SPDCinv: Inverse Quantum-Optical Design of High-Dimensional Qudits
Eyal Rozenberg, Aviv Karnieli, Ofir Yesharim, Joshua Foley-Comer,, Sivan Trajtenberg-Mills, Daniel Freedman, Alex M. Bronstein, and Ady Arie

TL;DR
This paper introduces a physically-constrained, differentiable model for inverse quantum-optical design in SPDC processes, enabling precise generation of high-dimensional entangled states for quantum information applications.
Contribution
It presents a novel, fully differentiable model that accurately captures all interactions in SPDC, allowing inverse design of quantum states with tailored properties.
Findings
Successfully designed pump shapes and holograms for desired quantum states
Validated model against experimental results with high accuracy
Demonstrated control over entanglement and state properties
Abstract
Spontaneous parametric down-conversion in quantum optics is an invaluable resource for the realization of high-dimensional qudits with spatial modes of light. One of the main open challenges is how to directly generate a desirable qudit state in the SPDC process. This problem can be addressed through advanced computational learning methods; however, due to difficulties in modeling the SPDC process by a fully differentiable algorithm that takes into account all interaction effects, progress has been limited. Here, we overcome these limitations and introduce a physically-constrained and differentiable model, validated against experimental results for shaped pump beams and structured crystals, capable of learning every interaction parameter in the process. We avoid any restrictions induced by the stochastic nature of our physical model and integrate the dynamic equations governing the…
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Taxonomy
TopicsQuantum Information and Cryptography · Neural Networks and Reservoir Computing · Cold Atom Physics and Bose-Einstein Condensates
