Indistinguishable Single Photons from Nanowire Quantum Dots in the Telecom O-Band
arXiv:2503.12116 · doi:10.1063/5.0271146
Abstract
On-demand single-photon sources operating at telecom wavelengths are crucial for quantum communication and photonic quantum technologies. In this work, we demonstrate high-purity, indistinguishable single-photon generation in the telecom O-band from an InAsP/InP nanowire quantum dot. We measured a single-photon purity of under aboveband excitation. Furthermore, we characterize two-photon interference via Hong-Ou-Mandel measurements and achieve a photon indistinguishability of with a temporal postselection of 100 ps time window and without temporal postselection. We measure a first-lens source efficiency of . These results highlight the potential of nanowire quantum dots as a promising source of telecom single photons for photonic quantum applications, offering deterministic positioning, efficient photon extraction, and scalable production.
6 pages, 4 figures
References in corpus (13)
- The Quantum Internet
- Photonic quantum technologies
- Quantum computational advantage using photons
- High-rate intercity quantum key distribution with a semiconductor single-photon source
- High-throughput quantum photonic devices emitting indistinguishable photons in the telecom C-band
- Coherence and indistinguishability of highly pure single photons from non-resonantly and resonantly excited telecom C-band quantum dots
- Single-emitter quantum key distribution over 175 km of fiber with optimised finite key rates
- On-Demand Generation of Indistinguishable Photons in the Telecom C-Band using Quantum Dot Devices
- Position-controlled Telecom Single Photon Emitters Operating at Elevated Temperatures
- Approaching transform-limited photons from nanowire quantum dots excited above-band
- Dynamic strain modulation of a nanowire quantum dot compatible with a thin-film lithium niobate photonic platform
- Efficient, indistinguishable telecom C-band photons using a tapered nanobeam
- Efficient and Versatile Toolbox for Analysis of Time-Tagged Measurements