TIME DEPENDENCE OF THE PROTON FLUX MEASURED BY PAMELA DURING THE 2006 JULY-2009 DECEMBER SOLAR MINIMUM

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The Astrophysical Journal, 765:91 (8pp), 2013 March 10 doi:10.1088/0004-637X/765/2/91C 2013. The American Astronomical Society. All rights reserved. Printed in the U.S.A.TIME DEPENDENCE OF THE PROTON FLUX MEASURED BY PAMELA DURING THE2006 JULY2009 DECEMBER SOLAR MINIMUMO. Adriani1,2, G. C. Barbarino3,4, G. A. Bazilevskaya5, R. Bellotti6,7, M. Boezio8, E. A. Bogomolov9, M. Bongi1,2,V. Bonvicini8, S. Borisov10,11,12, S. Bottai2, A. Bruno6,7, F. Cafagna7, D. Campana4, R. Carbone8, P. Carlson13,M. Casolino11, G. Castellini14, M. P. De Pascale10,11,21, C. De Santis10,11, N. De Simone10, V. Di Felice10, V. Formato8,15,A. M. Galper12, L. Grishantseva12, A. V. Karelin12, S. V. Koldashov12, S. Koldobskiy12, S. Y. Krutkov9,A. N. Kvashnin5, A. Leonov12, V. Malakhov12, L. Marcelli11, A. G. Mayorov12, W. Menn16, V. V. Mikhailov12,E. Mocchiutti8, A. Monaco6,7, N. Mori2, N. Nikonov9,10,11, G. Osteria4, F. Palma10,11, P. Papini2, M. Pearce13,P. Picozza10,11, C. Pizzolotto8,17,18, M. Ricci19, S. B. Ricciarini14, L. Rossetto13, R. Sarkar8, M. Simon16, R. Sparvoli10,11,P. Spillantini1,2, Y. I. Stozhkov5, A. Vacchi8, E. Vannuccini2, G. Vasilyev9, S. A. Voronov12, Y. T. Yurkin12, J. Wu13,22,G. Zampa8, N. Zampa8, V. G. Zverev12, M. S. Potgieter20, and E. E. Vos201 Department of Physics, University of Florence, I-50019 Sesto Fiorentino, Florence, Italy2 INFN, Sezione di Florence, I-50019 Sesto Fiorentino, Florence, Italy3 Department of Physics, University of Naples Federico II, I-80126 Naples, Italy4 INFN, Sezione di Naples, I-80126 Naples, Italy5 Lebedev Physical Institute, RU-119991 Moscow, Russia6 Department of Physics, University of Bari, I-70126 Bari, Italy7 INFN, Sezione di Bari, I-70126 Bari, Italy8 INFN, Sezione di Trieste, I-34149 Trieste, Italy9 Ioffe Physical Technical Institute, RU-194021 St. Petersburg, Russia10 INFN, Sezione di Rome Tor Vergata, I-00133 Rome, Italy11 Department of Physics, University of Rome Tor Vergata, I-00133 Rome, Italy12 Moscow Engineering and Physics Institute, RU-11540 Moscow, Russia13 KTH, Department of Physics, and the Oskar Klein Centre for Cosmoparticle Physics,AlbaNova University Centre, SE-10691 Stockholm, Sweden14 IFAC, I-50019 Sesto Fiorentino, Florence, Italy15 Department of Physics, University of Trieste, I-34147 Trieste, Italy16 Department of Physics, Universitat Siegen, D-57068 Siegen, Germany17 INFN, Sezione di Perugia, I-06123 Perugia, Italy18 Agenzia Spaziale Italiana (ASI) Science Data Center, I-00044 Frascati, Italy19 INFN, Laboratori Nazionali di Frascati, Via Enrico Fermi 40, I-00044 Frascati, Italy20 Centre for Space Research, North-West University, 2520 Potchefstroom, South AfricaReceived 2012 October 31; accepted 2013 January 16; published 2013 February 20ABSTRACTThe energy spectra of galactic cosmic rays carry fundamental information regarding their origin and propagation.These spectra, when measured near Earth, are significantly affected by the solar magnetic field. A comprehensivedescription of the cosmic radiation must therefore include the transport and modulation of cosmic rays inside theheliosphere. During the end of the last decade, the Sun underwent a peculiarly long quiet phase well suited to studymodulation processes. In this paper we present proton spectra measured from 2006 July to 2009 December byPAMELA. The large collected statistics of protons allowed the time variation to be followed on a nearly monthlybasis down to 400 MV. Data are compared with a state-of-the-art three-dimensional model of solar modulation.Key words: cosmic rays solar wind Sun: heliosphereOnline-only material: color figures1. INTRODUCTIONProtons are the most abundant species in cosmic rays,representing about 90% of the total flux. They are believed tobe mainly of primordial origin, accelerated during supernovaeexplosions and confined within our Galaxy, at least up to PeVenergies. During propagation through the interstellar medium,cosmic rays undergo interactions with gas atoms and lose energysignificantly modifying their injection spectra and composition.Besides the effect of propagation in the Galaxy, cosmic-rayparticles reaching the Earth are affected by the solar wind and21 Deceased.22 Now at School of Mathematics and Physics, China University ofGeosciences, CN-430074 Wuhan, China.the solar magnetic field. A continuous flow of plasma emanatesfrom the solar corona and extends out far beyond Pluto, up to theheliopause where the interstellar medium is encountered. Thesolar wind travels at supersonic speeds of about 350650 km s1up to the termination