E. Keihänen, S. Kermiche, A. Kiessling, M. Kilbinger, B. Kubik, M. Kunz, H. Kurki‐Suonio, S. Ligori, P. B. Lilje, V. Lindholm, I. Lloro, D. Maino, E. Maiorano, O. Mansutti, O. Marggraf, K. Markovič, N. Martinet, F. Marulli, R. Massey, S. Maurogordato, H. J. McCracken, E. Medinaceli, S. Mei, Y. Mellier, M. Meneghetti, G. Meylan, M. Moresco, L. Moscardini, E. Munari, S. -M. Niemi, S. Paltani, F. Pasian, K. Pedersen, Will J. Percival, S. Pires, G. Polenta, M. Poncet, L. A. Popa, F. Raison, A. Renzi, J. Rhodes, G. Riccio, E. Romelli, M. Roncarelli, E. Rossetti, R. P. Saglia, D. Sapone, B. Sartoris, M. Schirmer, P. Schneider, T. Schrabback, A. Secroun, G. Seidel, M. D. Seiffert, S. Serrano, C. Sirignano, G. Sirri, L. Stančo, P. Tallada-Crespí, A. N. Taylor, Harry I. Teplitz, I. Tereno, R. Toledo-Moreo, F. Torradeflot, I. Tutusaus, L. Valenziano, T. Vassallo, A. Veropalumbo, Yun Wang, G. Zamorani, J. Zoubian, E. Zucca, A. Biviano, E. Bozzo, C. Burigana, C. Colodro-Conde, D. Di Ferdinando, Giulio Fabbian, R. Farinelli, J. Graciá-Carpio, G Mainetti, M. Martinelli, N. Mauri, C. Neissner, Z. Sakr, V Scottez, M. Tenti, Matteo Viel, M. Wiesmann, Y. Akrami, V. Allevato, S Anselmi, C. Baccigalupi, M. Ballardini, Alain Blanchard, S. Borgani, Alejandro S. Borlaff, S Bruton, R. Cabanac, A. Cappi, C. S. Carvalho, G. Castignani, T. Castro, G. Ca nas-Herrera, K. C. Chambers, S. Contarini, J. Coupon, G. De Lucia, G. Desprez, S. Di Domizio, H. Dole, A. Díaz‐Sánchez, J.A. Escartin Vigo, I. Ferrero, F. Finelli⋆, L. Gabarra, J. García-Bellido, V Gautard, E. Gaztañaga, K George, F. Giacomini, G. Gozaliasl, A. Gregorio, A Hall, H. Hildebrandt, J. J. E. Kajava, V. Kansal, C.C Kirkpatrick, L. Legrand, A. Loureiro, M. Magliocchetti, F. Mannucci, C. J. A. P. Martins, S Matthew, L. Maurin, R. B. Metcalf, M. Migliaccio, Pierluigi Monaco, G. Morgante, S. Nadathur, N. A. Walton, L. Patrizii, V. Popa, D. Potter, M. Pöntinen, P.-F Rocci, M Sahlén, Aurel Schneider, E. Sefusatti, M. Sereno, J. Steinwagner, G. Testera, Romain Teyssier, Sune Toft, S. Tosi, A. Troja, J. Väliviita, D. Vergani, G Verza, G. Hasinger

Bibliographic record

VenuearXiv (Cornell University) · 2024
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsSaint Mary's UniversityPerimeter InstituteUniversity of Waterloo
FundersIntegrated Electronics Engineering Center, Binghamton UniversityCentro de Investigaciones Energéticas, Medioambientales y TecnológicasEuropean Regional Development FundStaatssekretariat für Bildung, Forschung und InnovationAgencia Estatal de InvestigaciónFundação para a Ciência e a TecnologiaGoddard Space Flight CenterNational Astronomical Observatory of JapanInstitut de Física d'Altes EnergiesNorsk RomsenterAgenția Spațială RomânăScience and Technology Facilities CouncilEuropean Space AgencyAgenzia Spaziale ItalianaJunta de Castilla y LeónNational Aeronautics and Space Administration
KeywordsCosmic microwave backgroundPhysicsAstrophysicsGalaxyDipoleCosmologyAstronomyCosmic background radiationKinematicsCOSMIC cancer databaseClassical mechanicsQuantum mechanics

Abstract

fetched live from OpenAlex

Verifying the fully kinematic nature of the cosmic microwave background (CMB) dipole is of fundamental importance in cosmology. In the standard cosmological model with the Friedman-Lemaitre-Robertson-Walker (FLRW) metric from the inflationary expansion the CMB dipole should be entirely kinematic. Any non-kinematic CMB dipole component would thus reflect the preinflationary structure of spacetime probing the extent of the FLRW applicability. Cosmic backgrounds from galaxies after the matter-radiation decoupling, should have kinematic dipole component identical in velocity with the CMB kinematic dipole. Comparing the two can lead to isolating the CMB non-kinematic dipole. It was recently proposed that such measurement can be done using the near-IR cosmic infrared background (CIB) measured with the currently operating Euclid telescope, and later with Roman. The proposed method reconstructs the resolved CIB, the Integrated Galaxy Light (IGL), from Euclid's Wide Survey and probes its dipole, with a kinematic component amplified over that of the CMB by the Compton-Getting effect. The amplification coupled with the extensive galaxy samples forming the IGL would determine the CIB dipole with an overwhelming signal/noise, isolating its direction to sub-degree accuracy. We develop details of the method for Euclid's Wide Survey in 4 bands spanning 0.6 to 2 mic. We isolate the systematic and other uncertainties and present methodologies to minimize them, after confining the sample to the magnitude range with negligible IGL/CIB dipole from galaxy clustering. These include the required star-galaxy separation, accounting for the extinction correction dipole using the method newly developed here achieving total separation, accounting for the Earth's orbital motion and other systematic effects. (Abridged)

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.442
Threshold uncertainty score0.796

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.4420.331

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 head0.056
GPT teacher head0.234
Teacher spread0.178 · 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.

Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations1
Published2024
Admission routes1
Has abstractyes

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