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Designing Nonlinear Photonic Crystals for High-Dimensional Quantum State Engineering

arXiv 2304.06810 ↗First posted 13 Apr 2023quant-ph cs.AI cs.LGcited by 0

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Abstract (arXiv)

We propose a novel, physically-constrained and differentiable approach for the generation of D-dimensional qudit states via spontaneous parametric down-conversion (SPDC) in quantum optics. We circumvent any limitations imposed by the inherently stochastic nature of the physical process and incorporate a set of stochastic dynamical equations governing its evolution under the SPDC Hamiltonian. We demonstrate the effectiveness of our model through the design of structured nonlinear photonic crystals (NLPCs) and shaped pump beams; and show, theoretically and experimentally, how to generate maximally entangled states in the spatial degree of freedom. The learning of NLPC structures offers a promising new avenue for shaping and controlling arbitrary quantum states and enables all-optical coherent control of the generated states. We believe that this approach can readily be extended from bulky crystals to thin Metasurfaces and potentially applied to other quantum systems sharing a similar Hamiltonian structures, such as superfluids and superconductors.

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References · 3

  1. 2021E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentialscited by 708
  2. 2019Deep neural network solution of the electronic Schr"odinger equationcited by 127
  3. 2021Inverse Design of Quantum Holograms in Three-Dimensional Nonlinear Photonic Crystalscited by 3

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