Skip to main content

Calculation of the scattering of EM radiation by a multilayered sphere

Project description

output example Output example: Field distribution inside layered Si\Ag\Si sphere and Poynting vector distribution in Ag sphere with powerflow lines calculated with Scattnlay (scripts field-SiAgSi-flow.py and field-Ag-flow.py from example section as revision ).

Discuss:

Try to join our Gitter chat: Join the chat at https://gitter.im/scattnlay/Lobby

Fill the issue here: Issues.

Stable releases

  • Version 2.0.1 (Jan 17, 2017). DOI
  • Version 2.0.0 (Apr 1, 2016).
  • Version 1.0.0 (Nov 22, 2014).

How to use scattnlay

Table of contents:

Mie theory calculator web application

Limited web version is available at https://physics.ifmo.ru/mie/

Compile Code

To compile the source you will need a C++11 capable compiler. To use optional MultiPrecision feature you need to install Boost.Multiprecision library (package names are given in Ubuntu\Debian notation):

  • libboost-all-dev (>= 1.58.0)

To compile the Python extension you need NumPy:

  • python-numpy (>= 1.0)
  • python-all-dev (any version)
  • python-numpy-dev (any version)
  • pybind11 (any version)

And to compile the Debian package you need some tools:

  • debhelper (>=7.0.0)
  • dh-python (any version)
  • cdbs (>= 0.4.49)

Compilation options

  • make source - Create source package for Python extension
  • make ext - Create Python extension using C++ code
  • make install - Install Python extension on local system
  • make rpm - Generate a rpm package for Python extension
  • make deb - Generate a deb package for Python extension
  • make standalone - Create standalone programs (scattnlay and fieldnlay)
  • make clean - Delete temporal files

There are also an experimental CMake project and it is possible to compile into JavaScript module (using Emscripten compiler).

Python module

To build and install Python module run from the source code directory:

pip install . --user

Binary install

Binary files for Ubuntu and derivative distributions can be found at Launchpad To install it you must configure the repository:

sudo add-apt-repository ppa:ovidio/scattering
sudo apt update

and then you simply install the package:

sudo apt install python-scattnlay

You can also install it from PyPi via

sudo pip install python-scattnlay

You can also git clone and pip install -e . to develop python package.

Use

  1. Python library
  • Use scattnlay directly
from scattnlay import scattnlay, fieldnlay
...
x = ...
m = ...
coords = ...
terms, Qext, Qsca, Qabs, Qbk, Qpr, g, Albedo, S1, S2 = scattnlay(x, m)
terms, E, H = fieldnlay(x, m, coords)
...
  • Execute some of the test scripts (located in the folder 'tests/python') Example:
./test01.py
  1. Standalone program
  • Execute scattnlay directly:
scattnlay -l Layers x1 m1.r m1.i [x2 m2.r m2.i ...] [-t ti tf nt] [-c comment]
  • Execute fieldnlay directly:
fieldnlay -l Layers x1 m1.r m1.i [x2 m2.r m2.i ...] -p xi xf nx yi yf ny zi zf nz [-c comment]
  • Execute some of the test scripts (located in the folder 'tests/shell'):
./test01.sh > test01.csv
  1. C++ library

Scattnlay "Hello world!" example:

    try {
      nmie::MultiLayerMieApplied<double> multi_layer_mie; 
      multi_layer_mie.AddTargetLayer(core_width, index_Si);
      multi_layer_mie.AddTargetLayer(inner_width, index_Ag);
      multi_layer_mie.AddTargetLayer(outer_width, index_Si);
      multi_layer_mie.SetWavelength(WL);
      multi_layer_mie.RunMieCalculation();
      double Qabs = multi_layer_mie.GetQabs();
      printf("Qabs = %g\n", Qabs);
    } catch( const std::invalid_argument& ia ) {
      // Will catch if  multi_layer_mie fails or other errors.
      std::cerr << "Invalid argument: " << ia.what() << std::endl;
      return -1;
    }

The complete example-minimal.cc and a bit more complicated example-get-Mie.cc can be found in example directory along with go-cc-examples.sh script with build commands.

example-get-Mie.cc can be compiled using double precision or multiple precision (just include -DMULTI_PRECISION=200 to use 200 digits for calculations).

Related papers

  1. O. Peña and U. Pal, "Scattering of electromagnetic radiation by a multilayered sphere," Comput. Phys. Commun. 180, 2348-2354 (2009). http://dx.doi.org/10.1016/j.cpc.2009.07.010

  2. K. Ladutenko, O. Peña-Rodríguez, I. Melchakova, I. Yagupov and P. Belov, "Reduction of scattering using thin all-dielectric shells designed by stochastic optimizer," J. Appl. Phys. 116, 184508 (2014). http://dx.doi.org/10.1063/1.4900529

  3. K. Ladutenko, P. Belov, O. Peña-Rodríguez, A. Mirzaei, A. Miroshnichenko and I. Shadrivov, "Superabsorption of light by nanoparticles," Nanoscale 7, 18897-18901 (2015). http://dx.doi.org/10.1039/C5NR05468K

  4. K. Ladutenko, U. Pal, A. Rivera, and O. Peña-Rodríguez, "Mie calculation of electromagnetic near-field for a multilayered sphere," Comp. Phys. Comm. 214, 225-230 (2017). http://dx.doi.org/j.cpc.2017.01.017

Acknowledgment

We expect that all publications describing work using this software, or all commercial products using it, cite at least one of the following references:

[1] O. Peña and U. Pal, "Scattering of electromagnetic radiation by a multilayered sphere," Computer Physics Communications, vol. 180, Nov. 2009, pp. 2348-2354.

[2] K. Ladutenko, U. Pal, A. Rivera and O. Peña-Rodríguez, "Mie calculation of electromagnetic near-field for a multilayered sphere," Computer Physics Communications, vol. 214, May 2017, pp. 225-230.

License

GPL v3+

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

python-scattnlay-2.4.tar.gz (2.1 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

python_scattnlay-2.4-cp311-cp311-macosx_14_0_arm64.whl (182.6 kB view details)

Uploaded CPython 3.11macOS 14.0+ ARM64

File details

Details for the file python-scattnlay-2.4.tar.gz.

File metadata

  • Download URL: python-scattnlay-2.4.tar.gz
  • Upload date:
  • Size: 2.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.2

File hashes

Hashes for python-scattnlay-2.4.tar.gz
Algorithm Hash digest
SHA256 81b152a1ab22ce78dde0670433e51b040aaac5aa082926d45f4e997b6ae3c38b
MD5 875d8135f289bab1c68a9f4a8e18659b
BLAKE2b-256 463b4574460f5e22e07dfa4775c5a274b71115a2d36186f6ac4a87d16bfcd224

See more details on using hashes here.

File details

Details for the file python_scattnlay-2.4-cp311-cp311-macosx_14_0_arm64.whl.

File metadata

File hashes

Hashes for python_scattnlay-2.4-cp311-cp311-macosx_14_0_arm64.whl
Algorithm Hash digest
SHA256 ec0ba790df187c2b7000866d9c93a536a11eef8f94b242b6313c2947126cf325
MD5 1bbfeb46cd44d374d56375380490f298
BLAKE2b-256 e6bc767b92ca299b780d763be11e8a3090dc3b20277b5b142f894ce125670d01

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page