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arXiv · 2205.01221

Resolution of 100 photons and quantum generation of unbiased random numbers

Miller Eaton·Amr Hossameldin·Richard J. Birrittella·Paul M. Alsing·Christopher C. Gerry·Hai Dong·Chris Cuevas·Olivier Pfister
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Abstract

Macroscopic quantum phenomena, such as observed in superfluids and superconductors, have led to promising technological advancements and some of the most important tests of fundamental physics. At present, quantum detection of light is mostly relegated to the microscale, where avalanche photodiodes are very sensitive to distinguishing single-photon events from vacuum but cannot differentiate between larger photon-number events. Beyond this, the ability to perform measurements to resolve photon numbers is highly desirable for a variety of quantum information applications including computation, sensing, and cryptography. True photon-number resolving detectors do exist, but they are currently limited to the ability to resolve on the order of 10 photons, which is too small for several quantum state generation methods based on heralded detection. In this work, we extend photon measurement into the mesoscopic regime by implementing a detection scheme based on multiplexing highly quantum-efficient transition-edge sensors to accurately resolve photon numbers between zero and 100. We then demonstrate the use of our system by implementing a quantum random number generator with no inherent bias. This method is based on sampling a coherent state in the photon-number basis and is robust against environmental noise, phase and amplitude fluctuations in the laser, loss and detector inefficiency as well as eavesdropping. Beyond true random number generation, our detection scheme serves as a means to implement quantum measurement and engineering techniques valuable for photonic quantum information processing.

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Miller Eaton, Amr Hossameldin, Richard J. Birrittella, Paul M. Alsing, Christopher C. Gerry, Hai Dong, Chris Cuevas, Olivier Pfister. 2022-05-02. Resolution of 100 photons and quantum generation of unbiased random numbers. https://doi.org/10.1038/s41566-022-01105-9

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