Qutat Waveform is a simulation and data science framework designed to accelerate wave optics research. Along with a GPU-accelerated FDTD (Finite Difference Time Domain) simulator, it provides convenient features for creating and utilizing simulation datasets. Waveform focuses more on creating and using 'simulation datasets' rather than individual simulation results. It offers a modeling method to effectively express randomized structures that can form the input dataset, and SPDM (Simulation Process and Data Management) features to obtain simulation results from each of them, which can form the output dataset.
On Waveform, machine learning models can be built using the dataset. Additionally, the prediction of simulation results, inverse designs, and optimizations can be conducted using these models. Although it contains a built-in wave optics solver, other user-defined solvers can also be integrated. Any simulation tool with a Python API can be connected and executed as a subprocess from the Waveform user interface. Therefore, many core-algorithm-only solvers can be integrated with several features of Waveform and easily scaled up to expand its functions, computational power, and user base.
Declare parameters as range, determine later.
Connect and utilize every computational resource that you already own.
User-defined simulation codes can be integrated.
Generates random structures
Reuses structures as components
Defines complex shapes with equations
Includes built-in GPU-accelerated FDTD Simulation
Integrates user-defined simulations with Python API
Executes multiple simulations on remote computers
Structures, Reusable Components and Materials
Simulation Setups
Each Randomly Generated Structures and Simulation Results
User-defined Post Processing
Correlation Analysis
Cluster Analysis
Parameter Optimization
Adjoint Optimization
Neural Network Model for Prediction/Design