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PLaSK

Photonic Laser Simulation Kit is a comprehensive tool for numerical analysis of broad range of physical phenomena in photonic devices. It has been designed for simulating mainly semiconductor lasers, however the range of the covered devices is much larger and includes e.g. transistors, light emitting diodes, photodetectors, etc. Due to its modular nature it is possible to perform computations of virtually any physical phenomenon in micro-scale structures.

PLaSK has been originally developed in a Photonics Group of Lodz University of Technology, which has many-year experience in numerical analysis of semiconductor lasers. Such structures, due to their complex structure, often fail to be correctly simulated by popular general-purpose software. However, in designing PLaSK we have taken special care to consider all the special cases of semiconductor lasers and to choose (or invent where necessary) appropriate algorithms.

Features

  • Multi-physics analysis of photonic devices
  • Automatic handling of relations between models
  • Advanced modeling of heat flow,current spreading, optical gain, electromagnetic radiation
  • Graphical user interface

Recognition

PLaSK is an effect of many years of scientific work of the members of the Photonics Group at TUL. We provide it to the world in hope it will be useful. However, if you use it for your work, we would appreciate if you gave us a proper recognition by citing the following works:

  1. M. Dems, P. Beling, M. Gębski, Ł. Piskorski, J. Walczak, M. Kuc, L. Frasunkiewicz, W. Michał, R. Sarzała, T. Czyszanowski: VCSEL modeling with self-consistent models: From simple approximations to comprehensive numerical analysis, Proc. SPIE 9381, 93810K (2015). https://doi.org/10.1117/12.2078321

  2. R. Sarzała, T. Czyszanowski, M. Wasiak, M. Dems, L. Piskorski, W. Nakwaski, K. Panajotov: Numerical self-consistent analysis of VCSELs, Adv. Opt. Technol. 2012, 689519 (2012). https://doi.org/10.1155/2012/689519

  3. Ł. Piskorski, R.P. Sarzała, W. Nakwaski: Self-consistent model of 650 nm GaInP/AlGaInP quantum-well vertical-cavity surface-emitting diode lasers, Semicond. Sci. Technol. 22, 593–600 (2007). https://doi.org/10.1088/0268-1242/22/6/002

  4. M. Dems, R. Kotynski, K. Panajotov: Plane Wave Admittance Method — a novel approach for determining the electromagnetic modes in photonic structures, Optics Express 13, 3196-3207 (2005). https://doi.org/10.1364/opex.13.003196

Building and Installation

Linux

Deb-dased systems (Debian, Ubuntu, Mint, etc.)

Enter the following commands:

$ sudo apt install g++ git cmake cmake-qt-gui ninja-build libboost-all-dev \
           libeigen3-dev libexpat1-dev libmkl-dev python3-dev \
           python3-numpy python3-scipy python3-matplotlib python3-h5py python3-lxml \
           python3-yaml python3-pyqt5 python3-sphinx python3-pip ipython3 \
           doxygen libgsl-dev libx11-dev qhelpgenerator-qt5 qttools5-dev-tools \
           python3-sphinxcontrib.qthelp

# On Ubuntu 21.10 the following command is necessary
$ sudo apt install python3-sphinxcontrib.qthelp

$ cd _your/chosen/plask/directory_

$ git clone [email protected]:plask.git .

$ git submodule update --init

$ mkdir build-release

$ cd build-release

$ cmake -G Ninja -DCMAKE_BUILD_TYPE=Release -DBUILD_GUI_TESTING=OFF ..

$ ninja

If you want to build debug version, replace release with debug and Release with Debug in above instruction.

You may also use alternative compiler CLang, which should compile your code faster. To do so, replace the above cmake -G Ninja -D CMAKE_BUILD_TYPE=Release .. command with

$ sudo apt install clang

$ cmake -G Ninja -DCMAKE_BUILD_TYPE=Release -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ ..

Additionally, you may install your favorite IDE. E.g. one of the following:

$ sudo apt install code

$ sudo apt install qtcreator

$ sudo apt install codeblocks

$ sudo apt install kdevelop

In vscode, qtcreator or kdevelop you may open CMakeList.txt as a project.

