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# photodetectors
MUTC Photodetector Dataset
This dataset lists four performance metrics of 1755 MUTC photodetectors with 17 layers.
The semiconductor types of these layers are fixed and they can be found in https://doi.org/10.1364/OE.27.003717
# photodetectors <br>
MUTC Photodetector Dataset <br>
This dataset lists four performance metrics of 1755 MUTC photodetectors with 17 layers. <br>
The semiconductor types of these layers are fixed and they can be found in https://doi.org/10.1364/OE.27.003717 <br>
**Columns**
phasenoise : true phasenoise of the photodetector (Unit: dBc/Hz)
phasenoise_15mA : hypothetical phasenoise of the photodetector if the output current was equal to 15 mA (Unit: dBc/Hz)
current : average current of the photodetector (Unit: mA)
IR_max : maximum value of the impulse response of the photodetector
decay_time: the time it takes for the impulse response to decay from its maximum value to 1% of that maximum value (Unit: ns)
t1 ... t17 : thickness each layer (Unit: nm)
d1 ... d17 : doping concentration of each layer (Unit: cm^-3)
phasenoise : true phasenoise of the photodetector (Unit: dBc/Hz) <br>
phasenoise_15mA : hypothetical phasenoise of the photodetector if the output current was equal to 15 mA (Unit: dBc/Hz) <br>
current : average current of the photodetector (Unit: mA) <br>
IR_max : maximum value of the impulse response of the photodetector <br>
decay_time: the time it takes for the impulse response to decay from its maximum value to 1% of that maximum value (Unit: ns) <br>
t1 ... t17 : thickness each layer (Unit: nm) <br>
d1 ... d17 : doping concentration of each layer (Unit: cm^-3) <br>
**Forward Problem:** Predicting Performance Metric From Design Parameters
**Forward Problem:** Predicting Performance Metric From Design Parameters <br>
The four machine learning algorithms, linear regression, k-nearest neighbor, random forest, and an artificial neural network, are used to predict performance metrics (phasenoise, current, IR_Max, and decay_time) from the design parameters (thicknesses and doping concentrations)

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