photodetector_pcell QA (Legacy)

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photodetector_pcell QA

Photonic Model: photodetector_pcell

Information on QA tests and QA types: Introduction to Quality Assurance (QA) tests

Instructions on running QA tests: Running QA tests in CML Compiler

QA tests

QA Variables

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Statistical QA Variables 

(statistical compact models only)

[[snippet||6600975919251]]

QA scripts

photodetector_pcell_Idark_Iphoto_qa.lsf

Following test-bench is used to extract the dark current and photo current of the photodetector compact model for all the combinations of bias and temperature values provided for the test at min, max, and default values of width and length parameters. Here the anode is biased to the value provided in the "bias_test_voltage" cell in source data file and the cathode current is measured to extract FOMs. To find the dark current, a CW laser with zero power will be connected to the photodetector under test and to find the photocurrent, CW laser will have 1mW power. Measured dark and photo currents will be compared to values in the source data file, Idark_data and Resp_data, and made sure the relative difference is less than the tolerance.

photodetector_pcell_BW_qa.lsf

Following test-bench is used to extract the 3dB bandwidth of the compact model for all the combinations of bias and temperature values provided for the test at min, max, and default values of width and length parameters. In this test bench, an optical impulse is fed to the photodetector under test and the photocurrent at the cathode measured using an oscilloscope. A Fourier transform is then performed of the impulse response to extract the 3dB cutoff frequency. This value is compared to "BW_data" provided in the source data and made sure the relative difference is less than the tolerance.

photodetector_pcell_statistical_qa.lsf

In this test, for each FOM the Monte Carlo analysis is performed on related test-benches described above and data is compared to data saved in "<element_name>_stat_refdata.mat". 

This test is a regression test. If this is the first time running QA, the "stat_reference_data_available" in source data should be set to "false", so the Monte Carlo results from first run will be saved in the element folder as  in "<element_name>_stat_refdata.mat". For consecutive runs, "stat_reference_data_available" should be set to true, and results will be compared to these statistical data and make sure the difference is within the tolerance value.