Ardavan Oskooi Sun, 01 Mar Skip to site navigation Press enter. Philip Haupt wrote: Thanks, I had no idea that the Prism object could do anything but right-angle sides.
It does leave some other questions how to make oblique pyramids, or rectangular - not square - pyramidsbut is there a way to do this in the Python interface yet? An alternative approach for creating an arbitrary pyramid is by overlapping a set of Block objects. It's a little cumbersome to work out the orientation and size of all the individual Blocks but it will be much faster and more accurate than using a material function.
However, I thought the parameter Simulation. Perhaps I do not understand this option, but it is not working as I expected it to.
As explained in that FAQ, even if you disable subpixel smoothing, for objects involving a material function the slow SWIG callbacks during the grid initialization may still be noticeable. Previous message View by thread View by date Next message. Ardavan Oskooi. Reply via email to. The Mail Archive home meep-discuss - all messages meep-discuss - about the list Expand Previous message Next message.It is possible to use the Meep time-domain simulation code in order to calculate Casimir forces and related quantitiesa quantum-mechanical force that can arise even between neutral bodies due to quantum vacuum fluctuations in the electromagnetic field, or equivalently as a result of geometry dependence in the quantum vacuum energy.
Go here to download Meep. Calculating Casimir forces in a classical finite-difference time-domain FDTD Maxwell simulation like Meep is possible because of a new algorithm described in:.Minecraft The Meepfiles (Meep Lawyer) EP:1
These papers describe how any time-domain code may be used to efficiently compute Casimir forces without modification of the internal code. Meep contains several optimizations of these algorithms, allowing for very rapid computation of Casimir forces reasonably-sized two-dimensional systems can be solved in a matter of seconds.
This page will provide some tutorial examples showing how these calculations are performed for simple geometries. For a derivation of these methods, the reader is referred to the papers above, which will be referred to as Part I and Part II in this webpage. In this section, we introduce the equations and basic considerations involved in computing the force using the method presented in Rodriguez et. Note that we keep the details of the derivation to a minimum and instead focus on the calculational aspects of the resulting algorithm.
The goal is to determine the Casimir force on one object shown in red due to the presence of other objects blue. Classically, the force on the red object due to the electromagnetic field can be computed by integrating the Maxwell stress tensor M i j ref: Griffiths over frequency and over any surface enclosing only that object as shown above. As has been known for several decades reviewed herethe the Casimir force can be obtained by a similar integral, except that the stress tensor is replaced with the expectation value of the corresponding operator in the quantum-mechanical ground state of the system:.
In Part I, it is shown how this formulation can be turned into an algorithm for computing Casimir forces in the time domain. The reader is referred there for details.
Below we present the basic steps used in our implementation. The functions are related to the Maxwell stress tensor introduced in the previous section.
Here the frequency integration has been turned into an integration over time, which is especially suited for our purposes. Note that the precise implementation of step 3 will greatly affect the efficiency of the method. For example, computing the fields due to each source at each point on the surface separately requires a separate Meep calculation for each source and polarization. This corresponds to taking for each pointand the sum over n becomes an integration over S.
As described in Part II arXiv Picking an extended basis e. In this section we calculate the Casimir force in the two-dimensional Casimir piston configuration Rodriguez et. This is described in the sample file rods-plates.
The dashed red lines indicate the surface S.This page is a listing of the functions exposed by the Scheme interface. This page does not document the Scheme language or the functions provided by libctl. Also, note that this page is not a complete listing of all functions.
See also the instructions for parallel Meep. Note: The Scheme interface is being deprecated. We highly recommend using the Python interface.
These are global variables that you can set to control various parameters of the Meep computation. In brackets after each variable is the type of value that it should hold.
The classes, complex datatypes like geometric-objectare described in a later subsection. The basic datatypes, like integerbooleancnumberand vector3are defined by libctl. When objects overlap, later objects in the list take precedence. Defaults to no objects empty list. Defaults to none. The symmetries must be obeyed by both the structure and the sources.
See also Exploiting Symmetry. Any sizes of no-size imply a reduced-dimensionality calculation. A 2d calculation is especially optimized. See dimensions below. Defaults to a cubic cell of unit size. See also epsilon-input-file below.Overview This section consists of various projects, with a focus on technology applications, which demonstrate the advanced functionality of Meep and MPB.
