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gmm_dip-gmm_field

Extension of Yu-lin Xu's GMM Electromagnetic multisphere scattering Fortran program to compute the near field with a dipole as incident field.

gptools

Gaussian processes with arbitrary derivative constraints and predictions.

gp_tomography

Non stationary gaussian process tomography for tokamak plasma

gt3

gtaw

eigenvalue code for MHD continuum and toroidal Alfven waves in Tokamaks

gtc-equilibrium-mapper

Generates input magnetic equilibria for the PIC plasma simulation code GTC, using analytical specifications or experimentally derived numerical data as inputs.

gtedge

gtneut

GTNEUT is a two-dimensional code for the calculation of the transport of neutral particles in fusion plasmas. It is based on the Transmission and Escape Probabilities (TEP) method and can be considered a computationally efficient alternative to traditional Monte Carlo methods. The code has been benchmarked extensively against Monte Carlo and has been used to model the distribution of neutrals in fusion experiments.

hack-week-2021

2021 Hack Week material...slides,notebooks, and more

hack-week-2021-demo-repo

hack-week-python-intro

A repository for Python tutorials to be held on June 21 & 22, 2021.

hack.plasmapy.org

The website for Plasma Hack Week: https://hack.plasmapy.org

i2py

Automatically exported from code.google.com/p/i2py

kn1d

Kinetic 1D-space, 2D-velocity neutral edge model

leaping-eels-transmitting-electrical-power-to-attack-large-preys

Principles of electrostatic, propagation of currents in typical waters at ambient temperature, and the electric field of a dipole to model the electric eels.

magnetic-dipole-field-calculations-in-parallel

Calculations of the magnetic field and the demagnetizing factor generated by a lattice of magnetic dipoles. Written in C++ with a serial implementation and a parallel implementation using MPI.

magnetic-field-decomposition

A program to decompose a magnetic field of a dipole magnet into harmonics

magnetic-moment

A program that calculates the magnetic moments of magnetic dipoles from magnetic field values that are measured with a Gauss meter.

magnetic_dipole

Models a charged particle moving in a magnetic dipole, and displays the three adiabatic invariants, written in C, matlab, and python

magnetic_field_sim

Training exercise simulating magnetic field of two dipoles.

magrav

Study of magnetic and gravitic fields (aka plasma energy).

magshield

Monte Carlo simulation of magnetic shielding to deflect high-energy charged particles in space.

mb19

Code used in the paper: M. Morzfeld and B.A. Buffett, A comprehensive model for the kyr and Myr time scales of Earth’s axial magnetic dipole field, Nonlinear Processes in Geophysics, 26, 123-142 (2019).

meg_data

MEG Brain Scan Data showing dipole vector field

mhd2d-matlab

Some of plasma physics code

mmcalc

MµCalc: software for calculating dipole fields in muon-spin relaxation

mpa

Magnetic Plasma Analyzer Instrument concept

mq1_prs

MIT Plasma Diagnostics 22.67 project

msc-whistler-waves-detector

Lightning strokes create powerful electromagnetic pulses that result in Very Low Frequency (VLF) waves propagating along the magnetic field lines of the earth. Due to the dipole shape of the geomagnetic field, these waves travel upward from the stroke location out through portions of the plasmasphere and back to the Earth’s surface at the field line foot point in the opposite hemisphere. VLF antenna receivers set up at various high and middle latitude locations can detect whistler waves generated by these lightning strokes. The propagation time delay of these waves is dependent on the plasma density along the propagation path. This enables the use of whistler wave observations for characterising the plasmasphere in terms of particle number and energy density. The dynamics of energetic particle populations in the plasmasphere are an important factor in characterising the risk to spacecraft in orbit around Earth. Annual global lightning flash rates are on the order of 45 flash/s [5]. The resulting high occurrence rate of whistler events makes it impossible to identify and characterise them in a reasonable time. Therefore the automatic detection and characterisation of whistlers are valuable to the study of energetic particle dynamics in the plasmasphere and to develop models for operational use. Lichtenberger [1] developed an automatic detector and analyser based on the Appleton-Hartree dispersion relation and experimental models of particle density distribution. Recent advances in artificial neural network-based image processing methods for example, convolutional networks [6] may be able to provide an alternative method for the automatic identification and characterisation of whistler events in broadband VLF spectra. Model development is based on training a neural-network-based model on a large set of spectrograms with whistler events identified by the nodes of the Automatic Whistler Detection and Analysis Network (AWDAnet [7]). Spectrograms will be presented in the form of images (Figure 1.1) to take advantage of the wide range of image-processing techniques available for this type of object identification.

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