shock where it slows down to about100150 km s1 to form the inner heliosheath.The plasma carries the solar magnetic field out into theheliosphere to form the heliospheric magnetic field (HMF).When interstellar cosmic rays enter the heliosphere, they interactwith the solar wind and the HMF that modify their energyspectra. These modifications are directly related to solar activityand the total effect is called solar modulation. Solar activityvaries strongly with time, rising from a minimum level whenthe Sun is quiet (with cosmic rays then having a maximumintensity at Earth) to a maximum period (when cosmic rays have1The Astrophysical Journal, 765:91 (8pp), 2013 March 10 Adriani et al.a minimum intensity) and then returning to a new minimum torepeat the cycle. This solar cycle spans approximately 11 years.Solar activity modulates cosmic rays with the same cycle as afunction of position in the heliosphere. Protons with rigiditiesup to at least 30 GV are affected and the effect becomesprogressively larger as the rigidity decreases (e.g., Potgieter2011). At each solar activity maximum the polarity of the solarmagnetic field reverses. When the solar magnetic field linespoint outward in the northern hemisphere and inward in thesouthern hemisphere, the Sun is said to be in an A > 0 cycle,whereas during an A < 0 cycle the solar magnetic field linespoint inward (outward) in the northern (southern) hemisphere.Direct cosmic-ray measurements above a few MeV have beenperformed from the inner to the outer heliosphere (see, e.g.,Heber & Potgieter 2006; Webber et al. 2012) and particularly atEarth where solar modulation effects are at their largest.Understanding the origin and propagation of cosmic raysrequires knowledge of the cosmic-ray energy spectra in theinterstellar medium, i.e., uninfluenced by the Suns magneticfield. These spectra, especially for protons, can be inferredfrom gamma-ray data (e.g., see Neronov et al. 2012). However,uncertainties are large and direct cosmic-ray measurementsare preferable. Voyager space missions (Decker et al. 2005;Richardson et al. 2008) have passed the termination shockand may soon start sampling the cosmic radiation in the localinterstellar medium. They will provide fundamental data tounderstand the basic features of the heliosphere. However,these cosmic-ray measurements are limited to the very lowenergy part of the spectra (from tens to a few 100 MeV), withgalactic protons, helium, and oxygen strongly contaminated bythe anomalous component (Stone et al. 2008). Higher energiesare needed to fully address fundamental questions in cosmic-ray physics. Moreover, the energy spectra of rare componentslike antiparticles may yield indirect information regarding newphysics such as dark matter. For example, the antiproton fluxbetween a few hundred MeV and a few GeV can be used (e.g.,Cerdeno et al. 2012; Asano et al. 2012; Garny et al. 2012) toconstrain models with light (10 GeV) dark matter candidatesput forward to interpret recent measurements by direct-detectionexperiments (Bernabei et al. 2000; Aalseth et al. 2011; Angloheret al. 2012). However, solar modulation has a relevant effecton the cosmic-ray spectra at these energies that needs to bedisentangled to allow a comprehensive picture to emerge.Precise measurements of cosmic-ray spectra over a widerigidity range, from a few hundred MV to tens of GV over anextended period of time (covering a significant fraction of thesolar cycle) can be used to study the effect of solar modulationin greater detail, including the convective and adiabatic coolingeffect of the expanding solar wind and the diffusive andparticle drift effects of the turbulent HMF. The most recentsolar minimum activity period (20062009) and the consequentminimum modulation conditions for cosmic rays were unusual.It was expected that the new activity cycle would begin early in2008. Instead, minimum modulation conditions continued untilthe end of 2009 when the highest levels of cosmic rays wererecorded at Earth since the beginning of the space age (see, e.g.,Mewaldt et al. 2010). This period of prolonged solar minimumactivity is well suited to study the various modulation processesthat affect the propagation of galactic cosmic rays insidethe heliosphere.PAMELA is a satellite-borne instrument designed for cosmic-ray antimatter studies. The instrument is flying on board theRussian Resurs-DK1 satellite since 2006 June, in a semi-polarFigure 1. Schematic view of the PAMELA apparatus.