Elemental Composition and Energy Spectra of Galactic Cosmic Rays During Solar Cycle 23

George, Jimin; Lave, K. A.; Wiedenbeck, M. E.; Binns, W. R.; Cummings, A. C.; Davis, A. J.; Nolfo, G. A. de; Hink, P. L.; Israel, M. H.; Leske, R. A.; Mewaldt, R. A.; Scott, L. M.; Stone, E. C.; Rosenvinge, T. T. von; Yanasak, N. E.

doi:10.1088/0004-637x/698/2/1666

Cited by 121 publications

(131 citation statements)

References 26 publications

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“…3, we have analysed the fluxes of primary cosmic rays in diffusion models with particular attention to p and He. The most recent data on p and He are well reproduced by a purely diffusive model, described by power-law source (Ahn et al 2008(Ahn et al , 2010a, CRN (Swordy et al 1990;Mueller et al 1991), HEAO-3 (Engelmann et al 1990), TRACER (Ave et al 2008(Ave et al , 2009, and low-energy ACE data (George et al 2009). spectrum, isotropic diffusion coefficient, spallative destructions and electromagnetic energy losses. This conclusion holds for single data sets but it is not reproduced in a combined data analysis (except for AMS01 and BESS98 proton data), due to the mean level of consistency among the different data collections.…”

Section: Discussionmentioning

confidence: 83%

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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Section: Discussionmentioning

confidence: 83%

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

Putze

Maurin

Donato

2011

A&A

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“…Low-energy data points include ACE data, taken during the solar minimum period 1997−1998(de Nolfo et al 2006. Close to submission of this paper, another ACE analysis was published (George et al 2009 Off-diagonal plots show the 2D marginalised posterior PDFs for the parameters in the same column and same line respectively. The colour code corresponds to the regions of increasing probability (from paler to darker shade), and the two contours (smoothed) delimit regions containing, respectively, 68% and 95% (inner and outer contour) of the PDF.…”

Section: Sensitivity To the Choice Of The B/c Datasetmentioning

confidence: 99%

A Markov Chain Monte Carlo technique to sample transport and source parameters of Galactic cosmic rays

Putze

Derome

Maurin

2010

A&A

150

191

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Context. Ongoing measurements of the cosmic radiation (nuclear, electronic, and γ-ray) are providing additional insight into cosmicray physics. A comprehensive picture of these data relies on an accurate determination of the transport and source parameters of propagation models. Aims. A Markov Chain Monte Carlo method is used to obtain these parameters in a diffusion model. By measuring the B/C ratio and radioactive cosmic-ray clocks, we calculate their probability density functions, placing special emphasis on the halo size L of the Galaxy and the local underdense bubble of size r h . We also derive the mean, best-fit model parameters and 68% confidence level for the various parameters, and the envelopes of other quantities. Methods. The analysis relies on the USINE code for propagation and on a Markov Chain Monte Carlo technique previously developed by ourselves for the parameter determination. Results. The B/C analysis leads to a most probable diffusion slope δ = 0.86 +0.04 −0.04 for diffusion, convection, and reacceleration, or δ = 0.234 +0.006 −0.005 for diffusion and reacceleration. As found in previous studies, the B/C best-fit model favours the first configuration, hence pointing to a high value for δ. These results do not depend on L, and we provide simple functions to rescale the value of the transport parameters to any L. A combined fit on B/C and the isotopic ratios ( 10 Be/ 9 Be, 26 Al/ 27 Al, 36 Cl/Cl) leads to L = 8 +8 −7 kpc and r h = 120 +20 −20 pc for the best-fit model. This value for r h is consistent with direct measurements of the local interstallar medium. For the model with diffusion and reacceleration, L = 4 +1 −1 kpc and r h = 3 +70 −3 pc (consistent with zero). We vary δ, because its value is still disputed. For the model with Galactic winds, we find that between δ = 0.2 and 0.9, L varies from O(0) to O(2) if r h is forced to be 0, but it otherwise varies from O(0) to O(1) (with r h ∼ 100 pc for all δ > ∼ 0.3). The results from the elemental ratios Be/B, Al/Mg, and Cl/Ar do not allow independent checks of this picture because these data are not precise enough. Conclusions. We showed the potential and usefulness of the Markov Chain Monte Carlo technique in the analysis of cosmic-ray measurements in diffusion models. The size of the diffusive halo depends crucially on the value of the diffusion slope δ, and also on the presence/absence of the local underdensity damping effect on radioactive nuclei. More precise data from ongoing experiments are expected to clarify this issue.

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“…George et al (2009) compared the composition of galactic cosmic rays with the solar system constituents and reported similar relative abundances except at Z = 3-5, 9-10, and 19-25. The mass composition of CRs at ultra high energy is still under debate (Kudela 2009) and precise measurements of the CR composition in the energy interval 10 16 eV \ E \ 10 19 eV is required to determine the transition from galactic to extra-galactic CR components.…”

Section: Galactic Cosmic Raysmentioning

confidence: 90%

Space Weather: Physics, Effects and Predictability

2010

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The time varying conditions in the near-Earth space environment that may affect space-borne or ground-based technological systems and may endanger human health or life are referred to as space weather. Space weather effects arise from the dynamic and highly variable conditions in the geospace environment starting from explosive events on the Sun (solar flares), Coronal Mass Ejections near the Sun in the interplanetary medium, and various energetic effects in the magnetosphere-ionosphere-atmosphere system. As the utilization of space has become part of our everyday lives, and as our lives have become increasingly dependent on technological systems vulnerable to the space weather influences, the understanding and prediction of hazards posed by these active solar events have grown in importance. In this paper, we review the processes of the Sun-Earth interactions, the dynamic conditions within the magnetosphere, and the predictability of space weather effects on radio waves, satellites and ground-based technological systems today.

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Elemental Composition and Energy Spectra of Galactic Cosmic Rays During Solar Cycle 23

Cited by 121 publications

References 26 publications

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

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

A Markov Chain Monte Carlo technique to sample transport and source parameters of Galactic cosmic rays

Space Weather: Physics, Effects and Predictability

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