PoS(ICRC2019)164 http://pos.sissa.it/ , Yang Liu, Qiang Yuan, Chuan Yue, on behalf of the DAMPE ∗ †‡ [email protected] Speaker. The data analysis was supported in part by the National Natural Science Foundation ofFor collaboration China list (Nos. see PoS 11773085, (ICRC2019) 1177. In this analysis, we measure the time-dependence(CRE) of fluxes the primary using cosmic over ray 3 electron and yearsmonthly of CRE data fluxes from show clear the variabilities Darkgate due Matter the to Particle short-term the Explorer structures (DAMPE). of modulation The theevent effect. occurred. CRE We Energy-dependent fluxes also Forbush in descreases investi- have September, been 2017 observed.amplitude when The and Forbush an recovery decrease X time level of solar theimplication flare CRE in fluxes understanding depend the on disturbances energies,ties. of which All may interplanetary these have environment results interesting indicate due that to theparticles DAMPE solar has and activi- a the great heliosphere potential to environment. probe the interplay between † ‡ ∗ Copyright owned by the author(s) under the terms of the Creative Commons c U1738207, 11722328, 11851305, 11873021), the 100Elite Talents Program Scientists of Sponsorship Chinese Program Academy by of CAST Sciences, (No. and YESS20160196). the Young Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). 36th International Conference -ICRC2019- July 24th - August 1st, 2019 Madison, WI, U.S.A. Jingjing Zang Key Laboratory of andAcademy Space of Astronomy, Purple Sciences, Mountain Nanjing Observatory, 210034, Chinese China E-mail: collaboration Observation of time evolution of cosmicand ray positron electron fluxes with the DarkExplorer Matter Particle PoS(ICRC2019)164 sr) for CRE 2 Jingjing Zang 35 m . 0 ∼ ]) and muon detectors play important 3 ]. Precise measurements of time variations -ray photons. Here we study the time evolu- 2 γ ], with significantly improved measurements by 4 1 ]. 8 ] recently. The FD behaviors of different particle species were also 7 , 6 ]. Solar energetic particles (SEPs) can also be produced by the solar 1 pairs. The third one is a BGO calorimeter which is the key sub-detector to − e ], meaning that the DAMPE can reach the polar region which is less affected + 9 e ] and AMS-02 [ 5 -rays into . At the top is a plastic scintillator array detector (PSD) for charge measurement. The γ 1 Direct measurements of the GCR flux variations with the space particle detectors are there- The Dark Matter Particle Explorer (DAMPE) is a space-borne detector for observations of cos- The DAMPE mission was launched into a -synchronous at 500 km altitude on De- Before arriving at the Earth, Galactic cosmic rays (GCRs) propagate in the interplanetary For a long time, ground-based neutron monitors (e.g., [ tion of the CRE fluxes using thetwo DAMPE unique data. advantages Compared in with measurements other experiments, oforbit the is the DAMPE 97 CRE has degrees fluxes. [ The inclination angle of the DAMPE second part is a siliconconvert strip detector (STK) aiming to measure track of charged particles and to PAMELA [ observed for the first time by PAMELA [ by the geomagnetic rigidity cutoff. In addition, a relatively large acceptance ( fore superior in overcoming the abovetion mentioned of problems. GRC Observations intensities of can the date long-term back evolu- to 1950s [ mic ray electrons and (CREs), nuclei, and cember 17, 2015.Figure The DAMPE detector system consists of four sub-detectors, as illustrated in roles in monitoring the time evolution ofwhen GCRs, GCRs through (mostly detecting protons the and neutrons Helium or nuclei)monitors hit muons or the produced muon atmosphere. detections The are advantages oftime the the resolution large neutron can acceptance be of achieved. ground-based However,The detectors disadvantages energy and of resolution hence these of a measurements primary high are GCRssince also the obvious. inferred neutron from or muon the fluxes neutron areinteraction or the convolution cross muon of section. the measurements primary Second, is GCR the poor spectrum neutron andGCRs or the with muon hadronic all fluxes elements just and reflect are the lack total fluxes of of composition primary information. observations enables a high time-resolution. In thisof analysis, the we CRE study both fluxes the since long-terman the evolution X-level launch solar of flare DAMPE, occurred. as well as an FD event in2. September, 2017 DAMPE when detector flares, with maximum energies reaching a few GeV [ space with continuous interaction with solarsequence, winds their and fluxes their get associated modulated magnetic byflares fields. the and solar As coronal cycle. a In con- ejections addition,and violent (CME) rapidly. solar can activities disturb The such the intensities as interplanetaryshort-time of environment GCRs variabilities, substantially are known affected as byserved Forbush these this decrease transient phenomenon (FD) disturbances [ after and experience Scott E. Forbush who firstly ob- Time evolution of CREs 1. Introduction of GCR fluxes can thus beheliosphere. very useful in understanding the particle transport and interaction in the PoS(ICRC2019)164 ]. Jingjing Zang 10 seconds at 2 GeV. 5 10 × 8 . 