Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 376

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Antiprotons in cosmic rays from neutralino annihilation

Open access
Donato, F., Fornengo, N., Maurin, D., Salati, P., Taillet, R.·2004·Physical Review D

Abstract

We calculate the antiproton flux due to relic neutralino annihilations, in a two-dimensional diffusion model compatible with stable and radioactive cosmic ray nuclei. We find that the uncertainty in the primary flux induced by the propagation parameters alone is about two orders of magnitude at low energies, and it is mainly determined by the lack of knowledge of the thickness of the diffusive halo. On the contrary, different dark matter density profiles do not significantly alter the flux: a Novarro-Frenk-White distribution produces fluxes which are at most 20% higher than an isothermal sphere. The most conservative choice for propagation parameters and dark matter distribution normalization, together with current data on cosmic antiprotons, cannot lead to any definitive constraint on the supersymmetric parameter space, either in a low-energy effective minimal supersymmetric standard model, or in a minimal supergravity scheme. However, if the best choice for propagation parameters---corresponding to a diffusive halo of $L=4\mathrm{kpc}$---is adopted, some supersymmetric configurations with the neutralino mass ${m}_{\ensuremath{\chi}}\ensuremath{\lesssim}100\mathrm{GeV}$ should be considered as excluded. An enhancement flux factor---due for instance to a clumpy dark halo or a higher local dark matter density---would imply a more severe cut on the supersymmetric parameters.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1103/physrevd.69.063501

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 376

Metadata

Authors
Donato, F., Fornengo, N., Maurin, D., Salati, P., & Taillet, R.
Venue
Physical Review D
Published
2004-03-02
Volume
69
Issue
6
ISSN
  • 0556-2821 (ISSN-L)
  • 1550-7998
  • 1550-2368
OpenAlex
W2019889489
Cited by
376
References
4
FWCI
10.70
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.