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SiEPIC_Photonics_Package

A Python (v3.6.5) package that provides a set of basic functions commonly used in integrated photonics.

Functions

• calibrate

Calibrates an input spectrum response with respect to another input response. Example

• calibrate_envelope

Calibrates an input spectrum response with respect to the envelope of another input response. This is useful for calibrating non-periodic responses using another non-periodic response. i.e. calibrating the reflection port spectrum of a Bragg response using its through port spectrum. Example

• baseline_correction

Calibrates an input response with respect to it's baseline. This is useful for calibrating periodic responses, using their own response as a reference, i.e. a ring resonator response or a mach-zehnder interferometer response. Example

• cutback

Extrapolate the losses of different input data files losses using the cutback method. Example

• to_s_params

Converts the input data to generate a .dat file compatible with Lumerical INTERCONNECT's N-port s-parameter file format. Example

• download_response

Downloads a .mat response (Caverley's pyoptomip format) from a url and parses data into a variable. Example

Simulators and solvers

• EM_solver

Eigenmode solver for a 2D waveguide structure.

• RAMZI_Modulators

Ring-assisted Mach-Zehnder Interferometer-based modulators designer. Example

• Ring_Designer

Microrings designer: model N-order rings system spectrum. Example

• MZI_simulator

Simulate the spectrum of a Mach-Zehnder interferometer with different input parameters. Example

• Bragg_TMM

Model the response of a Bragg grating based on the transfer matrix method (TMM). Example

• Bragg_CMT

Model the response of a Bragg grating based on the coupled-mode theory (CMT). Example

• Contra_DC

Fully automated, Lumerical-assisted flow to model the response of a contra-directional coupler based on a coupled-mode theory (CMT) and transfer matrix method. Example (run main.py)

Lab equipment and testing stage scripts

• Stage control
• Keithly 2602B
• Agilent OSA

To-do:

• Integrate Jupyter Notebook
• Add PCM analysis script