Seasonal variation of atmospheric muons in IceCube

Dennis Soldin; Paolo Desiati (for the IceCube Collaboration); Serap Tilav; Thomas K. Gaisser

Seasonal variation of atmospheric muons in IceCube

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 1909.01406 v1 pith:VOI5IBYB submitted 2019-09-03 astro-ph.HE

Serap Tilav , Thomas K. Gaisser , Dennis Soldin , Paolo Desiati (for the IceCube Collaboration) This is my paper · ORCID

classification astro-ph.HE

keywords analysisatmosphericdataicecubemuonsrateseasonalvariations

verification ladder T0 review T1 audit T2 compute T3 formal

0 comments

read the original abstract

After more than seven years of data taking with the full IceCube detector triggering at an average rate of 2.15 kHz, a sample of half a trillion muon events is available for analysis. The extreme temperature variations in the stratosphere together with the high data rate reveal features on both long and short time scales with unprecedented precision. In this paper we report an analysis in terms of the atmospheric profile for production of muons from decay of charged pions and kaons. We comment on the implications for seasonal variations of neutrinos, which are presented in a separate paper at this conference.

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

Using Cosmic Rays to Predict the Weather: Meteorological Data Assimilation of Atmospheric Muon Flux Data
physics.ao-ph 2025-09 conditional novelty 7.0 of 10

Simulated cosmic-ray muon counts, assimilated into an ensemble weather model, improve short-range forecasts of a tropical cyclone beyond what a single surface pressure measurement provides.

Pith tools