Green InGaN LED-based quantum random number generation compatible with silicon avalanche photodiodes

Area of Science:

• Quantum physics
• Information security
• Materials science

Background:

• Quantum random number generators (QRNGs) offer enhanced security over classical methods.
• Existing optical QRNGs using blue LEDs have spectral mismatch issues with silicon avalanche photodiodes (APDs).
• This mismatch limits signal-to-noise ratio (SNR) and extractable quantum entropy.

Purpose of the Study:

• To demonstrate a spontaneous emission-based QRNG with improved spectral overlap.
• To utilize a green InGaN LED coupled to a silicon APD for better performance.
• To establish longer-wavelength nitride-based LEDs as a viable entropy source for QRNGs.

Main Methods:

• Employed a green InGaN LED as the quantum entropy source.
• Coupled the green LED with a silicon avalanche photodiode (APD).
• Filtered the signal with a high-pass filter and extracted randomness using the SHAKE256 hash function.

Main Results:

• Achieved significantly higher SNR compared to blue LEDs due to improved spectral overlap.
• Demonstrated a quantum entropy generation rate of 2.78 Gbit/s.
• Validated the suitability of green LEDs and silicon APDs for QRNG systems.

Conclusions:

• Green InGaN LEDs offer superior spectral matching with silicon APDs for QRNG applications.
• The developed QRNG system provides a high-rate, secure source of random numbers.
• This approach leverages inexpensive and widely available components for robust quantum random number generation.