Physics Software


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Physics Software

  • Open source. Easy to use. Proven. Complete. Open source. Easy to use. Proven. Complete. Icon
    Open source. Easy to use. Proven. Complete. Icon

    End to end big data in a massively scalable super computing platform that enables you spend less time formatting data and more time analyzing it.

    Discover HPCC Systems - the truly open source big data solution that allows you to quickly process, analyze and understand large data sets, even data stored in massive, mixed-schema data lakes. Designed by data scientists, HPCC systems is a complete integrated solution from data ingestion and data processing to data delivery. The free online introductory courses and a robust developer community allow you to get started quickly.
  • Any Platform Anywhere: The Best Workflow Software Any Platform Anywhere: The Best Workflow Software Icon
    Any Platform Anywhere: The Best Workflow Software Icon

    Empower employees to improve their productivity with nocode process automation tools.

    Most people intuitively understand how workflows can streamline and speed up their business processes, integrate systems and route content to the right people. While every business has different needs, requirements and goals, workflow automation can help everyone. Whether you’re a company of 500 or 5,000, based in the cloud or on-premises, workflow automation can help maximize the efficiency of your business processes.
  • DataMelt Icon


    Computation and Visualization environment

    DataMelt (or "DMelt") is an environment for numeric computation, data analysis, computational statistics, and data visualization. This Java multiplatform program is integrated with a number of scripting languages: Jython (Python), Groovy, JRuby, BeanShell. DMelt can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential equations. Linear, non-linear and symbolic regression are also available. Neural networks and various data-manipulation methods are integrated using powerful Java API. Elements of symbolic computations using Octave/Matlab scripting are supported.

  • PROPER Optical Propagation Library

    Routines for wavefront propagation in IDL, Matlab, and Python

    PROPER is a library of routines for the propagation of wavefronts through an optical system using Fourier-based methods. It was developed at the Jet Propulsion Laboratory for modeling stellar coronagraphs, but it can be applied to other optical systems were diffraction propagation is of concern. It is currently available for IDL (Interactive Data Language), Matlab and Python (2.7 & 3.x). It includes routines for generating complex apertures and obscurations and aberrations (Zernike & PSD-defined). It includes a model of a deformable mirror for wavefront control. The routines perform near and far field propagation with automatic selection of propagators. All Python users are urged to download v3.0b, which has some major bug fixes. The latest Python version is v3.0b released on 6 Mar 2018. IDL and Matlab versions are v3.0a from 22 Jan 2018.

    Downloads: 25 This Week Last Update: See Project

    RINGS "Rigorous Investigation of Networks Generated using Simulations" is a scientific code developed in Fortran90/MPI to analyze the results of molecular dynamics simulations. Its main feature is the analysis of the connectivity using ring statistics.

    Downloads: 20 This Week Last Update: See Project
  • SoAx

    Structure of Arrays of multiple types

    Structures of arrays (SoA) are generally faster than arrays of structures (AoS) while AoS are more handy. This project (SoAx) combines the advantages of both. By means of C++(11) meta-template programming SoAx achieves maximal performance (efficient use of vector units and cache of modern CPUs) while providing a very convenient user interface (including object-oriented element handling) and flexibility. It has been designed to handle list-like sets of particles (similar to struct {int id; double[3] pos; float[3] vel;};) in the context of high-performance numerical simulations. It can be applied to many other problems. Please check the sample file main.cpp to see examples of code that you can write with SoAx.

    Downloads: 0 This Week Last Update: See Project
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