Permissions Request permission to reuse content from this site. In he was made a fellow of the Institute of Electrical and Electronic Engineers. His research interests are electromagnetic and quantum simulation, and include hyperthermia cancer therapy, nonlinear optical simulation, and quantum semiconductor simulation. The book also covers advanced Python features and deep regional hyperthermia treatment planning. Topics covered in include one-dimensional simulation with the FDTD method, two-dimensional simulation, and three-dimensional simulation. Some basic applications of signal processing theory are explained to enhance the effectiveness of FDTD simulation. This third edition utilizes the Python programming language, which is becoming the preferred computer language for the engineering and scientific community.
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Included projects increase in complexity, ranging from simulations in free space to propagation in dispersive media. Each chapter contains a concise explanation of an essential concept and instruction on its implementation into computer code. This book allows engineering students and practicing engineers to learn the finite-difference time-domain FDTD method and properly apply it toward their electromagnetic simulation projects.
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Provides an introduction to the Finite Difference Time Domain method and shows how Python code can be used to implement various simulations. Would you like to change to the United States site? Jennifer E. It is therefore fastest to get along with the non-MPI version of meep here, although the second processor core remains idle.Looks like you are currently in Russia but have requested a page in the United States site. The speed of computation depends on many parameters and paralellisation may or may not be advantageous. On many computers, the bottleneck limiting the speed of computation is not the CPU frequency, but the frequency of the RAM or even more likely, the front side bus data throughput. For typical simulations, tens to hundreds of megabytes in memory are updated each step. As ofif frequency-domain solver is to be used, one has to compile the latest version from source see above. Python-meep needs however to be still built, and I added a little fix to its building script that had to be done in Ubuntu I tested this for the MPI-enabled version only, but it should work with the non-mpi one, too.
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The same holds for older Ubuntu Hereby I thank Martin Fiers for his kind help with the installation process.įailsave alternative: download the 1. The following compilation procedure has been tested on Debian-based Linux distributions, but there should be no principial limitation in running meep and python-meep on and other systems, too. It was tested to work flawlessly on many systems, so in case of any problems, write me an e-mail and I will try to fix it. If our simulation environment was built without support for multiprocessing, it would be simply called meep and imported as import meep.Īll these steps are covered by the following blue box, so you may simply copy the commands to your terminal. They seem to work the same, so for simplicity, we choose the latter and compile everything with support for MPI. The python-meep interface has always to be compiled against the MEEP binary present in the system. Get inspired and reuse them as you need! Before we get to writing the first simulation, we will discuss the installation procedure and multiprocessing. I will simply try to provide the reader with several working examples. The reason why I chose the Python interface lies in my preference of Python syntax as well as in many excellent Python modules available scipymatplotlib and mayavi2 will be used in the examples here. One of the interfaces is python-meep with its official website at Ghent university.
The examples here are based on the python-meep interface. I will try to provide the reader with a module and examples that should help to focus on the scientific part of the task. On the other hand, it may be quite disappointing to start using MEEP: Setting up a realistic simulation is usually a challenging scientific task on its own, and with MEEP one also needs to write a working code.
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This has a good purposeas experienced users may employ MEEP for problems where more user-friendly simulation software does not provide enough versatility e. MEEP is controlled by command-line interface which requires some programming. It can compute the propagation of an electromagnetic wave through very complicated structures, using realistic material models including dispersion, conductivity, anisotropy or nonlinearitiesdistributed computing and combination of time-domain and frequency-domain solver. I use the python-meep interface for all examples presented. Installation procedure, basic simulation, material definition and some advanced features are discussed.