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Comparison of Noise Temperature of Rydberg-Atom and Electronic Microwave Receivers
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Comparison of Noise Temperature of Rydberg-Atom and Electronic Microwave Receivers
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Microwave receivers using electromagnetically-induced transparency (EIT) in Rydberg atoms have recently demonstrated improved sensitivities. It is not evident how their state-of-the-art electric field sensitivities compare to those achieved using standard electronic receivers consisting of low-noise amplifiers (LNAs) and mixers. In this paper, we show that conventional room-temperature electronic receivers greatly outperform the best demonstrated sensitivities of room-temperature Rydberg electrometers in standard free-space coupled configurations. However, Rydberg-atom receivers can surpass the sensitivity of conventional receivers if resonant or confining microwave structures are designed to enhance the electric fields sensed by the atoms. For a given microwave resonator, the external (coupling) quality factor must be carefully chosen to minimize their thermal and quantum noise contributions. Closed-form expressions for these optimal design points are found, and compared in terms of noise temperature with conventional LNAs reported in the literature from 600 MHz to 330 GHz.
Forward citations
Cited by 5 Pith papers
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A comprehensive survey bridges Rydberg-atom physics to wireless communications by reviewing architectures, response models, metric trade-offs, equivalent channels, and RAQ-enabled technologies for next-generation networks.
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Wideband Quantum Transduction for Rydberg Atomic Receivers Using Six-Wave Mixing
A six-wave-mixing Rydberg receiver is modeled as a two-pole low-pass RF-to-optical transducer, claimed to reach ~7.2 MHz baseband bandwidth versus ~0.66 MHz for EIT, with a tunable bandwidth-linearity trade-off.
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Rydberg Atomic Quantum Radio: A Comprehensive Survey From Wireless Communication Perspective
A wireless-communications-oriented survey of Rydberg atomic quantum radios covering physics, architectures, sensitivity-bandwidth-frequency trade-offs, channel models, and SAGSIN use cases.
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