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Raphael Pooser, PhD Computing and Computational Sciences Directorate Dr. Raphael Pooser is an expert in continuous variable quantum optics. He has over 15 years of quantum optics experience, having led the Quantum Sensing Program at ORNL over the past 7 years. Dr. Pooser has published multiple refereed papers in high-impact journals, including in Science, Nature, and Physical Review Letters. He previously worked as a postdoctoral fellow in the Laser Cooling and Trapping Group at NIST after receiving his PhD in engineering physics from the University of Virginia. He received a B.S. in physics from New York University, graduating cum laude on an accelerated schedule. Technology Quantum Random Number Generator US Patents 9,436,436 and 9,335,973 Invention Disclosure Nos. 201102727, 201202833, and 201703949 Inventors Raphael Pooser, Travis Humble, and Ben Lawrie Computational Sciences and Engineering Division, Quantum Information Science Group For more information, please contact Eugene Cochran Commercialization Manager cochraner@ornl.gov 865-576-2830 Creating Truly Random Numbers: The Self-Correcting Random Number Generator 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 less expensive. 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 is 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 is to demonstrate the ability to generate random numbers at a rate greater than 20 Gbps. The key applications of this device are in the fields of cryptography, high performance computing, authentication, and digital/online gambling. These fields would all benefit from large amounts of cheap, truly random numbers. Publications • 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).PDF Image | Technology Innovation Program 2017
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