(A color version of this figure is available in the online journal.)near-Earth orbit. PAMELA has provided important results onthe antiproton (Adriani et al. 2009a) and positron (Adriani et al.2009b) galactic abundances. The high-resolution magnetic spec-trometer allowed hydrogen and helium spectral measurementsup to 1.2 TV (Adriani et al. 2011), the highest limit ever achievedby this kind of experiment. We present here results on the long-term variations in the absolute flux of hydrogen nuclei, measureddown to 400 MV.The analysis, described in Section 3, is based on data collectedbetween 2006 July and 2009 December. The analyzed periodcovers the unusually long most recent solar minimum. Thelarge proton statistics collected by the instrument allowed theproton flux to be measured for each Carrington rotation23(hereafter the flux measured on this time basis will be referred asCarrington flux).2. THE INSTRUMENTThe PAMELA instrument, shown schematically in Figure 1,comprises a number of highly redundant detectors, capable ofidentifying particles by providing charge (Ze), mass, rigidity(R = pc/Ze, with p momentum of the particle and c speed oflight), and velocity () measurements over a very wide energyrange. Multiple detectors are placed around a permanent magnetwith a silicon micro-strip tracking system, providing charge andtrack deflection (d = 1/R) information. A scintillator system(TOF: S1, S2, and S3) provides the trigger for event acquisition,23 Mean synodic rotational period of the Sun surface, corresponding to about27.28 days (Carrington 1863).2The Astrophysical Journal, 765:91 (8pp), 2013 March 10 Adriani et al.the time-of-flight measurement, and further charge information.A silicontungsten calorimeter is used to perform hadron/leptonseparation; a scintillator (S4) and a neutron detector placedat the bottom of the apparatus increase the rejection powerat high energy. An anti-coincidence system (AC: CAS, CAT,and CARD) registers hits produced by particles entering fromoutside the instrument acceptance. A detailed description of theapparatus can be found in Picozza et al. (2007).3. ANALYSIS3.1. Event SelectionIn order to give a valid trigger for data acquisition, a particlemust cross the S2 and S3 scintillators, located above and belowthe tracking system, respectively. The requirement of a hiton S3 sets a limit on the minimum detectable rigidity, whichfor vertical protons is on average 400 MV, i.e., 80 MeV ofkinetic energy.Clean events are selected by requiring a precision track inthe spectrometer, a trajectory contained within the instrumentacceptance, and no hits in the CARD and CAT scintillators.Protons are identified among all the selected particles byrequiring a positive track curvature and ionization energy losses(dE/dX) in the tracking system consistent with a hydrogennucleus. The dE/dX selection included deuterons, which in thiswork have been treated as being protons. Galactic particles havebeen selected by requiring that the measured rigidity was a factor1.3 above the geomagnetic vertical cutoff, evaluated using theStormer approximation, at a given orbital position. The satelliteorbit has an inclination of 70, which allows galactic particlesto be studied down to the minimum detectable rigidity.The analysis procedure was similar to previous work on high-energy proton and helium fluxes (Adriani et al. 2011). The majordifferences concern track-quality requirements and the fiducialvolume definition. The procedure used in the proton and heliumstudy aimed to maximize the spectrometer performance andminimize systematic uncertainties in the flux normalization,in order to perform a precise spectral measurement up to thehighest achievable energy. The study presented in this paperaims to trace time variations in the low-energy particle flux,with the finest possible time binning. Hence, high-performingtracking was less important than high statistics. For this reasonthe tracking requirements were relaxed (at least three hits,instead of four, on both X and Y view, a track lever arm of atleast four silicon planes in the tracker) and the fiducial volumewas enlarged (bounded 1.5 mm from the magnet cavity walls,instead of 7 mm), allowing the collection of more particles withonly a small degradation in the measurement precision in theenergy range under study.3.2. Flux NormalizationThe absolute proton flux in the spectrometer was obtained bydividing the measured energy spectrum by the acquisition time,the geometrical acceptance, and the selection efficiency.3.2.1. Acquisition TimeFlux evaluation was performed as a function of time, binningthe data according to the Carrington rotations. The time periodstudied corresponds to Carrington rotation numbers 20452092.The acquisition time was evaluated for each energy bin as thetotal live time spent above the geomagnetic cutoff, outside theSouth Atlantic Anomaly and during periods when no solarevents had occurred (hence 