Diffractive neural networks for mode-sorting with flexible detection regions

Optics & Laser Technology Elsevier 195 (2026) 114544

Authors:

Kaden Bearne, Alexander Duplinskiy, Matthew J Filipovich, AI Lvovsky

Abstract:

Mode-sorting is a procedure that decomposes a light field into a basis of transverse modes, directing each mode into a separate spatial location, allowing the constituent mode intensities to be measured simultaneously. We demonstrate a mode-sorter based on a diffractive optical neural network and show that it is advantageous to include the output detection regions in the trainable set of parameters of that network. This approach outperforms traditional mode-sorting methods, achieving lower crosstalk levels for the same efficiency. For example, in sorting 25 Hermite-Gaussian modes with a 3 plate sorter, at 12 % efficiency, the experimentally measured crosstalk decreases from 37.5 % for fixed detection to 8.7 % for flexible detection.

Machine learning of quantum data using optimal similarity measurements

ArXiv 2602.23501 (2026)

Authors:

Zhenghao Li, Hao Zhan, Shana H Winston, Ewan Mer, Zhenghao Yin, Shang Yu, Yazeed K Alwehaibi, Gerard J Machado, Dayne Marcus Lopena, Lijian Zhang, MS Kim, Aonan Zhang, Ian A Walmsley, Raj B Patel

Time Crystals as Passively Protected Oscillating Qubits

(2026)

Authors:

Mert Esencan, AI Lvovsky, Berislav Buča

Enhancing quantum memories with light–matter interference

Optica Optica Publishing Group 12:9 (2025) 1514

Authors:

Paul M Burdekin, Ilse Maillette de Buy Wenniger, Steven Sagona-Stophel, Jerzy Szuniewicz, Aonan Zhang, Sarah E Thomas, Ian A Walmsley

Abstract:

Future optical quantum technologies, such as quantum networks, distributed quantum computing and sensing, demand efficient, broadband quantum memories. However, achieving high efficiency without introducing noise, reducing bandwidth, or limiting scalability remains a challenge. Here, we present an approach to enhance quantum memory protocols by leveraging constructive light–matter interference, leading to an increase in memory efficiency without increasing atomic density or laser intensity. We implement this method in a Raman quantum memory in warm cesium vapor and achieve more than a threefold improvement in total efficiency, reaching (34.3±8.4)%, while retaining GHz-bandwidth operation and low noise levels. Numerical simulations predict that this approach can boost efficiencies in systems limited by atomic density, such as cold atomic ensembles, from 65% to beyond 96%, while in warm atomic vapors, it could reduce the laser intensity needed to reach a given efficiency by over an order-of-magnitude, exceeding 95% total efficiency. Furthermore, our method preserves the single-mode nature of the memory at high efficiencies. This protocol is applicable to various memory architectures, paving the way toward scalable, efficient, low-noise, and high-bandwidth quantum memories.

A nanoscopic light swing

Newton Elsevier 1:5 (2025) 100164

Abstract:

Large arrays of optical parametric oscillators can solve combinatorial optimization problems with potential quantum advantage but are challenging to realize. Gray et al. developed a photonic chip with this capability and elaborated a method to bring these oscillators into controllable interaction, opening new possibilities in quantum and classical optical computing.