Data from modeling published in the paper "Phase-space analysis of a two-section InP laser as an all-optical spiking neuron: dependency on control and design parameters"

doi: 10.4121/fa5c829d-0304-4c55-97d5-be1cafa318f9.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/fa5c829d-0304-4c55-97d5-be1cafa318f9
Datacite citation style:
Puts, Lukas; Lenstra, Daan; Williams, Kevin; Yao, Weiming (2024): Data from modeling published in the paper "Phase-space analysis of a two-section InP laser as an all-optical spiking neuron: dependency on control and design parameters". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/fa5c829d-0304-4c55-97d5-be1cafa318f9.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

This upload contains the complete Python code to generate the figures as shown in the paper "Phase-space analysis of a two-section InP laser as an all-optical spiking neuron: dependency on control and design parameters". The code comprises the Yamada rate equation model to calculate the carrier densities and photon number, as well as underlying compact models to simulate an integrated two-section laser neuron in the generic InP technology platform as mentioned in the paper. To calculate the outcome of the model, Pythons ODE solver is used. A 2D sweep function is implemented to generate the data for the 2D parameter sweep plot (figure 7). Alternatively, two addition folders with pre-generated data using this model is provided to generate this figure. All generated data is saved as figures directly, or in the numpy format.

history
  • 2024-07-10 first online, published, posted
publisher
4TU.ResearchData
format
py, npy, png
organizations
Eindhoven University of Technology, Photonic Integration Group

DATA

files (24)