2006 December, when a large solarevent took place, was excluded from the data). This work isbased on data collected between 2006 July and 2009 December.The total live time was about 5 107 s (590 days) above20 GV, reducing to about 13% of this value at 0.4 GV, due tothe relatively short time spent by the satellite at low geomagneticlocations. The accuracy of the live-time determination wascross-checked by comparing different clocks available in flight,which showed a relative difference of less than 0.2%.3.2.2. Geometrical FactorThe geometrical factor for this analysis (G = 19.9 cm2 sr)is determined by the requirement of containment within thefiducial volume: a reconstructed track had to be 1.5 mm awayfrom the magnet walls and the TOF-scintillator edges. Thegeometrical factor is constant above 1 GV and slowly decreasesby 2% to lower energies, where the curvature of the protonparticle trajectory is no longer negligible.The value of G has been evaluated with two indepen-dent numerical methods, which provided values consistentwithin 0.1%.3.2.3. Selection EfficiencyThe PAMELA instrument has been designed to provide re-dundant information on event topology and particle character-istics. This feature allowed the efficiencies of each detector tobe measured directly from flight data. Due to the large protonstatistics, detector behavior could be monitored over very shorttimescales. For this analysis, efficiencies were evaluated inde-pendently for each time interval, in order to follow any possibletime variation of detector responses.The major time-dependent effect was the sudden failure ofsome front-end chips in the tracking system. Chip failures startedto occur few months after the launch of the satellite, initiallywith an almost constant rate. In the following years the rate offailures significantly decreased and the tracking system reachedan almost stable condition near the end of 2009. The net effectwas a progressive reduction of the tracking efficiency, since thenumber of hits available for track reconstruction decreased. Nodegradation in the signal-to-noise ratio and spatial resolutionwas observed.The approach described in Adriani et al. (2011) for the evalu-ation of the tracking efficiency was used: a high energy averagevalue was experimentally obtained using non-interacting mini-mum ionizing particles in the calorimeter from flight data and anenergy-dependent correction factor was evaluated using MonteCarlo simulation. The average tracking efficiency was measuredusing a test sample of non-interacting relativistic protons inthe imaging calorimeter. The resulting efficiency varied almostmonotonically from 94% during the first months to 20% inthe final months. The efficiency variation was correctly repro-duced by the simulation, which included a map of dead channelsas a function of time. Since the requirement of non-interactingminimum ionizing particles in the calorimeter selected essen-tially protons with rigidities 2 GV, the determination of thetracking efficiency at lower rigidities was performed using thesimulation. The simulation results were normalized to exper-imental values at high rigidities after performing an identicalselection. This was required because, due to the relatively poortracking resolution of the calorimeter, the average efficiencyvalues obtained using the calorimeter selection were differ-ent from the average efficiency of an isotropically distributedparticle sample (as was the case for triggered events). This3The Astrophysical Journal, 765:91 (8pp), 2013 March 10 Adriani et al.normalization was applied to the simulation estimated efficiencythat accounted for the full energy dependence of the tracking ef-ficiency and was used for the flux estimation. When comparingthe average experimental and simulated efficiencies, differencesof less than 4% were found, except during the last few monthsof 2009 when the tracking efficiency fell below 40% and, con-sequently, the discrepancy became more significant, increasingup to 13%. These differences were included in the systematicuncertainties of the measurements. As a further check, two dif-ferent simulation packages were used: GEANT3 (Brun et al.1994) and GEANT4 (Agostinelli et al. 2003). The resultingefficiencies differed by 1.5% and this was included in thesystematic uncertainty.TOF and AC selection efficiencies were evaluated relative tothe tracking selection. For well-contained events, the TOF andAC responses were not correlated and the selection efficienciescould be measured independently. At low rigidities TOF andAC efficiency measurements were affected by background con-tamination in the test samples of low-energy secondary particlesproduced by high-energy primaries