Abstract:
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We describe a methodology and standard of proof for experimental claims of quantum random-number
generation (QRNG), analogous to well-established methods from precision measurement. For appropriately
constructed physical implementations, lower bounds on the quantum contribution to the average min-entropy can
be derived from measurements on the QRNG output. Given these bounds, randomness extractors allow generation
of nearly perfect “-random” bit streams. An analysis of experimental uncertainties then gives experimentally
derived confidence levels on the randomness of these sequences. We demonstrate the methodology by
application to phase-diffusion QRNG, driven by spontaneous emission as a trusted randomness source. All
other factors, including classical phase noise, amplitude fluctuations, digitization errors, and correlations due to
finite detection bandwidth, are treated with paranoid caution, i.e., assuming the worst possible behaviors consistent
with observations. A data-constrained numerical optimization of the distribution of untrusted parameters is used
to lower bound the average min-entropy. Under this paranoid analysis, the QRNG remains efficient, generating
at least 2.3 quantum random bits per symbol with 8-bit digitization and at least 0.83 quantum random bits per
symbol with binary digitization at a c |