Integrated Quantum Photonic Neural Networks interfaced with Quantum Computers
POSTER
Abstract
energy waves confined within resonant cavities or non-uniform LC circuits [1]. By reformulating
the perturbative Coulomb interaction scheme in a photonic representation, it becomes feasible to
realize single-electron semiconductor quantum neural networks [2-4, 6], as well as electrostatic
quantum and classical logic circuits, within an optical domain. This photonic reformulation offers a
substantial reduction in system complexity and fabrication cost. A conceptual interface between a
quantum photonic neural network and semiconductor-based single-electron electronics is presented.
Moreover, the prospective integration of Josephson junctions interfaced to semiconductor quantum
dots [7], in conjunction with Gaussian Boson Sampling quantum processors [5] and photonic neural
networks, is discussed as a pathway toward hybrid quantum–photonic computational platforms.
Publication: [1]. G.Kron, Electric Circuit Models of the Schrödinger Equation, Physical Review, Vol.67, Nr 1,2.
[2]. V.Yon et al, Experimental Online Quantum Dots Charge Autotuning Using Neural Networks,
Nano Lett, 25, 2025,
[3]. L.Monbroussou, Photonic Quantum Convolutional Neural Networks with Adaptive State
Injection, Arxiv: 2504.20989v1, 2025,
[4]. M.V.Altaisky et al, Towards a feasible implementation of quantum neural networks using
quantum dots, Appl. Phys. Lett. 108, 103108, 2016,
[5]. R.Kruse et al., Detailed study of Gaussian boson sampling, Phys. Rev. A 100, 032326, 2019,
[6]. K.Pomorski et al., Analytic view on coupled single-electron lines , Semicond. Sci. Technology,
Vol.34, 125015, 2019,
[7]. K.Pomorski et al. , Analytical solutions for N interacting electron system confined in graph of
coupled electrostatic semiconductor and superconducting quantum dots in tight-binding model,
Cryogenics, Vol. 109, 2020, 103117.
Presenters
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Krzysztof D Pomorski
- University of New Mexico