Truly random numbers are incredibly difficult to produce. Pseudo-random number generators, typically used in computational applications, are not truly random because they are based on computations and require a seed from some source, typically the system time. This basis in computation can be potentially reverse engineered, making the numbers predictable, and that is dangerous for cyber security. Quantum random number generators (QRNGs) are different because they rely on the truly random nature of quantum mechanics to guarantee the unpredictability of their numbers. However, while the quantum mechanics guarantees theoretical randomness, there are ambient effects that can affect the results. Additionally, QRNGs are notoriously slow in putting out numbers and are renowned for being expensive. Researchers at ORNL have developed a self-correcting quantum random number generator. The device generates a field of photons and measures the quantum statistics after passing them through a beam splitter. By creating a beam of many photons instead of a single one, ORNL’s device is able to generate random numbers at a significantly higher rate, and the device itself is several orders of magnitude cheaper. In addition, the device is capable of recognizing and accounting for its own bias, making the produced numbers truly random.
Overall, the goal of this project was to demonstrate that a QRNG which corrects and removes its own biases can be integrated into a small package and that the total cost of such a device can be under $100. A secondary goal was to allow a greater random data rate than 20 Gbps for the generation of numbers.
The four key applications of this device are in the fields of cryptography, high performance computing, authentication, and digital/online gambling. These fields would all benefit greatly from large amounts of cheap, truly random numbers.
For more information, or to obtain an application to license this technology, please contact Eugene Cochran at 865-576-2830 or firstname.lastname@example.org.
– Fed Business Ops
– Fact Card
– ORNL UT-B ID: 201202833
– ORNL UT-B ID: 201102727
– Travis S. Humble, Quantum Statistical Testing of a Quantum Random Number Generator and http://web.ornl.gov/~humblets/publications/SPIE.QCQIXII.922509.2014.pdf
– R.C. Pooser and B.J. Lawrie, “Plasmonic trace sensing below the photon shot noise limit”, ACS Photonics 3, 8 (2016).
– R.C. Pooser, “Practical Quantum Sensing at Ultra Trace Levels with Squeezed States of Light”, SPIE Photonics West (2017).
– Eugene Cochran, tel. 865-576-2830, email@example.com
– Raphael Pooser, tel. 865-576-6658, firstname.lastname@example.org