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Plasma particle dynamics in collisionless magnetic reconnection Seiji ZENITANI Kyoto University 60 YEARS 0. Old tales 1. Ion dynamics 2. Electron dynamics 3. Perspectives U. Tokyo, STP (Solar Terrestrial Physics) group Super Terasawa

  1. Plasma particle dynamics in collisionless magnetic reconnection Seiji ZENITANI Kyoto University 60 YEARS

  2. 0. Old tales 1. Ion dynamics 2. Electron dynamics 3. Perspectives

  3. U. Tokyo, STP (Solar Terrestrial Physics) group “Super Terasawa Physics” “Masahiro Hoshino Dynamics” • We initially considered: • Relativistic magnetic reconnection (SZ, Ph.D thesis 2006) • Reconnection in rotating systems (Hoshino, Shirakawa, 2013-2015)

  4. Relativistic reconnection: Particle-in-Cell (PIC) simulation • Relativistic reconnection is a particle accelerator • SZ & Hoshino 2001-2008 (5 papers; 440 citations) Energy spectra Zenitani & Hoshino 2001, 2007

  5. （シミュレーション研究会スライド） Selected topics on Relativistic Particle-in-Cell Simulations S. Zenitani (Kyoto U), T. N. Kato (NAOJ), T. Umeda (Nagoya U) •1. Loading – Loading velocity distributions by random variables 
 (Sobol 1976, Swisdak 2013, Zenitani 2015) – Lorentz transformation for the spatial part (Zenitani 2015) •2. Computation – EM field (Haber 1974, Vay 2013, Ikeya & Matsumoto 2015) – Particle (Vay 2008, Zenitani & Kato 2018b, Zenitani & Umeda 2018c) •3. Diagnosis & Interpretation – Relativistic fluid decomposition (Zenitani 2018a)

  6. （シミュレーション研究会スライド） Selected topics on Relativistic Particle-in-Cell Simulations S. Zenitani (Kyoto U), T. N. Kato (NAOJ), T. Umeda (Nagoya U) •1. Loading – Loading velocity distributions by random variables 
 Poster (Sobol 1976, Swisdak 2013, Zenitani 2015) – Lorentz transformation for the spatial part (Zenitani 2015) •2. Computation – EM field (Haber 1974, Vay 2013, Ikeya & Matsumoto 2015) – Particle (Vay 2008, Zenitani & Kato 2018b, Zenitani & Umeda 2018c) •3. Diagnosis & Interpretation – Relativistic fluid decomposition (Zenitani 2018a)

  7. （シミュレーション研究会スライド） Selected topics on Relativistic Particle-in-Cell Simulations S. Zenitani (Kyoto U), T. N. Kato (NAOJ), T. Umeda (Nagoya U) •1. Loading – Loading velocity distributions by random variables 
 (Sobol 1976, Swisdak 2013, Zenitani 2015) – Lorentz transformation for the spatial part (Zenitani 2015) •2. Computation – EM field (Haber 1974, Vay 2013, Ikeya & Matsumoto 2015) – Particle (Vay 2008, Zenitani & Kato 2018b, Zenitani & Umeda 2018c) •3. Diagnosis & Interpretation – Relativistic fluid decomposition (Zenitani 2018a)

  8. Relativistic fluid mechanics is a nightmare… Energy flow γ = 100 Number flow v ~ +c γ = 200 v ~ -c γ = 10 v ~ +c Eckart frame Landau frame +X N i = 0 T i 0 = T 0 j = 0 —> Fluid analysis in relativistic reconnection (SZ 2018 PPCF)

  9. Reconnection as a particle accelerator SZ & Hoshino 2001 ApJL Hoshino 2012 PRL Hoshino+ 2001, 2005 JGR ※ Not confirmed by SZ

  10. Electron dynamics in reconnection Hoshino+ 2001 EPS Masahiro-Hoshino Dynamics (MHD) is 
 very different from the standard MHD

  11. Beyond MHD Our recent results (SZ+ 2013,2016)

  12. Magnetic reconnection in near-Earth space Burch+ 2016 Space Sci. Rev.

  13. Magnetospheric Multiscale (MMS) mission 2015 2017~ Magnetotail reconnection region (Results coming soon) 2016 Burch+ 2016 Science

  14. Central engine of magnetic reconnection ion electron Electron Diffusion Region Ion Diffusion Region Electron Dissipation Region Ion Dissipation Region Typically, fluid properties of PIC data were analyzed

  15. (E+v i xB) y Z Ion Diffusion Region ? X Vz Vy Vy Vx Ion Velocity Distribution Functions Vx

  16. Nonlinear particle dynamics • Poincaré map • One way to categorize particle orbits Buchner & Zelenyi 1989 Chen & Palmadesso 1986

  17. by T. Wada (NAOJ)

  18. Confined on a hyper-surface by T. Wada (NAOJ)

  19. Ion velocity distribution function (VDF) B y V y Z X V x B y Z V y X V x

  20. 8 VDF & Poincaré map Two choices from 5 free parameters (x, y, V x , V y , V z ) B y Z V y X V x

  21. Ion orbits in PIC simulation 8-shaped orbit Z X-line Speiser orbit (known) Speiser orbit (known) Speiser orbit (known) Y X First demonstration of 
 8-shaped orbit in PIC simulation

  22. Electron VDFs in PIC simulation 6x4 Chen+ 2008 JGR • Many PIC studies on electron VDFs • Hoshino+ 2001, Pritchett 2006, Chen+ 2008, 2009, Ng+ 2011, 2012, Bessho+ 2014, Shuster+ 2014, 2015, Cheng+ 2015 Hoshino+ 2001 EPS