interacting with the appa-ratus. This contamination resulted in an underestimation of theefficiency, since background interactions were often associatedwith multiple hits in both the TOF and AC scintillators. An up-per limit on this contamination was determined by excluding theTOF and AC conditions from the test sample selection, therebyadding background events into the test sample. The differencebetween the results was found to be 6% in the lowest-energybin. This value was conservatively treated as an asymmetricsystematic uncertainty on the absolute flux.3.3. Spectral Unfolding and Other CorrectionsThe proton spectrum measured in the spectrometer wascorrected to the top of the payload by accounting for theeffects of rigidity displacement due to finite spectrometerresolution and particle slow-down by ionization energy loss,the latter being more relevant at low energies. The correctionwas applied by means of an unfolding procedure, followingthe Bayesian approach proposed by DAgostini (1995). Thedetector response matrix was obtained from the simulation.The resulting spectrum was corrected for the contamination oflocally produced secondary particles and for attenuation dueto particles interacting with the satellite and the instrumentitself. In order to estimate the residual contamination of locallyproduced secondary particles, simulations of protons and heliumnuclei isotropically hitting the PAMELA payload within a 2solid angle were carried out. The estimated background wasfound to be less than 6% at 0.4 GV and inversely proportionalto energy, becoming negligible above 1 GV. Flux attenuation,which was slightly energy dependent and amounted to 5%6%,accounted for both particle loss by non-elastic interactions andloss and gain of particles from within the acceptance due toelastic scattering.Finally, in order to correct for systematic time-dependentvariations of the Carrington fluxes (see next section), thesewere normalized, at high energy (3050 GeV), to the proton fluxmeasured with the more stringent tracking conditions of Adrianiet al. (2011) and averaged over the period 2006 July2008March.2424 An improved use of the simulation resulted in slightly higher selectionefficiencies than previously estimated. Therefore, the proton spectrum ofAdriani et al. (2011) should be lowered by 3.2%. Furthermore, the overallsystematic uncertainty is slightly larger at low energies (4.5% at 1 GV).3.4. Systematic UncertaintiesBy relaxing the tracking selection the proton statistics couldbe significantly increased, allowing the proton flux to beevaluated on a Carrington rotation basis up to the end of2009. This approach also led to an increase of the systematicuncertainties on the measured absolute fluxes.The reliability of the flux determination was verified bystudying the time variation of the flux at high energy (above30 GeV) since no significant modulation effects are expectedin this energy region. As a reference, we considered the fluxesobtained with the stringent tracking conditions and averagedover the period 2006 July2008 March. Figure 2 shows the timedependence of the ratio between the Carrington fluxes and thereference flux for two high-energy intervals at about 30 GVand 47 GV. Two different selection criteria were considered:stringent (open circles; as in Adriani et al. 2011) and relaxedtracking selections (filled circles; this work).Comparing the upper and lower panels of Figure 2 a correla-tion between the time profiles at different energies can be no-ticed, which indicates the presence of non-negligible systematiceffects. The Carrington fluxes based on the analysis describedin Adriani et al. (2011) fluctuate around a mean value consistentwith the quoted 4% systematic uncertainty, while the fluxes forthis analysis show a decreasing trend, with a relative variationover the whole time interval of 10%. This time-dependent sys-tematic effect was corrected as discussed in the previous section.The assumption behind this correction implies that PAMELAresults are not sensitive to solar modulation-induced flux varia-tions smaller than about 5%.Further contributions to the total uncertainty resulted fromthe unfolding procedure (1%5%) and from the correction tothe top of the payload (1%).4. RESULTSFigure 3 shows the time profile of the proton flux forthree energy intervals; the error bars are statistical, while theshaded area represents the quadratic sum of all systematicuncertainties. The systematic uncertainty is dominated by thetracking efficiency and reaches a minimum above a few tens ofGeV and for the first Carrington rotations, when the trackingefficiency is maximum. Additional time- and energy-dependentcontributions to the overall uncertainty