Statistical adaptive sensing by detectors with spectrally overlapping bands

Area of Science:

• Optoelectronics
• Quantum Engineering
• Signal Processing

Background:

• Spectral-tuning algorithms combine photodetector photocurrents to synthesize arbitrary responsivity.
• Photocurrent noise significantly degrades the performance of existing spectral-tuning algorithms.
• Quantum-dot mid-infrared detectors exhibit bias-dependent spectral responses.

Purpose of the Study:

• To generalize the spectral-tuning algorithm to effectively accommodate noise.
• To improve the performance of spectral-tuning algorithms in the presence of noise.
• To apply the noise-robust algorithm to quantum-dot mid-infrared detectors.

Main Methods:

• Developed a generalized spectral-tuning algorithm incorporating noise accommodation.
• Applied the algorithm to quantum-dot mid-infrared detectors with varying spectral responses.
• Utilized simulation and experimental validation to assess the algorithm's effectiveness.

Main Results:

• The generalized algorithm effectively reduces the adverse impact of noise on spectral-tuning.
• Demonstrated successful synthesis of arbitrary detector responsivity even with noisy photocurrents.
• Validated the algorithm's performance on quantum-dot mid-infrared detectors.

Conclusions:

• The noise-robust spectral-tuning algorithm enhances the reliability of synthesized detector responses.
• This advancement is particularly beneficial for applications involving noisy photocurrents, such as in quantum-dot detectors.
• The generalized algorithm offers a significant improvement for spectral-tuning capabilities in optoelectronic systems.