[Paper Review] Quantum random number generator based on quantum tunneling effect

Haihan Zhou, Junlin Li+3 more|arXiv (Cornell University)|Nov 6, 2017

Quantum Computing Algorithms and Architecture2 references3 citations

TL;DR

This paper proposes a photonic-source-free quantum random number generator (QRNG) based on the intrinsic randomness of electron quantum tunneling in InGaAs/InP avalanche diodes. By applying periodic voltage pulses to trigger tunneling events, the system generates random bits with a rate of 8 Mb/s, verified as truly random via NIST and Diehard tests, offering a low-cost, integrable, and chip-compatible solution for practical QRNG applications.

ABSTRACT

In this paper, we proposed an experimental implementation of quantum random number generator(QRNG) with inherent randomness of quantum tunneling effect of electrons. We exploited InGaAs/InP diodes, whose valance band and conduction band shared a quasi-constant energy barrier. We applied a bias voltage on the InGaAs/InP avalanche diode, which made the diode works under Geiger mode, and triggered the tunneling events with a periodic pulse. Finally, after data collection and post-processing, our quantum random number generation rate reached 8Mb/s, and final data was verified by NIST test and Diehard test. Our experiment is characterized as an innovative low-cost, photonic source free, integratable or even chip-achievable method in quantum random number generation.

Motivation & Objective

• To develop a true random number generator based on the fundamental indeterminism of quantum tunneling, avoiding reliance on photonic sources.
• To address the limitations of existing QRNGs—such as high cost, poor integration, and environmental sensitivity—by leveraging electronic tunneling in standard semiconductor diodes.
• To demonstrate a practical, low-cost, and integratable QRNG architecture suitable for on-chip implementation using widely available InGaAs/InP avalanche diodes.
• To validate the randomness of the generated sequences through rigorous statistical testing (NIST and Diehard) and post-processing with a Toeplitz-hashing extractor.

Proposed method

• The QRNG protocol exploits the inherent quantum tunneling probability of electrons across a potential barrier in an InGaAs/InP avalanche diode under periodic high-voltage pulses.
• Electron tunneling events are detected as electrical signals: '1' indicates tunneling occurred within a pulse period, '0' indicates no tunneling.
• The tunneling probability per pulse is determined by the peak voltage $U_H$, ensuring intrinsic quantum randomness independent of classical noise.
• Raw bit sequences are collected via an FPGA-based data acquisition system and post-processed using a Toeplitz-hashing extractor to enhance randomness quality.
• The system operates in Geiger mode with a stable, high-frequency trigger pulse generator to maximize generation speed.
• Environmental photons are excluded by sealing the diode in a shielded box, ensuring that detected signals originate solely from tunneling, not optical crosstalk.

Experimental results

Research questions

• RQ1 Can electron quantum tunneling in standard InGaAs/InP avalanche diodes serve as a reliable source of intrinsic quantum randomness without requiring photonic or single-photon sources?
• RQ2 What is the achievable random bit generation rate using this tunneling-based approach, and can it be scaled beyond 8 Mb/s with improved hardware?
• RQ3 How does the statistical quality of the generated random sequences compare to established benchmarks like NIST and Diehard tests?
• RQ4 To what extent can this QRNG be integrated into compact, chip-scale systems, and how does it compare in robustness and cost to existing photonic-based QRNGs?
• RQ5 Can post-processing techniques like Toeplitz-hashing effectively extract high-quality randomness from the raw tunneling signals?

Key findings

• The QRNG achieved a raw generation rate of 8.3 Mb/s using standard InGaAs/InP avalanche diodes, with the potential to scale to 20 Mb/s by increasing the trigger pulse frequency.
• The final random bit sequences passed all NIST Statistical Test Suite (STS) and Diehard test batteries, with p-values ranging from 0.014 to 0.986 and success assessments across all 16 NIST and 17 Diehard tests.
• Auto-correlation analysis confirmed a significant reduction in correlation after post-processing, indicating effective removal of biases and temporal dependencies.
• The system is photonic-source-free, relying solely on electron tunneling, which enhances stability and reduces environmental sensitivity compared to photon-based QRNGs.
• The use of commercially available diodes and FPGA-based data collection enables low-cost, scalable, and integrable implementation suitable for on-chip deployment.
• The method is fundamentally distinct from prior work using dark counts in InGaAs/InP diodes, as it exploits tunneling as the primary physical mechanism rather than a noise artifact.