have been introducedin order to account for both the reduced accuracy of thesimulation in reproducing the spectrometer behavior as thedetection efficiency decreases in time, and the larger uncertaintyon the simulated efficiency at low energy.Figure 4 shows the evolution of the Carrington proton energyspectra from 2006 July (blue curve) to 2009 December (redcurve). Around 100 MeV proton intensities increased by 20%over 12 months, from 2006 December to 2007 December, witha slightly larger increase of 25% from 2007 December to2008 December. For 2009, when solar minimum conditionscontinued to prevail throughout the heliosphere, intensitiesincreased by almost 40%. From these data it is clear that protons(evident across the greater part of the energy spectrum) reachedmaximum intensities at the end of 2009.5. DATA INTERPRETATION AND DISCUSSIONFigure 5 and Table 1 present the galactic proton spectrameasured by PAMELA over four time periods. These dataillustrate how the proton spectra evolved from late 2006 to late4The Astrophysical Journal, 765:91 (8pp), 2013 March 10 Adriani et al.Table 1Hydrogen Flux Measured by PAMELA over Five Time PeriodsKinetic Energy Flux(GeV) (m2 s sr MeV)12006 Nov 132006 Dec 4 2007 Nov 302007 Dec 27 2008 Nov 192008 Dec 15 2009 Dec 62010 Jan 10.0820.095 (0.721 0.032+0.0610.100) (1.045 0.031+0.0900.102 (1.191 0.035+0.1050.104) (1.730 0.143+0.2660.163)0.0950.10 (0.759 0.036+0.0630.096) (1.111 0.030+0.0940.098 (1.332 0.034+0.1160.100) (1.722 0.156+0.2630.160)0.100.11 (0.818 0.030+0.0670.093) (1.151 0.027+0.0970.094) (1.401 0.031+0.1210.097) (2.016 0.134+0.3070.158)0.110.12 (0.893 0.034+0.0720.089) (1.230 0.027+0.1020.091) (1.477 0.031+0.1260.094) (2.210 0.151+0.3360.157)0.120.13 (0.928 0.030+0.0740.086) (1.334 0.026+0.1100.088) (1.543 0.029+0.1310.091) (2.162 0.129+0.3270.155)0.130.15 (0.960 0.028+0.0760.084) (1.411 0.025+0.1150.086) (1.607 0.027+0.1350.089) (2.256 0.123+0.3410.154)0.150.16 (1.030 0.028+0.0810.083) (1.453 0.023+0.1170.085) (1.675 0.026+0.1390.087) (2.447 0.122+0.3680.153)0.160.17 (1.085 0.027+0.0840.081) (1.477 0.022+0.1180.083) (1.727 0.025+0.1420.085) (2.359 0.112+0.3540.152)0.170.19 (1.123 0.025+0.0860.079) (1.545 0.021+0.1220.081) (1.805 0.024+0.1470.084) (2.277 0.102+0.3410.151)0.190.21 (1.164 0.024+0.0880.078) (1.613 0.020+0.1260.080) (1.865 0.023+0.1500.082) (2.423 0.097+0.3620.150)0.210.22 (1.194 0.022+0.0900.076) (1.634 0.019+0.1260.078) (1.899 0.021+0.1520.081) (2.592 0.093+0.3860.149)0.220.24 (1.222 0.022+0.0910.075) (1.673 0.018+0.1280.077) (1.968 0.021+0.1560.080) (2.647 0.091+0.3930.149)0.240.26 (1.278 0.021+0.0940.074) (1.732 0.018+0.1310.076) (2.031 0.020+0.1590.079) (2.682 0.088+0.3970.148)0.260.29 (1.359 0.020+0.0980.073) (1.775 0.017+0.1330.075) (2.047 0.019+0.1590.078) (2.684 0.082+0.3960.148)0.290.31 (1.371 0.020+0.0980.072) (1.788 0.016+0.1320.074) (2.025 0.018+0.1550.077) (2.603 0.077+0.3830.147)0.310.34 (1.380 0.019+0.0980.071) (1.818 0.016+0.1330.073) (2.040 0.017+0.1550.076) (2.656 0.075+0.3900.147)0.340.36 (1.381 0.018+0.0970.070) (1.822 0.015+0.1320.072) (2.036 0.017+0.1530.075) (2.633 0.072+0.3850.146)0.360.39 (1.398 0.017+0.0970.069) (1.816 0.014+0.1300.072) (2.019 0.016+0.1500.074) (2.504 0.067+0.3660.146)0.390.43 (1.410 0.016+0.0960.068) (1.778 0.013+0.1260.071) (1.983 0.015+0.1460.074) (2.415 0.061+0.3510.146)0.430.46 (1.396 0.016+0.0940.068) (1.754 0.013+0.1230.070) (1.959 0.014+0.1430.073) (2.495 0.060+0.3620.145)0.460.50 (1.391 0.015+0.0930.067) (1.715 0.012+0.1190.069) (1.941 0.014+0.1400.072) (2.383 0.056+0.3450.145)0.500.54 (1.349 0.014+0.0890.066) (1.677 0.012+0.1150.068) (1.844 0.013+0.1320.071) (2.200 0.052+0.3180.144)0.540.58 (1.328 0.014+0.0860.065) (1.643 0.011+0.1110.068) (1.789 0.012+0.1260.071) (2.213 0.050+0.3190.144)0.580.62 (1.300 0.009+0.0840.064) (1.577 0.010+0.1050.067) (1.731 0.013+0.1210.070) (2.107 0.032+0.3030.144)0.620.67 (1.254 0.008+0.0800.064) (1.527 0.009+0.1010.066) (1.641 0.012+0.1140.069) (1.966 0.030+0.2820.143)0.670.72 (1.220 0.008+0.0770.063) (1.468 0.009+0.0960.065) (1.587 0.011+0.1090.068) (1.870 0.028+0.2680.143)0.720.77 (1.173 0.007+0.0730.062) (1.403 0.008+0.0910.065) (1.510 0.011+0.1020.068) (1.769 0.026+0.2520.143)0.770.83 (1.125 0.007+0.0690.061) (1.341 0.007+0.0860.064) (1.431 0.010+0.0960.067) (1.710 0.025+0.2430.142)0.830.89 (1.064 0.006+0.0640.060) (1.272 0.007+0.0800.063) (1.357 0.009+0.0900.066) (1.550 0.022+0.2200.142)0.890.96 (1.003 0.006+0.0600.060) (1.197 0.007+0.0750.062) (1.273 0.009+0.0840.066) (1.442 0.021+0.2040.142)0.961.02 (0.964 0.005+0.0570.059) (1.135 0.006+0.0700.062) (1.192 0.008+0.0770.065) (1.382 0.020+0.1950.141)1.021.09 (0.919 0.005+0.0530.058) (1.066 0.006+0.0650.061) (1.127 0.007+0.0720.064) (1.294 