Refer to their homepages for an introduction to each software package including descriptions of core features and user interface as well as tutorials demonstrating basic functionality.
Each project consists of a simulation script, a shell script to run the simulation, and Python post-processing routines for visualizing the output. A version of this page is available for the Python user interface. One of the main limitations of OLED energy efficiency is the low light extraction from the device. This is based on results published in Applied Physics Letters, Vol. A typical device structure for a bottom-emitting OLED is shown below. The device consists of a stack of four planar layers.
Electrons are injected into the organic layer from the Al cathode and holes from the ITO anode. These charge carriers form bound states called excitons which spontaneously recombine to emit photons.
Light is extracted from the device through the transparent glass substrate. We compute the fraction of the total power in each of these three device components for broadband emission from a white source spanning to nm.
The results can be obtained using just one finite-difference time-domain FDTD simulation. There are three key features involved in developing an accurate model. This requires fitting the material data to a sum of Drude-Lorentzian susceptibility terms. In this example, we treat the glass, ITO, and organic as lossless since their absorption coefficient is small. The refractive index of Al can be obtained from Applied Optics, Vol.
This can be modeled using a collection of point-dipole sources with random phase positioned within the organic layer. Given the stochastic nature of the sources, the results must be averaged using Monte-Carlo sampling.
The number of samples must be large enough to ensure that the variance of the computed quantities is sufficiently small. The size and position of these monitors must be chosen correctly to fully capture the relevant fields.
The choice of resolution requires a convergence test to determine a value suitable for a desired level of accuracy.
This is particularly relevant in this example given the presence of the lossy-metal aluminum with its nanoscale skin depth as well as the flux monitors. This is useful if we want to optimize the design. We use typical values for OLEDs. The length of the absorbing layer should be at least half the largest wavelength in the simulation to ensure negligible reflections.
This is because incident waves are absorbed twice through a round-trip reflection from the hard-wall boundaries of the computational cell.
We choose a value of several wavelengths. The choice of the waveguide length has a direct impact on the results. Meep provides an alternative absorber which tends to be more stable. We use an absorber in the X and Y directions and a PML for the outgoing waves in the glass substrate.
The metal cathode on top of the device either reflects or absorbs the incident light. No light is transmitted.This will involve automating the most technically intensive tasks required to accurately, reliably, and efficiently design and prototype photonic and optoelectronic devices.
Current simulation tools require everything to be set up by hand which, even for trained experts, is time consuming and error prone. Also, the computational design and prototyping of photonic devices involves too much trial and error. Our advanced simulation tools will facilitate enterprises and entrepreneurs with bringing products to market in a variety of industries critical to national security, health, and education.
Easy-to-use and affordable design tools will also reduce the need to fabricate and test as many iterations thereby conserving environmental resources. This is the next generation of computer-aided design CAD tools to accelerate photonics innovation and discovery. The proposed project involves the development of a turn-key, electromagnetic, simulation platform which automates complex, multi-step tasks involved in the design and prototyping of photonic and optoelectronic devices.
Photonics, the science of light, underlies critical technologies in telecommunications, networking, photovoltaics, biomedicine, photolithography, imaging, displays, and solid-state lighting. Phase II involves automating the deployment of finite difference time-domain FDTD simulations in four key areas: 1 large-scale shape optimization for devices involving tens to hundreds of degrees of freedom, 2 sensitivity analysis to assess the impact on device performance of manufacturing errors and predicting manufacturing yields, 3 launching simulation jobs using on-demand, scalable, high-performance computing HPC in the public cloud, and 4 seamlessly importing and exporting planar device geometries based on the standard Graphic Database System GDSII file format widely supported by electronic design automation EDA tools and semiconductor foundries.
This will be made possible by combining advances in machine learning, nonlinear optimization, and computational electromagnetics. This SBIR Phase I project involves the development of a turn-key simulation platform to automate electromagnetic design and modeling.
This involves the integration of state-of-the-art open-source simulation engines with intelligent control software and cloud-based high-performance computing HPC. This tool enables the advanced manufacturing of new kinds of photonic and optoelectronic devices in critical industries including telecommunications, photovoltaics, biomedicine, photolithography, imaging, displays, and solid-state lighting.
