Journal article
Tomographic constraints on the high-energy cosmic neutrino emission rate
- Abstract:
- Despite growing efforts to find the sources of high-energy neutrinos measured by IceCube, the bulk of the neutrinos remain with unknown origins. In this work, we aim to constrain the emissivity of cosmic high-energy neutrinos from extragalactic sources through their correlation with the large-scale structure. We use cross-correlations between the IceCube 10-year data set and tomographic maps of the galaxy overdensity to place constraints on the bias-weighted high-energy neutrino emissivity out to redshift . We test two different models to describe the evolution of neutrino emissivity with redshift, a power-law model , and a model tracking the star formation history, assuming a simple power-law model for the energy injection spectrum. We also consider a non-parametric reconstruction of the astrophysical neutrino emissivity as a function of redshift. We do not find any significant correlation, with our strongest results corresponding to a deviation with respect to a model with zero signal. We use our measurements to place upper bounds on the bias-weighted astrophysical high-energy neutrino emission rate as a function of redshift for different source models. This analysis provides a new probe to test extragalactic neutrino source models. With future neutrino and galaxy data sets, we expect the constraining and detection power of this type of analysis to increase.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 2.2MB, Terms of use)
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- Publisher copy:
- 10.1093/mnras/stag084
Authors
+ Swedish Research Council for Health Working Life and Welfare
More from this funder
- Funder identifier:
- https://ror.org/02d290r06
- Publisher:
- Oxford University Press
- Journal:
- Monthly Notices of the Royal Astronomical Society More from this journal
- Volume:
- 546
- Issue:
- 3
- Article number:
- stag084
- Publication date:
- 2026-01-14
- Acceptance date:
- 2025-12-28
- DOI:
- EISSN:
-
1365-2966
- ISSN:
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0035-8711
- Language:
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English
- Keywords:
- Pubs id:
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2370210
- UUID:
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uuid_8e63d22e-20c9-4864-a570-65bf997dac56
- Local pid:
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pubs:2370210
- Source identifiers:
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3721610
- Deposit date:
-
2026-02-03
- ARK identifier:
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Terms of use
- Copyright date:
- 2026
- Licence:
- CC Attribution (CC BY)
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