Deep-Learning-Designed AlGaAs Interface Linking Trapped Ions to Telecom Quantum Networks

Quantum Physics [Submitted on 13 Mar 2026] Deep-Learning-Designed AlGaAs Interface Linking Trapped Ions to Telecom Quantum Networks I.P. De Simeone, G. Maltese, V. Cambier, J-P. Likforman, M. Ravaro, L. Guidoni, F. Baboux, S. Ducci The realization of a scalable quantum internet requires efficient light-matter interfaces that map stationary qubits onto photonic carriers for long-distance transmission. A central challenge is the generation of entangled photons simultaneously compatible with single-emitter transitions and low-loss telecom fiber infrastructure. Spontaneous parametric down-conversion in integrated photonic platforms offers a promising route toward this goal. Among available material systems, AlGaAs is particularly attractive due to its large second-order nonlinearity and strong potential for monolithic integration. However, engineering the spectral and spatial properties of the generated quantum states requires the simultaneous optimization of numerous geometric and material parameters, a task remaining computationally demanding for conventional numerical approaches. To address this challenge and enable rapid and high-fidelity modeling of complex nonlinear photonic devices, we develop an inverse-design framework based on neural network surrogate models. Using this readily extendable method, we design a transversely pumped AlGaAs waveguide microcavity that produces polarization-entangled photon pairs in distinct spatial modes and frequency channels, one at 1092 nm, resonant with a ^{88}\text{Sr}^{+} transition, and the other at 1550 nm in the telecom C-band. This device establishes a direct photonic interface between trapped-ion qubits and long-haul fiber networks, providing a scalable pathway toward hybrid quantum network architectures. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2603.12846 [quant-ph]   (or arXiv:2603.12846v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2603.12846 Focus to learn more Submission history From: Italo Pio De Simeone [view email] [v1] Fri, 13 Mar 2026 09:46:03 UTC (2,148 KB) Access Paper: HTML (experimental) view license Current browse context: quant-ph < prev   |   next > new | recent | 2026-03 References & Citations INSPIRE HEP NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)