This is the next generation of computer-aided design CAD tools.Meep is a free and open-source software package for electromagnetics simulation via the finite-difference time-domain FDTD method. Meep was originally developed as part of graduate research at MIT.
The project is now being maintained by Simpetus and the developer community on GitHub. There is a public mailing list for users to discuss issues pertaining to setting up simulations, post-processing output, installation, etc. Bug reports and new feature requests should be filed as a GitHub issue. Pull requests involving bug fixes, new features, and general improvements are welcome and can be made to the master branch on GitHub.
This includes tweaks, revisions, and updates to this documentation, generated from markdownwhich is also part of the source repository. A video presentation and slides as well as a podcast are also available. For a list of more than published works which have used Meep, see the Google Scholar citation page as well as that for the technical reference and also the subpixel smoothing reference. To access this AMI, follow these instructions.
Conda packages of the latest released version are available for Linux and macOS. There are also Conda packages of nightly development builds which can be used to experiment with new features. Installing Meep from the source code requires some understanding of Unix, especially to install the various dependencies. Installation shell scripts are available for Ubuntu For Windows 10, you can install the Ubuntu terminal as an app which is based on the Windows Subsystem for Linux framework and then follow the instructions for obtaining the Conda packages or building from source.
Support for visualization is enabled using a browser-based Jupyter notebook which can also be installed via the Ubuntu terminal. For Windows 8 and older versions, you can use the free Unix-compatibility environment Cygwin following these instructions.
However, the Meep packages for Ubuntu The Meep package for Ubuntu is in the process of being updated and will likely appear in Ubuntu In the meantime, since the Scheme interface is no longer being supported and has been replaced by the Python interfaceyou can use the Conda packages which contain the official releases as well as nightly builds of the master branch of the source repository.
With most Linux distributions as well as Cygwin, packages like Guile are split into two parts: a guile package that just contains the libraries and executables, and a guile-dev or guile-devel package that contains the header files and other things needed to compile programs using Guile. Usually, the former is installed by default but the latter is not. You need to install both, which means that you probably need to install guile-dev.
Similarly for any other library packages needed by Meep.
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A classic example is an antenna in front of a ground plane, which radiates very different amounts of power depending on the distance between the antenna and the plane half wavelength vs. Alternatively, if you put a current source inside a perfect electric conductor, the resulting field will be zero. Also, as the frequency of the current increases, the amplitude of the resulting field will also increase.
This is due to Rayleigh scattering which explains why the sky is blue: scattered power increases with frequency; alternatively the density of states increases as the frequency to the d-1 power in d dimensions. For a leaky resonant mode where the fields are spatially confined and decaying away exponentially with time, the power expended by a dipole source at a given frequency and position is proportional to the ratio of the quality factor Q and modal volume V m.
This is known as Purcell enhancement of the LDOS: the same current source in a higher Q cavity emits more power if the coupling to the mode is the same. On the other hand, if you were to put in a dipole source with a fixed voltageinstead of a fixed currentyou would get less power out with higher Q.This page is a listing of the functions exposed by the Python interface. Note that this page is not a complete listing of all functions. See also the instructions for parallel Meep. If you installed into a nonstandard location e.
You typically import the meep module in Python via import meep as mp. The Simulation class contains all the attributes that you can set to control various parameters of the Meep computation. The function signature of the Simulation constructor with its default values is listed here for convenience:. All Simulation attributes are described in further detail below. In brackets after each variable is the type of value that it should hold.
The classes, complex datatypes like GeometricObjectare described in a later subsection. The basic datatypes, like integerbooleancomplexand string are defined by Python. Vector3 is a meep class. When objects overlap, later objects in the list take precedence. Defaults to no objects empty list. Defaults to 0, 0, 0but changing this allows you to shift the coordinate system used in Meep for example, to put the origin at the corner. Defaults to none empty list. The symmetries must be obeyed by both the structure and the sources.
See also Exploiting Symmetry. Defaults to none. Any sizes of 0 imply a reduced-dimensionality calculation.
Strictly speaking, the dielectric function is taken to be uniform along that dimension. A 2d calculation is especially optimized.
See dimensions below. However, it is usually convenient to pick some characteristic lengthscale of your problem and set that length to 1. See also Units. Required argument no default. See also Medium.