0.018+0.1830.141)1.091.17 (0.860 0.005+0.0490.057) (0.993 0.005+0.0600.060) (1.041 0.007+0.0660.064) (1.178 0.017+0.1660.141)1.171.25 (0.813 0.004 0.046) (0.934 0.005 0.056) (0.983 0.006 0.062) (1.105 0.016 0.155)1.251.34 (0.753 0.004 0.042) (0.860 0.005 0.051) (0.903 0.006 0.056) (1.030 0.014 0.144)1.341.42 (0.708 0.004 0.039) (0.813 0.004 0.047) (0.845 0.006 0.052) (0.931 0.013 0.130)1.421.52 (0.650 0.004 0.035) (0.748 0.004 0.043) (0.782 0.005 0.048) (0.862 0.012 0.120)1.521.62 (0.607 0.003 0.033) (0.693 0.004 0.039) (0.719 0.005 0.044) (0.789 0.011 0.110)1.621.72 (0.562 0.003 0.030) (0.640 0.003 0.036) (0.670 0.004 0.040) (0.720 0.010 0.100)1.721.83 (0.520 0.003 0.027) (0.590 0.003 0.033) (0.612 0.004 0.036) (0.675 0.010 0.094)1.831.95 (0.481 0.003 0.025) (0.540 0.003 0.030) (0.562 0.004 0.033) (0.605 0.009 0.084)1.952.07 (0.441 0.002 0.023) (0.501 0.003 0.027) (0.512 0.004 0.030) (0.547 0.008 0.076)2.072.20 (0.412 0.002 0.021) (0.450 0.002 0.024) (0.461 0.003 0.027) (0.499 0.008 0.069)2.202.33 (0.374 0.002 0.019) (0.409 0.002 0.022) (0.428 0.003 0.024) (0.450 0.007 0.062)2.332.48 (0.347 0.002 0.017) (0.377 0.002 0.020) (0.388 0.003 0.022) (0.411 0.006 0.057)2.482.62 (0.315 0.002 0.015) (0.348 0.002 0.018) (0.356 0.003 0.020) (0.390 0.006 0.054)2.622.78 (0.286 0.002 0.014) (0.318 0.002 0.016) (0.322 0.002 0.018) (0.334 0.005 0.046)2.782.94 (0.262 0.002 0.012) (0.288 0.002 0.015) (0.291 0.002 0.016) (0.303 0.005 0.042)2.943.12 (0.239 0.001 0.011) (0.258 0.002 0.013) (0.262 0.002 0.014) (0.276 0.005 0.038)3.123.30 (0.215 0.001 0.010) (0.234 0.001 0.012) (0.239 0.002 0.013) (0.251 0.004 0.034)3.303.49 (0.195 0.001 0.009) (0.210 0.001 0.010) (0.215 0.002 0.012) (0.223 0.004 0.031)5The Astrophysical Journal, 765:91 (8pp), 2013 March 10 Adriani et al.Table 1(Continued)Kinetic Energy Flux(GeV) (m2 s sr MeV)12006 Nov 132006 Dec 4 2007 Nov 302007 Dec 27 2008 Nov 192008 Dec 15 2009 Dec 62010 Jan 13.493.69 (0.175 0.001 0.008) (0.189 0.001 0.009) (0.194 0.002 0.010) (0.204 0.004 0.028)3.694.12 (151.4 0.7 6.9) 103 (163.3 0.7565 8.050) 103 (164.7 0.9853 8.790) 103 (0.172 0.002 0.023)4.124.59 (124.4 0.6 5.6) 103 (132.0 0.6391 6.446) 103 (134.3 0.8364 7.113) 103 (0.141 0.002 0.019)4.595.11 (99.15 0.5 4.4) 103 (106.8 0.5402 5.168) 103 (109.1 0.7083 5.731) 103 (0.113 0.002 0.015)5.115.68 (81.38 0.4 3.6) 103 (85.34 0.4537 4.093) 103 (86.97 0.5944 4.536) 103 (0.091 0.001 0.012)5.686.30 (65.27 0.4 2.9) 103 (68.61 0.3820 3.262) 103 (69.55 0.4994 3.601) 103 (0.069 0.001 0.009)6.306.99 (52.12 0.3 2.3) 103 (54.86 0.3211 2.587) 103 (55.60 0.4197 2.859) 103 (56.69 0.9533 7.693) 1036.997.74 (41.66 0.3 1.8) 103 (43.65 0.2691 2.042) 103 (44.15 0.3514 2.255) 103 (44.91 0.7967 6.088) 1037.748.57 (33.18 0.2 1.4) 103 (34.31 0.2241 1.593) 103 (34.65 0.2923 1.759) 103 (34.70 0.6572 4.700) 1038.579.48 (26.26 0.2 1.1) 103 (26.80 0.1856 1.235) 103 (27.12 0.2424 1.368) 103 (27.44 0.5473 3.713) 1039.4810.48 (208.8 1.5 8.8) 104 (214.3 1.556 9.872) 104 (21.32 0.2014 1.075) 103 (21.77 0.4564 2.945) 10310.4811.57 (164.0 1.2 6.9) 104 (167.1 1.286 7.697) 104 (167.7 1.672 8.456) 104 (16.86 0.3755 2.281) 10311.5712.77 (128.9 1.0 5.5) 104 (130.2 1.061 5.998) 104 (134.6 1.399 6.785) 104 (13.03 0.3083 1.763) 10312.7714.09 (100.1 0.8 4.2) 104 (103.4 0.8845 4.762) 104 (102.8 1.143 5.182) 104 (10.22 0.2554 1.384) 10314.0915.54 (78.59 0.7 3.3) 104 (79.72 0.7250 3.672) 104 (78.55 0.9319 3.960) 104 (8.339 0.2150 1.129) 10315.5417.12 (62.71 0.6 2.7) 104 (64.08 0.6064 2.952) 104 (62.57 0.7736 3.154) 104 (62.71 1.735 8.486) 10417.1218.86 (47.92 0.5 2.0) 104 (49.08 0.4937 2.261) 104 (49.15 0.6357 2.478) 104 (47.39 1.400 6.413) 10418.8620.76 (37.16 0.4 1.6) 104 (37.96 0.4066 1.748) 104 (38.06 0.5230 1.919) 104 (38.42 1.181 5.200) 10420.7622.85 (28.92 0.3 1.2) 104 (29.32 0.3398 1.351) 104 (28.47 0.4282 1.435) 104 (28.76 9.688 3.892) 10422.8525.15 (225.8 2.6 9.6) 105 (23.07 0.2879 1.063) 104 (22.61 0.3642 1.140) 104 (21.59 0.8009 2.922) 10425.1527.66 (171.3 2.2 7.2) 105 (173.8 2.389 8.006) 105 (173.5 3.049 8.745) 105 (18.35 0.7055 2.484) 10427.6630.42 (138.0 1.9 5.8) 105 (137.7 2.031 6.344) 105 (138.8 2.603 6.997) 105 (14.03 0.5883 1.898) 10430.4233.44 (103.8 1.5 4.4) 105 (105.6 1.699 4.862) 105 (101.5 2.127 5.118) 105 (10.95 0.4965 1.482) 10433.4436.75 (81.42 1.3 3.4) 105 (80.24 1.416 3.696) 105 (81.51 1.820 4.109) 105 (76.20 0.3955 1.031) 10436.7540.39 (63.41 1.1 2.7) 105 (62.97 1.199 2.900) 105 (62.22 1.520 3.137) 105 (61.51 3.396 8.323) 10540.3944.37 (47.29 0.9 2.0) 105 (49.30 1.014 2.271) 105 (49.86 1.300 2.514) 105 (47.38 2.847 6.412) 10544.3748.74 (35.22 0.8 1.5) 105 (33.67 0.801 1.551) 105 (35.50 1.049 1.790) 105 (36.99 2.404 5.006) 105Note. The first and second errors represent the statistical and systematic uncertainties, respectively.Figure 2. Carrington proton fluxes shown relative to the flux obtained in Adriani et al. (2011; value averaged over the period 2006 July2008 March) for stringenttracking criteria (open circles) and relaxed tracking criteria (filled circles). Two energy intervals are presented.6The Astrophysical Journal, 765:91 (8pp), 2013 March 10 Adriani et al.Figure 3. Time profile of the proton flux for three energy intervals (from top to bottom): 0.5970.625 GeV, 0.991.04 GeV, and 2.993.13 GeV. The error bars arestatistical and the shaded area represents the quadratic sum of all systematic uncertainties.