JunPy

Here is the home page of JunPy Website.

Introduction

JunPy is a Python package for spin transport calculation within the framework of non-equilibrium Green’s function method (NEGF). It serves as post analysis tools of first principles calculation under two-probes device to calculate:

1. Transmission

2. Current

3. Density of states

4. Spin torque.

Feature

• Based on Python3 and C++

• Spin calculate with non-equilibrium Green’s function method (NEGF)

  • Current, transmission, dos

  • Single -band tight-binding model

  • Combine first-principles calculation

• Open source

  • General public license (GPL)

• User and developer friendly

  • Online manual

  • Rich examples

• Performance issues

  • High performance library: Numpy and ScyPy

  • Using symmetry k-points (using spglib)

  • Parallel computing with MPI (using mpi4py)

  • Combine C++ directly

Guildlines:

• Installation
  • Install for linux
  • Install for windows
• Tutorial
  • Carbon Chain (Part 1)
  • Carbon Chain (Part 2)
  • Graphene
  • Simple Metallic Chain
  • FM/I/FM Magnetic Tunnel Junction
• Example
• Input reference
  • Carbon Chain
  • Graphene

Appendix:

• Theorem
  • Basic Formulism
  • Flow Chart
  • Code Architecture
• Contact us
• Forum

Caution

This Website is still building, and Source codes of JunPy are going to be opened in the future. JunPy is still in development and temporarily unavailable in public. If you have some ideas and questions, please contact us

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If anyone want to learn more about JunPy, you can read the following content.

If you want to use JunPy you can just import jumpy as jp so that you can use JunPy in python as jp.[function].

Roughly, JunPy can calculate following things:

Tip

This package need to use with nanodcal. Because it will use the hamitonian which is calculated by nanodcal

Danger

This package is pretty good. Please be careful not to become overly addicted