2 ] between 2 GeV and 20 GeV and higher than 1.2 times 11 Exploded view of the DAMPE detector. Figure 1: seconds per month for energies above 15 GeV and 8 6 10 × 9 . Cosmic ray protons are rejected based on the shower development in the BGO calorimeter The data used in this analysis were recorded between April 1, 2016 and June 30, 2019. The ]. The background contamination is estimated according to a fitting of the Monte Carlo (MC) 12 [ of the vertical rigidity cutoff (VRC). simulation templates in each energy bin.vary The with primary abundance time ratios due between CREs toabout and the protons 2% solar per modulation. year. Itflight The data. is trigger Due found to efficiency that the is the radiationgain determined damage proton of from and the background electronics the PMTs decreases aging, change MC the by slightlythrough data light with yield and modifying time. of validated the Their the by impacts crystal trigger and on the 1% the threshold the per trigger of year. efficiency is the Due investigated MCtime to bin-by-bin data, the through VRC, which adding the results the exposure timesmaller in when time than a the 1/1.2 varies variation of with travels the of energy. inthe lowest within the We rigidity dead regions calculate of time with the the VRC of energy exposure values thetime bin, is data and 1 subtracting acquisition the system, SAA and passage the time, calibration time. On average the exposure pre-selection of events includesEnergy the Trigger exclusion or Low of Energy the Trigger,the the SAA full charge containment region, selection of to the the shower exclude triggers development,the heavy the energy nuclei with geometry cut and cut either with with photons, track corrected High crossing energies the [ PSD, and 3. Data analysis Time evolution of CREs measure the energy and direction ofprimitives. particles, At to the identify bottom the is particle a speciessub-detectors neutron and work detector to together (NUD) provide trigger to for assist measureDetailed of the performance particle charge, of identification. direction, each The and detector four and energy the of on-orbit cosmic calibration ray can particles. be found in [ PoS(ICRC2019)164 (3.1) , to fit ] 1 p represents / ) 1 0 Jingjing Zang t p − is the live time, t j [( T ∆ exp . With about 36 hours 0 3 p − 1 = . Here the relative fluxes with 2 Φ R , i ) i , E j ∆ σ j T − ∆ i 1 , j ( can be calculated as i 3 , i j η represents the decrease amplitude and A N 0 p = i , is the effective area of the detector, j A Φ and energy bin j ]). We also observe relatively significant monthly variations of the 13 10 GeV, the CRE fluxes become less affected by the solar activities. ∼ represent the number of CRE candidates, the fraction of the background con- i , j η , i , j σ , i , j is the width of the energy bin. . i 4 N E The behaviors of CRE fluxes corresponding to an FD event associated with the solar flare Monthly evolution of CRE fluxes is studied with more than three years of DAMPE data. An We first study the long-term evolution of the CRE fluxes. The monthly CRE fluxes are derived, The CRE flux at time bin ∆ where after the solar flare, thedays. CRE To characterize fluxes the decrease recover behavior, to we the use the minimum function, values and then recover in several 4.2 Forbush decrease occurred on September 7, 2017the have been short-term studied. variabilities of The the time fluxes. bin is The adopted results to are be shown 6 in hours Figure to study 5. Summary overall anti-correlation between the CRE fluxesbers and of the solar sunspots) activities is (characterized observed. byCRE the fluxes num- With of a an time FDtime resolution event decrease of occurred with in 6 energy. September, hours, Thistime 2017. we analysis variations obtain illustrates of Both that CRE the the the fluxes time FDnitely with DAMPE profiles amplitudes shed very is new of and high well light recovery energy suitable on resolution the tointerplanetary understanding and study of space time the the environment. resolution, particle and transport in can the defi- heliosphere as well as the CRE fluxes, indicating that the interpanetary environmentFor changes energies at higher relatively than smaller time scales. tamination, and the trigger efficiency, 4. Result 4.1 Long-term evolution of CRE fluxes with results of four selected energy bins being shown in Figure and the time profile after thethe minimum, where recovery time.Figure Both the amplitudes and the recovery time depend on energy, as shown in Time evolution of CREs respect to that of April,data 2016 collected are shown. during two To avoidAn FD influences overall events from trend occurred short-term that in solar theapproaches activities, July, CRE the 2017 to fluxes and the increase September, quiet withmonthly 2017 time state sunspot are can in numbers excluded. be these [ clearly years seen, (see due the to that bottom the panel Sun for the variation of the total PoS(ICRC2019)164 , Jingjing Zang ]. 13 Preliminary Preliminary 4 : total number of sunspots of each month [ ]. Bottom 3 On the Effects in Cosmic-Ray Intensity Observed During the Recent Magnetic Storm (1937) 1108. 51 : Variations of CRE fluxes in four chosen energy bins. Error bars (too small to be visible) are Top Time profile of relative CRE fluxes in September, 2017 with respect to the average flux of August, Phys. Rev. [1] S. E. Forbush, References statistical errors only. Figure 2: Figure 3: 2017, for two energy bins, [2.08-2.26] GeVstation and is [10.30-11.20] also GeV. The shown neutron [ monitor data from the Oulu Time evolution of CREs PoS(ICRC2019)164 , Phys. , time series Jingjing Zang φ Astropart. Phys. (2018) 76 , 853 (2011) 102 742 0.3106 0.3106 ±± 0.005016 0.005016 0.007302 0.007302 0.007765 0.007765 16.81 / 23 16.81 / 23 24.13 / 23 24.13 / 23 ±± ±± ±± 8.553 8.553 Energy (GeV) Energy (GeV) Astrophys. J. 0.3123 0.3123 , •0.08773 •0.08773 •0.07814 •0.07814 (2018) L2 [arXiv:1801.07112]. 10 10 Astrophys. J. , 854 9 9 / ndf / ndf / ndf / ndf 22 22 p1 p1 p0 p0 χχ p0 p0 χχ p1 p1 8 8 7 7 6 6 5 5 5 Astrophys. J. The on-orbit calibration of DArk Matter Particle Recovery Time , Decrease Amplitude (red solid lines). The DArk Matter Particle Explorer mission ) Observation of Fine Time Structures in the Cosmic Proton Observation of Complex Time Structures in the Cosmic-Ray 4 4 x ∗ 1 p ( 3 3 (2019) 18. Preliminary Preliminary exp (2018) 051102. ∗ 0 106 p 121 2 2 = 1 8 7 6 5 4 3 2 y 0.1 0.3 0.2

0.05 0.35 0.25 0.15

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