True randomness from an incoherent source

TL;DR

This paper introduces a quantum random number generator that utilizes quadrature fluctuations of a thermal state measured via optical homodyne detection, achieving high entropy and passing standard randomness tests despite high detector noise.

Contribution

It proposes a novel QRNG scheme based on measuring thermal state quadratures with optical homodyne detection, tolerant to high detector noise and validated by statistical testing.

Findings

Observed quadrature variance much larger than vacuum noise

Achieved 5.12 bits per sample in randomness extraction

Successfully passed all NIST statistical tests

Abstract

Quantum random number generators (QRNGs) harness the intrinsic randomness in measurement processes: the measurement outputs are truly random given the input state is a superposition of the eigenstates of the measurement operators. In the case of \emph{trusted} devices, true randomness could be generated from a mixed state $\rho$ so long as the system entangled with $\rho$ is well protected. We propose a random number generation scheme based on measuring the quadrature fluctuations of a single mode thermal state using an optical homodyne detector. By mixing the output of a broadband amplified spontaneous emission (ASE) source with a single mode local oscillator (LO) at a beam splitter and performing differential photo-detection, we can selectively detect the quadrature fluctuation of a single mode output of the ASE source, thanks to the filtering function of the LO. Experimentally, a quadrature variance about three orders of magnitude larger than the vacuum noise has been observed, suggesting this scheme can tolerate much higher detector noise in comparison with QRNGs based on measuring the vacuum noise. The high quality of this entropy source is evidenced by the small correlation coefficients of the acquired data. A Toeplitz hashing extractor is applied to generate unbiased random bits from the Gaussian distributed raw data, achieving an efficiency of 5.12 bits per sample. The output of the Toeplitz extractor successfully passes all the NIST statistical tests for random numbers.