(A color version of this figure is available in the online journal.)Figure 4. Evolution of the proton energy spectrum as particle intensitiesapproached the period of minimum solar activity, from 2006 July (violet) to2009 December (red). The region between the blue and red curves indicates thespread in proton fluxes during this time.(A color version of this figure is available in the online journal.)2009. The latter represents the highest proton flux observedby PAMELA. In Figure 5 the PAMELA proton spectra areoverlaid with the corresponding computed spectra (solid lines).A full three-dimensional (3D) model was used to computethe differential intensity of cosmic-ray protons at Earth from10 MeV to 30 GeV. The model is based on the numerical solutionof the Parker transport equation (Parker 1965), including all fourmajor modulation mechanisms: convection, particle drift causedby gradients and curvatures in the HMF, diffusion describedby a full 3D diffusion tensor, and adiabatic energy changes.For these calculations, a local interstellar spectrum (LIS) wasassumed (shown as a solid black line in Figure 5). The protonLIS was based on that by Langner & Potgieter (2004) modified athigh energies to match PAMELA observations. It follows fromthe comparison between the model and observations that theproton spectra became progressively softer, as expected, from2006 but requiring larger diffusion coefficients at lower energiesthan anticipated. At the same time full particle drifts occurredbut with the modulation drift effects somewhat obscured bythe effective diffusion. This caused the effect of the HMF wavycurrent sheet to be less well correlated to increases in cosmic-rayintensities at Earth. Details concerning the modulation modeland theoretical assumptions and implications will be publishedin a subsequent paper (Potgieter et al. 2013).7The Astrophysical Journal, 765:91 (8pp), 2013 March 10 Adriani et al.Kinetic energy (GeV)Differential flux (m2 sr s MeV)1Protons (A < 0)EarthEquatorial plane101 100 101103102101100101LIS2006 Computed spectrum2007 Computed spectrum2008 Computed spectrum2009 Computed spectrumPAMELA Nov, 2006PAMELA Dec, 2007PAMELA Dec, 2008PAMELA Dec, 2009Figure 5. PAMELA proton spectra for 2006 November (blue), 2007 December(green), 2008 December (yellow), and 2009 December (red) overlaid with thecorresponding computed spectra (solid lines; Potgieter et al. 2013). The LISused for the computation is also shown (black solid line).(A color version of this figure is available in the online journal.)We acknowledge support from The Italian Space Agency(ASI), Deutsches Zentrum fur Luft- und Raumfahrt (DLR), TheSwedish National Space Board, The Swedish Research Council,The Russian Space Agency (Roscosmos), and The RussianFoundation for Basic Research. Partial financial support wasgiven by the South African National Research Council (NRF)for the numerical modeling.REFERENCESAalseth, C. E., Barbeau, P. S., Bowden, N. S., et al. 2011, PhRvL, 106, 131301Adriani, O., Barbarino, G. C., Bazilevskaya, G. A., et al. 2009a, PhRvL,102, 051101Adriani, O., Barbarino, G. C., Bazilevskaya, G. A., et al. 2009b, Natur, 458, 607Adriani, O., Barbarino, G. 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V., & Taylor, A. M. 2012, PhRvL, 108, 051105Parker, E. N. 1965, P&SS, 13, 9Picozza, P., Galper, A. M., Castellini, G., et al. 2007, APh, 27, 296Potgieter, M. S. 2011, SSRv, DOI:10.1007/s11214-011-9750-7Potgieter, M. S., Vos, E. E., Boezio, M., et al. 2013, ApJ, submitted(arXiv:1302.1284)Richardson, J. D., Kasper, J. C., Wang, C., Belcher, J. W., & Lazarus, A. J.2008, Natur, 454, 63Stone, E. C., Cummings, A. C., McDonald, F. B., et al. 2008, Natur, 454, 71Webber, W. R., McDonald, F. B., Cummings, A. C., et al. 2012, GeoRL,39, L0610781. INTRODUCTION2. THE INSTRUMENT3. ANALYSIS3.1. Event Selection3.2. Flux Normalization3.3. Spectral Unfolding and Other Corrections3.4. Systematic Uncertainties4. RESULTS5. DATA INTERPRETATION AND DISCUSSIONREFERENCES

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