Manjaro and Arch Linux

Enter the following commands:

$ sudo pacman -S --needed gcc cmake git boost boost-libs eigen expat \
       ninja openmp openblas lapack python-numpy python-scipy \
       python-matplotlib python-h5py python-lxml python-yaml \
       pyside2 python-sphinx python-pip ipython doxygen gsl libx11

$ cd _your/chosen/plask/directory_

$ git clone [email protected]:plask.git .

$ git submodule update --init

$ mkdir build-release

$ cd build-release

$ cmake -G Ninja -DCMAKE_BUILD_TYPE=Release -DBUILD_GUI_TESTING=OFF ..

$ ninja

If you want to build debug version, replace release with debug and Release with Debug in above instruction.

You may also use alternative compiler CLang, which should compile your code faster. To do so, replace the above cmake -G Ninja -D CMAKE_BUILD_TYPE=Release .. command with

$ sudo pacman -S clang

$ cmake -G Ninja -DCMAKE_BUILD_TYPE=Release -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ ..

Additionally, you may install your favorite IDE. E.g. one of the following:

$ sudo pacman -S code

$ sudo pacman -S kdevelop

$ sudo pacman -S qtcreator

$ sudo pacman -S codeblocks

In vscode, qtcreator of kdevelop you may open CMakeList.txt as a project.

Windows

This is a new instruction for Building PLaSK with Visual Studio and Python 3.

Required tools and libraries

  • Microsoft Visual Studio 2017, 2019, or 2022 (recommended). You need to update it to the newest version, or at least 15.9.3!

  • Anaconda Python Distribution 3.9 64-bit. You may install either for the current user (just you) or all users. It is recommended to select select ‘Add to Path’ checkbox if possible (if you do not this, you will have to add Anaconda to your path manually).

  • Additional libraries (see below)...

  • Optionally:

    • Doxygen. Automatic developer documentation builder. It is not necessary.

Installing additional libraries

In order to install required libraries (Boost, Expat, and Eigen), please download Libraries.zip and extract it into C:\ folder. You should see a new folder C:\Libraries around 200MB large.

Next you must add the folder C:\Libraries\bin to the Path environment variable. In Windows 10 and 11, open the Start menu and start typing variables. Then select Edit environment variables four your account. In the dialog window that opens, find Path in the User variables, select it and click Edit.... In the another window, which pop-ups, click New, type C:\Libraries\bin and finally click Ok in all the dialogs.

If you have not selected Add to Path while installing Anaconda you must additionally add the following folders to the PATH (replace C:\ProgramData\Anaconda3 with the folder you installed Anaconda into): C:\ProgramData\Anaconda3, C:\ProgramData\Anaconda3\Library\bin, C:\ProgramData\Anaconda3\Library\usr\bin, C:\ProgramData\Anaconda3\Scripts.

Eventually your Path environment variable must contain the following folders:

  • C:\Libraries\bin (this should come first)
  • C:\ProgramData\Anaconda3
  • C:\ProgramData\Anaconda3\Library\bin
  • C:\ProgramData\Anaconda3\Library\usr\bin
  • C:\ProgramData\Anaconda3\Scripts

You also need to define two new environment variables:

  • CMAKE_PREFIX_PATH — set its value to C:\Libraries
  • MKLROOT — set it to C:\ProgramData\Anaconda3\Library

Next open an Anaconda Prompt as administrator and type two commands:

conda install mkl-devel

The last step is to create the file (or open if it already exists) C:\ProgramData\Anaconda3\Lib\site-packages\sitecustomize.py and to put into it:

import os
os.add_dll_directory('C:\\Libraries\\bin')

Compile PLaSK under Visual Studio

Start Microsoft Visual Studio. Open the file CMakeLists.txt from PLaSK source folder, by using File → Open → CMake... menu. Select x64-Debug or x64-Release configuration (x86 build will fail). Use the menu CMake → Build All to build PLaSK.

Debugging

To set up command line arguments for the debugger, refer to https://docs.microsoft.com/en-us/cpp/ide/cmake-tools-for-visual-cpp#configuring-cmake-debugging-sessions. We suggest that you use the target ${buildRoot}\bin\plask.exe for debugging.