Solar energetic particle
simulations in SEPServer
How to deal with scale separation
of thirteen orders of magnitude
R. Vainio, A. Afanasiev, J. Pomoell
University of Helsinki, FINLAND
N. Agueda, B. Sanahuja,
University of Barcelona, SPAIN
M. Battarbee, E. Valtonen,
University of Turku, FINLAND
U. Ganse, P. Kilian, F. Spanier,
University of Würzburg, GERMANY
Introduction
Solar energetic particle (SEP) acceleration
occurs in flares and coronal/interplanetary
shocks driven by CMEs
Electron (proton) spectra extend from
suprathermal energies up to tens
(thousands) of MeVs in large SEP events
SEPServer develops simulation tools for
studying SEP acceleration and transport
as well as for studies of radiation from the
coronal acceleration regions
Extreme spatial scales involved:
- electron inertial length ~ 1 cm
- distance to the observer ~ 1 AU
Scale separation = 1013 !
Models used to tackle the problem
Global dynamics


Dynamics of the bulk plasma
→ MHD simulation
Particle transport from the
source to the observer
→ Monte Carlo simulation
Ion acceleration

Coronal Shock Acceleration
→ Monte Carlo simulation
Electron acceleration

PiC simulation
Plasma emission

PiC simulation
Electron transport modeling
Electron transport from a coronal source to the observer treated using the
focused transport equation:
+ advection and adiabatic cooling
Solved using the Monte Carlo method: simulate a large number of individual particles and
collect the statistics at the position of the observer
Service to the community
Database of Green's functions
(= response at 1 AU to impulsive
injection at the Sun) simulated:
1600 cases for different transport
parameters simulated and made
available to the community.
Green's functions allow semi-empirical
modeling of coronal sources
See poster by Agueda et al.
Solar eruptions and shocks
An MHD model used to model
shocks driven by CMEs
Parameters of the shock

location

speed

normal angle
etc. extracted from simulations
CSA – Coronal
shock acceleration
Results from MHD fed to a Monte Carlo
simulation that follows ambient ion
populations interacting with the shock



Particle acceleration results from
scattering off Alfvén waves on both
sides of the shock
Alfvén wave growth approximately
computed from the streaming of ions
Turbulent trap caused by the wave
growth bootstraps the acceleration
Shock model: RH jump conditions + semiempirical cross-shock potential
Very sensitive to ambient ion population,
especially for oblique shocks!
But: not applicable to electrons (different
wave modes).
Testing the streaming-induced wave growth
for flare-accelerated protons
(see poster by Afanasiev et al.)
escaping protons
precipitating protons
new results
Ω
kr =
vμ
previous results by
Vainio & Kocharov (2001)
Modeling at electron scales:
ACRONYM PiC-Code
Fully relativistic, 2D/3D PiC Code
Correctly models complete collisionless plasma
microphysics
Constrained to kinetic scales
Kinetic Instabilities
Wave Behaviour
Particle Acceleration
Type II Radio Burst Emission
Drift-accelerated electrons in
CME foreshock excite
electrostatic waves
Nonlinear wave-wave
interaction leads to fundamental
and harmonic radio emission
Reproducible with ACRONYM
Electron acceleration at shocks
Realistic vth, vA, vS
Resolved e- scales
Few proton gyro radii
Focused on microphysics
Constrained by computation time
Discussion:
Coupling models or combining results?
The complete modeling of solar energetic particle events requires a treatment
of scales varying from electron inertial length to global scales.
Problem treated using three approaches in SEPServer:

MHD

Monte Carlo simulation: particles and Alfvén waves (for ions)

PiC simulation
Increased understanding in SEPServer obtained so far by linking model results
rather than coupling the codes.
But is coupling of codes necessary to model the complete dynamics?
Possible approaches (within computational reach):

MHD wave effects on bulk plasma dynamics

Detailed structure of shocks accelerating ions

Fluctuations at MHD and ion scales cascading to electron scales
Interesting new problems for future projects!
Acknowledgements
The research leading to these results has received
funding from the European Union’s Seventh Framework
Programme (FP7/2007-2013) under grant agreement
n:o 262773 (SEPServer).
Computational support was provided by the Centre de
Serveis Científics i Acadèmics de Catalunya (CESCA),
CSC – IT Centre for Science, and Jülich Supercomputer
Centre.
We also acknowledge support by the COST Action
ES0803 “Developing space weather products and
services in Europe”.