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Quantum Machine Learning
Generation of 1 Gb full entropy random numbers with the enhanced-NRBG method
arXiv
Authors: Deepika Aggarwal, Karthick Balaji R, Rohit Ghatikar, Sruthi Chennuri, Anindita Banerjee
Year
2021
Paper ID
62491
Status
Preprint
Abstract Read
~2 min
Abstract Words
123
Citations
N/A
Abstract
Random numbers have significant applications in fundamental science, high-level scientific research, cryptography, and several other areas where there is a pressing need for high-quality random numbers. We present an experimental demonstration of a non-deterministic random bit generator from a quantum entropy source and a deterministic random bit generator mechanism to provide high quality random numbers providing a throughput of 1 Gb. Quantum entropy is realized by a series of quantum chips based on radioactive isotope Americium-241. The extracted raw random numbers are further post-processed to generate a high-entropy seed for the hash based deterministic random bit generator. We discuss the implementation of randomness extraction algorithm and Hash-DRBG algorithm in detail. The random numbers pass all randomness measures provided in ENT and NIST test suites.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2021 reference point for readers tracking recent quantum research.
- Random numbers have significant applications in fundamental science, high-level scientific research, cryptography, and several other areas where there is a pressing need for...
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