Resource-efficient loss-aware photonic-graph-state preparation using atomic emitters

Multiqubit entangled photonic graph states are an important ingredient for all-photonic quantum computing, repeaters, and networking. Preparing them using probabilistic stitching of single photons using linear optics presents a formidable resource challenge due to multiplexing needs. Quantum emitters provide a viable solution to prepare photonic graph states, as they enable deterministic production of photons entangled with emitter qubits and deterministic two-qubit interactions among emitters. A handful of emitters often suffice to generate useful-size graph states that would otherwise require millions of emitters used as single photon sources, using the linear-optics method. Photon loss, however, impedes the emitter method due to a large circuit depth and hence loss accrual on the photons of the graph state produced, given the typically large number of slow two-qubit controlled-not (cnot) gates between emitters. We propose an algorithm that can trade the number of emitters with the graph-state depth, while minimizing the number of emitter cnot gates. We apply our algorithm to generate a repeater graph state (RGS) for an alternative all-photonic repeater protocol, which achieves a far superior rate-distance trade-off compared to using the least number of emitters needed to generate the RGS. Yet it needs five orders of magnitude fewer emitters than the multiplexed linear-optics method---with each emitter used as a photon source---to achieve a desired rate-distance performance.

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Publication Details

Journal
Physical review. A/Physical review, A
Published
2025-11-07
DOI
https://doi.org/10.1103/2cbn-448l
Citations
2
Primary Topic
Quantum Information and Cryptography
Type
article
Field-Weighted Citation Impact
4.96
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article

Resource-efficient loss-aware photonic-graph-state preparation using atomic emitters

Saikat Guha, Eneet Kaur, Ashlesha Patil
2 citations
Physical review. A/Physical review, A
Quantum Information and Cryptography
4.96
article

Resource-efficient loss-aware photonic-graph-state preparation using atomic emitters

Saikat Guha, Eneet Kaur, Ashlesha Patil
article en
2 citations

Abstract

Multiqubit entangled photonic graph states are an important ingredient for all-photonic quantum computing, repeaters, and networking. Preparing them using probabilistic stitching of single photons using linear optics presents a formidable resource challenge due to multiplexing needs. Quantum emitters provide a viable solution to prepare photonic graph states, as they enable deterministic production of photons entangled with emitter qubits and deterministic two-qubit interactions among emitters. A handful of emitters often suffice to generate useful-size graph states that would otherwise require millions of emitters used as single photon sources, using the linear-optics method. Photon loss, however, impedes the emitter method due to a large circuit depth and hence loss accrual on the photons of the graph state produced, given the typically large number of slow two-qubit controlled-not (cnot) gates between emitters. We propose an algorithm that can trade the number of emitters with the graph-state depth, while minimizing the number of emitter cnot gates. We apply our algorithm to generate a repeater graph state (RGS) for an alternative all-photonic repeater protocol, which achieves a far superior rate-distance trade-off compared to using the least number of emitters needed to generate the RGS. Yet it needs five orders of magnitude fewer emitters than the multiplexed linear-optics method---with each emitter used as a photon source---to achieve a desired rate-distance performance.

Physical review. A/Physical review, AVol. 112(6)
University of Arizona (US), Cisco Systems (China) (CN), University of Maryland, College Park (US)
Openalex Percentile: Top 4%
Quantum Information and Cryptography
4.96
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Resource-efficient loss-aware photonic-graph-state preparation using atomic emitters — Saikat Guha, Eneet Kaur, et al. · Physical review. A/Physical review, A (2025) | TGRS Research Map | TGRS