Pith. sign in

REVIEW 1 cited by

21 cm Intensity Mapping

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 0902.3091 v1 pith:ZB4BE2R5 submitted 2009-02-18 astro-ph.IM astro-ph.CO

21 cm Intensity Mapping

Jeffrey B. Peterson , Roy Aleksan , Reza Ansari , Kevin Bandura , Dick Bond , John Bunton , Kermit Carlson , Tzu-Ching Chang
show 32 more authors
Fritz DeJongh Matt Dobbs Scott Dodelson Hassane Darhmaoui Nick Gnedin Mark Halpern Craig Hogan Jean-Marc Le Goff Tiehui Ted Liu Ahmed Legrouri Avi Loeb Khalid Loudiyi Christophe Magneville John Marriner David P. McGinnis Bruce McWilliams Marc Moniez Nathalie Palanque-Delabruille Ralph J. Pasquinelli Ue-Li Pen Jim Rich Vic Scarpine Hee-Jong Seo Kris Sigurdson Uros Seljak Albert Stebbins Jason H. Steffen Chris Stoughton Peter T. Timbie Alberto Vallinotto Stuart Wyithe Christophe Yeche
This is my paper
classification astro-ph.IM astro-ph.CO
keywords largeacrossdataintensityrangeredshiftscalestructure
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

Using the 21 cm line, observed all-sky and across the redshift range from 0 to 5, the large scale structure of the Universe can be mapped in three dimensions. This can be accomplished by studying specific intensity with resolution ~ 10 Mpc, rather than via the usual galaxy redshift survey. The data set can be analyzed to determine Baryon Acoustic Oscillation wavelengths, in order to address the question: 'What is the nature of Dark Energy?' In addition, the study of Large Scale Structure across this range addresses the questions: 'How does Gravity effect very large objects?' and 'What is the composition our Universe?' The same data set can be used to search for and catalog time variable and transient radio sources.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Deep learning with hybrid frequency differencing and principal component analysis for 21-cm foreground and beam mitigation

    astro-ph.CO 2025-11 conditional novelty 5.0

    A two-channel UNet combining frequency differencing and PCA preprocessing recovers the 21-cm HI power spectrum at large scales under realistic beam effects, improving cross-correlation by 5-8% over single-channel baselines.