On the Accuracy of Underground Muon Intensity Calculations
Anatoli Fedynitch,
William Woodley,
Marie-Cecile Piro
Abstract:Cosmic ray muons detected by deep underground or underwater detectors have served as an information source on the high-energy cosmic ray spectrum and hadronic interactions in air showers for almost a century. The theoretical interest in underground muons has nearly faded because space-borne experiments probe the cosmic ray spectrum more directly, and accelerators provide precise measurements of hadron yields. However, underground muons probe unique hadron interaction energies and phase space, which are still i… Show more
“…A difference of ∼ 20% to HKKMS is somewhat larger than expected. The description of fluxes in the TeV range by MCEq and DDM has been recently studied for underground muon intensities [44], and found to be in good agreement with vertical intensity data, and the error estimation of muon fluxes in DDM has been demonstrated to be realistic.…”
Section: B Muon and Electron Neutrino Fluxesmentioning
confidence: 82%
“…4, the caveat is that only 20−30% of muons observed at large depths originate from kaon decays (see Fig. 5 in [44]) in contrast to almost 80% of observed muon neutrinos. Under some soft model dependence, data-driven constraints from underground muons on very high energy conventional neutrino fluxes will have much lower uncertainties than estimates (such as [27]) that imply the complete absence of data from accelerators.…”
Section: Particle Production Phase Spacementioning
confidence: 97%
“…Fig. 7 in [44]). Flux "calibration" applications (such as [26,31]) would profit from underground muon rates measured as a function of the zenith angle and the slant depth in km.w.e., even if only a few bins are populated.…”
Section: Fluxes and Charge Ratios From Ddm A Muon Flux And Charge Ratiomentioning
confidence: 97%
“…To cover the IceCube energy range, the required muon energy at the surface is > 1 TeV. More related are muon fluxes or rates observed in deep underground detectors, which are known to much better precision than the few TeV-range measurements at the surface [44]. While there is full overlap between the deep underground contours in Fig.…”
Section: Particle Production Phase Spacementioning
confidence: 99%
“…As previously discussed, good collider constraints would come from air-shower specific measurements at LHCb in proton-oxygen runs [38]. An alternative source of constrains are atmospheric inclusive muons [26,31], deep underground muons [44,[60][61][62], seasonal variations [63,64] and atmospheric neutrinos [65].…”
The leading contribution to the uncertainties of atmospheric neutrino flux calculations arise from the cosmic ray nucleon flux and the production cross sections of secondary particles in hadron-air interactions. The data-driven model (DDM) developed in this work parametrizes particle yields from fixed-target accelerator data. The propagation of errors from the accelerator data to the inclusive muon and neutrino flux predictions results in smaller uncertainties than in previous estimates, and the description of atmospheric flux data is good. The model is implemented as part of the MCEq package, and hence can be flexibly employed for theoretical flux error estimation at neutrino telescopes.1 In high-energy physics such models are called event generators
“…A difference of ∼ 20% to HKKMS is somewhat larger than expected. The description of fluxes in the TeV range by MCEq and DDM has been recently studied for underground muon intensities [44], and found to be in good agreement with vertical intensity data, and the error estimation of muon fluxes in DDM has been demonstrated to be realistic.…”
Section: B Muon and Electron Neutrino Fluxesmentioning
confidence: 82%
“…4, the caveat is that only 20−30% of muons observed at large depths originate from kaon decays (see Fig. 5 in [44]) in contrast to almost 80% of observed muon neutrinos. Under some soft model dependence, data-driven constraints from underground muons on very high energy conventional neutrino fluxes will have much lower uncertainties than estimates (such as [27]) that imply the complete absence of data from accelerators.…”
Section: Particle Production Phase Spacementioning
confidence: 97%
“…Fig. 7 in [44]). Flux "calibration" applications (such as [26,31]) would profit from underground muon rates measured as a function of the zenith angle and the slant depth in km.w.e., even if only a few bins are populated.…”
Section: Fluxes and Charge Ratios From Ddm A Muon Flux And Charge Ratiomentioning
confidence: 97%
“…To cover the IceCube energy range, the required muon energy at the surface is > 1 TeV. More related are muon fluxes or rates observed in deep underground detectors, which are known to much better precision than the few TeV-range measurements at the surface [44]. While there is full overlap between the deep underground contours in Fig.…”
Section: Particle Production Phase Spacementioning
confidence: 99%
“…As previously discussed, good collider constraints would come from air-shower specific measurements at LHCb in proton-oxygen runs [38]. An alternative source of constrains are atmospheric inclusive muons [26,31], deep underground muons [44,[60][61][62], seasonal variations [63,64] and atmospheric neutrinos [65].…”
The leading contribution to the uncertainties of atmospheric neutrino flux calculations arise from the cosmic ray nucleon flux and the production cross sections of secondary particles in hadron-air interactions. The data-driven model (DDM) developed in this work parametrizes particle yields from fixed-target accelerator data. The propagation of errors from the accelerator data to the inclusive muon and neutrino flux predictions results in smaller uncertainties than in previous estimates, and the description of atmospheric flux data is good. The model is implemented as part of the MCEq package, and hence can be flexibly employed for theoretical flux error estimation at neutrino telescopes.1 In high-energy physics such models are called event generators
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.