Pith. sign in

REVIEW 1 cited by

An excess of non-Gaussian fluctuations in the cosmic infrared background consistent with gravitational lensing

Not yet reviewed by Pith; the record is open.

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 1905.02084 v1 pith:SS5I5NLZ submitted 2019-05-06 astro-ph.CO

classification astro-ph.CO
keywords lensingbackgroundcosmicdataconsistentdetectestimateexcess
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
abstract

The cosmic infrared background (CIB) is gravitationally lensed. A quadratic-estimator technique that is inherited from lensing analyses of the cosmic microwave background (CMB) can be applied to detect the CIB lensing effects. However, the CIB fluctuations are intrinsically strongly non-Gaussian, making CIB lensing reconstruction highly biased. We perform numerical simulations to estimate the intrinsic non-Gaussianity and establish a cross-correlation approach to precisely extract the CIB lensing signal from raw data. We apply this technique to CIB data from the Planck satellite and cross-correlate the resulting lensing estimate with the CIB data, galaxy number counts and the CMB lensing potential. We detect an excess that is consistent with a lensing contribution at $>4\sigma$.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

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

  1. Bias to CMB lensing from lensed foregrounds

    astro-ph.CO 2019-08 conditional novelty 7.0 of 10

    Lensed extragalactic foregrounds create a percent-level bias in CMB lensing estimators that is significant for upcoming Simons Observatory measurements and can be reduced by modified estimators.

Pith tools