Measurements of primary and atmospheric cosmic-ray spectra with the BESS-TeV spectrometer

Haino, S.; Sanuki, T.; Abe, K.; Anraku, K.; Asaoka, Y.; Fuke, H.; Imori, M.; Itasaki, A.; Maeno, T.; Makida, Y.; Matsuda, Shinya; Matsui, N.; Matsumoto, H.; Mitchell, J. W.; Моисеев, А. А.; Nishimura, Jun; Nozaki, M.; Orito, S.; Ormes, J. F.; Sasaki, M.; Seo, E. S.; Shikaze, Y.; Streitmatter, R. E.; Suzuki, Jun–ichi; Takasugi, Y.; Tanaka, Kenichi; Tanizaki, K.; Yamagami, T.; Yamamoto, A.; Yamamoto, Y.; Yamato, Kazuhiro; Yoshida, Tetsuya; Yoshimura, K.

doi:10.1016/j.physletb.2004.05.019

Cited by 254 publications

(203 citation statements)

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“…For the primary flux model, we take the same primary flux model as HKKM04, based on AMS [12,13] and BESS [4,14] data, with a spectral index of −2.71 above 100 GeV (see also Refs. [15,16]).…”

Section: Calculation Of Atmospheric Neutrino Fluxmentioning

confidence: 99%

“…In the previous paper [1] (hereafter Paper I), we have studied the interaction model (DPMJET-III [3]) employed in the HKKM04 atmospheric neutrino flux calculation [2], using the atmospheric muon flux data observed by precision measurements [4,5,6]. In the study, we found that the calculated and observed muon fluxes did not agree, especially for momenta above 30 GeV/c.…”

Section: Introductionmentioning

confidence: 99%

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Calculation of atmospheric neutrino flux using the interaction model calibrated with atmospheric muon data

et al. 2007

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Using the "modified DPMJET-III" model explained in the previous paper [1], we calculate the atmospheric neutrino flux. The calculation scheme is almost the same as HKKM04 [2], but the usage of the "virtual detector" is improved to reduce the error due to it. Then we study the uncertainty of the calculated atmospheric neutrino flux summarizing the uncertainties of individual components of the simulation. The uncertainty of K-production in the interaction model is estimated using other interaction models: FLUKA'97 and Fritiof 7.02, and modifying them so that they also reproduce the atmospheric muon flux data correctly. The uncertainties of the flux ratio and zenith angle dependence of the atmospheric neutrino flux are also studied.

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Section: Calculation Of Atmospheric Neutrino Fluxmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Calculation of atmospheric neutrino flux using the interaction model calibrated with atmospheric muon data

et al. 2007

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“…2 to illustrate the error bars and differences between the most recent and consistent sets of p and He data, namely AMS-01 AMS Collaboration et al 2000), BESS98 (Sanuki et al 2000;Shikaze et al 2007) and BESS-TeV (a.k.a. BESS02, Haino et al 2004;Shikaze et al 2007). For the proton flux, the AMS-01 and BESS98 data, both taken in 1998 in the same solar period, are consistent except at low energy.…”