  23. 6x4

  24. Electron VDFs vs electron orbits VDFs Orbits B • In addition to VDFs, 
 -B y we have to understand Egedal orbit Field-aligned electron orbits, too. inflow Do we really Dissipation understand region Local Global Speiser electron orbits? Speiser orbit z orbit +B y y x -B

  25. 8 Do we really understand electron orbits? Ions Electrons • Gyration • Opposite gyration • Large gyroradius • Small gyroradius • (Response to E field) Previous expectation B -B y Egedal orbit Field-aligned inflow Dissipation region Local Global Speiser z Speiser orbit orbit +B y y x -B

  26. Trajectory analysis in PIC simulations Memory I P C Oka et al. 2010 ApJ

  27. Trajectory analysis in PIC simulations Memory P I P C Oka et al. 2010 ApJ

  28. Trajectory analysis in PIC simulations Memory P P P P P I P C Oka et al. 2010 ApJ

  29. Trajectory analysis in PIC simulations The number of self-consistent trajectories is limited Memory P P P P P I P C Oka et al. 2010 ApJ

  30. Our simple solution Hard drive Memory I P C I P C

  31. Our simple solution Hard drive Memory I P C I P C I P C I P C I P C I P C

  32. PIC simulation & full Lagrange analysis • 2.5D • m i /m e =100 • 76.8 x 38.4 [d i ] • Harris sheet • n bg /n cs = 0.2 • 2 x 10 9 particles X • 20,000,000 electron orbits 
 from 1250 snapshot data • 3,000 orbits are inspected with eyes

  33. Electron Speiser VDFs in PIC simulation V ex : electron jets “Global Speiser” 
 via X-line region “Local Speiser” 
 Z of reflection type 3 2 1 Z 0 -1 -2 -3 35 40 45 50 0 -5 Y -10 -15 1 2 3 -20 35 40 45 50 X Speiser 1965 JGR 3

  34. 8 Electron regular orbits (b) V ex z Z Trapped in a figure-8 Chen & Palmadesso 1986 JGR Zenitani+ 2013 PoP 2.5 shaped orbit ( κ ~0.2) 2 1.5 1 0.5 Z 0 -0.5 -1 -1.5 -2 36 38 40 42 44 46 48 2 X

  35. Noncrossing electrons Orbits 3 (a) 2.5 2 1.5 z Z 1 0.5 Midplane 0 -0.5 35 40 45 50 X 1 Traditional orbits Electrostatic field E z Midplane

  36. Noncrossing electrons Orbits 3 (a) 2.5 2 1.5 z Z 1 -eE z 0.5 Midplane 0 -0.5 35 40 45 50 X 1 Traditional orbits Electrostatic field E z -E z Midplane electron ion E z

  37. Noncrossing regular orbits Trapped on flanks of 2.5 the midplane 2 1.5 1 0.5 Z 0 -0.5 -1 -1.5 -2 36 38 40 42 44 46 48 2 X Phase-space diagrams 1 1 Chen & Palmadesso 1986 JGR 0.5 0.5 Z 0 0 -0.5 -0.5 -1 -1 -10 -5 0 5 10 15 -10 -5 0 5 10 V x V z

  38. Noncrossing regular orbits Trapped on flanks of 2.5 the midplane 2 1.5 1 0.5 Z 0 -0.5 -1 -1.5 -2 36 38 40 42 44 46 48 2 X Phase-space diagrams 1 1 Chen & Palmadesso 1986 JGR 0.5 0.5 Detached from 
 Z 0 0 the midplane, -0.5 -0.5 due to E z -1 -1 -10 -5 0 5 10 15 -10 -5 0 5 10 V x V z

  39. Orbit theories 1965 1980’s Speiser 1965 Chen & Palmadesso 1986, Buchner & Zelenyi 1989 2016 A related theory came out recently: Tsai+ 2017 Zenitani & Nagai 2016

  40. Noncrossing electrons in the VDF • Cold core is occupied by noncrossing electrons in green (c) B v ez v ex

  41. Noncrossing electrons: Spatial distribution

  42. Noncrossing electrons: majority in number MRX z z v z v z

  43. State-of-art picture of electron orbits Noncrossing global B Speiser orbit -B y Noncrossing local Egedal orbit Speiser orbit F i e l d - a l i g n e i n d fl o Super-Alfvénic w Nongyrotropic electron jet electrons Dissipation Crossing Noncrossing regular orbit regular orbit region Local Global Speiser orbit Speiser orbit z +B y Field-aligned y electron outflow x -B Zenitani & Nagai, Physics of Plasmas 23 , 102102 (2016)

  44. PIC シミュレーション研究の課題 • 2010年代 大規模PICシミュレーションで複雑かつ乱流的描像が見えてきた • 流体量解析＋粒子加速研究に行き詰まり感 → さらに進んだ解析で突破 • 乱流、分布関数、軌道（Zenitani & Nagai 2016） • 粒子データを活かした解析 • 2015年～ MMS衛星が電子運動論スケールのプラズマ観測を開始 Daughton et al. 2011 Nature Phys. Karimabadi et al. 2013 Phys. Plasmas

  45. 粒子データの活用：プラズマ混合度 電子混合度 Lagrangian + ∆ t Coherent Structure Attracting boundary Repelling boundary 0 1 M f ( t 0 , ∆ t ) M b ( t 0 , ∆ t ) M R ( t 0 , ∆ t ) Zenitani et al. 2017 JGR

  46. 粒子データの活用：エントロピー (Shannon) エントロピー • p i : ３次元速度空間内の確率密度 • H関数（-f log f）も評価可能 
 →現象の不可逆性を議論するヒント Vy Vx X p i log p i − i Zenitani et al. 2018d in prep.

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