Section: Datamentioning

confidence: 99%

p, He, and C to Fe cosmic-ray primary fluxes in diffusion models

Putze

Maurin

Donato

2011

A&A

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Context. The source spectrum of cosmic rays is not well determined by diffusive shock acceleration models. The propagated fluxes of proton, helium, and heavier primary cosmic-ray species (up to Fe) are a means to indirectly access it. But how robust are the constraints, and how degenerate are the source and transport parameters? Aims. We check the compatibility of the primary fluxes with the transport parameters derived from the B/C analysis, but also ask whether they add further constraints. We study whether the spectral shapes of these fluxes and their ratios are mostly driven by source or propagation effects. We then derive the source parameters (slope, abundance, and low-energy shape). Methods. Simple analytical formulae are used to address the issue of degeneracies between source/transport parameters, and to understand the shape of the p/He and C/O to Fe/O data. The full analysis relies on the USINE propagation package, the MINUIT minimisation routines (χ 2 analysis) and a Markov Chain Monte Carlo (MCMC) technique. Results. Proton data are well described in the simplest model defined by a power-law source spectrum and plain diffusion. They can also be accommodated by models with, e.g., convection and/or reacceleration. There is no need for breaks in the source spectral indices below ∼1 TeV/n. Fits to the primary fluxes alone do not provide physical constraints on the transport parameters. If we leave the source spectrum free, parametrised by the form dQ/dE = qβ η S R −α , and fix the diffusion coefficient K(R) = K 0 β η T R δ so as to reproduce the B/C ratio, the MCMC analysis constrains the source spectral index α to be in the range 2.2−2.5 for all primary species up to Fe, regardless of the value of the diffusion slope δ. The values of the parameter η S describing the low-energy shape of the source spectrum are degenerate with the parameter η T describing the low-energy shape of the diffusion coefficient: we find η S − η T ≈ 0 for p and He data, but η S − η T ≈ 1 for C to Fe primary species. This is consistent with the toy-model calculation in which the shape of the p/He and C/O to Fe/O data is reproduced if η S − η T ≈ 0−1 (no need for different slopes α). When plotted as a function of the kinetic energy per nucleon, the low-energy p/He ratio is determined mostly by the modulation effect, whereas primary/O ratios are mostly determined by their destruction rate. Conclusions. Models based on fitting B/C are compatible with primary fluxes. The different spectral indices for the propagated primary fluxes up to a few TeV/n can be naturally ascribed to transport effects only, implying universality of elemental source spectra.

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“…We thus begin by finding the values of the nucleon source parameters that best fit this data. We use the GALPROP default spatial distribution for nucleon sources and tune the overall JHEP01(2011)064 normalization and spectral index (i.e., the exponent of the power-law describing the energydependence of the sources) of these sources to best fit measurements of the proton absolute spectrum from BESS/BESS-TeV [60,64], AMS-01 [65], CAPRICE98 [66] and ATIC [67]. It is clear that the data favor a (locally-measured) spectral index of ≈ 2.75 ± 0.05, though the ATIC points stiffen somewhat above ∼ 1 TeV; including all four data sets, we find a best fit spectral index of γ n = 2.73 and normalization 3.96 × 10 −6 GeV −1 cm −2 sr −1 s −1 @ 100 GeV.…”

Section: Nucleon Source and Turbulent Diffusion Parametersmentioning

confidence: 99%

Cosmic ray anomalies from the MSSM?

Cotta

Conley

Gainer

et al. 2011

J. High Energ. Phys.

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Abstract:The recent positron excess in cosmic rays (CR) observed by the PAMELA satellite may be a signal for dark matter (DM) annihilation. When these measurements are combined with those from FERMI on the total (e + + e − ) flux and from PAMELA itself on thep/p ratio, these and other results are difficult to reconcile with traditional models of DM, including the conventional mSUGRA version of Supersymmetry even if boosts as large as 10 3−4 are allowed. In this paper, we combine the results of a previously obtained scan over a more general 19-parameter subspace of the MSSM with a corresponding scan over astrophysical parameters that describe the propagation of CR. We then ascertain whether or not a good fit to this CR data can be obtained with relatively small boost factors while simultaneously satisfying the additional constraints arising from gamma ray data. We find that a specific subclass of MSSM models where the LSP is mostly pure bino and annihilates almost exclusively into τ pairs comes very close to satisfying these requirements. The lightestτ in this set of models is found to be relatively close in mass to the LSP and is in some cases the nLSP. These models lead to a significant improvement in the overall fit to the data by an amount ∆χ 2 ∼ 1/dof in comparison to the best fit without Supersymmetry while employing boosts ∼ 100. The implications of these models for future experiments are discussed.

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Measurements of primary and atmospheric cosmic-ray spectra with the BESS-TeV spectrometer

Cited by 254 publications

References 28 publications

Calculation of atmospheric neutrino flux using the interaction model calibrated with atmospheric muon data

Calculation of atmospheric neutrino flux using the interaction model calibrated with atmospheric muon data

p, He, and C to Fe cosmic-ray primary fluxes in diffusion models

Cosmic ray anomalies from the MSSM?

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