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Long-lived quantum memories are essential components of a long-standing goal of remote distribution of entanglement in quantum networks. These can be realized by storing the quantum states of light as single-spin excitations in atomic…

Significant advances in coherence have made superconducting quantum circuits a viable platform for fault-tolerant quantum computing. To further extend capabilities, highly coherent quantum systems could act as quantum memories for these…

A qubit memory is the building block for quantum information. Cavity-enhanced spin-wave-photon entanglement has been achieved by applying dual-control modes. However, owing to cross readouts between the modes, the qubit retrieval efficiency…

Quantum Physics · Physics 2021-10-22 Minjie Wang , Shengzhi Wang , Tengfei Ma , Ya Li , Yan Xie , Haole Jiao , Hailong Liu , Shujing Li , Hai Wang

Inhomogeneously broadened spin ensembles play an important role in present-day implementation of hybrid quantum processing architectures. When coupled to a resonator such an ensemble may serve as a multi-mode quantum memory for the…

Quantum Physics · Physics 2013-12-23 Brian Julsgaard , Klaus Mølmer

Spin-boson models can describe a variety of physical systems, such as atoms in a cavity or vibrating ion chains. In equilibrium these systems often feature a radical change in their behavior when switching from weak to strong spin-boson…

Quantum Physics · Physics 2020-08-19 Eliana Fiorelli , Matteo Marcuzzi , Pietro Rotondo , Federico Carollo , Igor Lesanovsky

In this paper, we show that quantum memory for qudit states encoded in a single photon pulsed optical field has a conceptually simple modular realization using only passive linear optics and coherent feedback. We exploit the idea that two…

Quantum Physics · Physics 2015-08-03 Hendra I. Nurdin , John E. Gough

We propose a cavity QED setup which implements a dissipative Lipkin-Meshkov-Glick model -- an interacting collective spin system. By varying the external model parameters the system can be made to undergo both first-and second-order quantum…

Quantum Physics · Physics 2008-05-07 S. Morrison , A. S. Parkins

Associative memories in the brain receive and store patterns of activity registered by the sensory neurons, and are able to retrieve them when necessary. Due to their importance in human intelligence, computational models of associative…

Machine Learning · Computer Science 2021-09-17 Tommaso Salvatori , Yuhang Song , Yujian Hong , Simon Frieder , Lei Sha , Zhenghua Xu , Rafal Bogacz , Thomas Lukasiewicz

Classical autoassociative memory models have been central to understanding emergent computations in recurrent neural circuits across diverse biological contexts. However, they typically neglect neuromodulatory agents that are known to…

Neurons and Cognition · Quantitative Biology 2025-12-17 Daiki Goto , Hector Manuel Lopez Rios , Monika Scholz , Suriyanarayanan Vaikuntanathan

Practical realizations of quantum repeaters require quantum memory simultaneously providing high retrieval efficiency, long lifetime and multimode storages. So far, the combination of high retrieval efficiency and spatially multiplexed…

Quantum Physics · Physics 2023-07-25 Minjie Wang , Haole Jiao , Jiajin Lu , Wenxin Fan , Zhifang Yang , Mengqi Xi , Shujing Li , Hai Wang

Bose-Einstein condensates are a promising platform for optical quantum memories, but suffer from several decoherence mechanisms, leading to short memory lifetimes. While some of these decoherence effects can be mitigated by conventional…

Atomic Physics · Physics 2023-07-07 Elisa Da Ros , Simon Kanthak , Erhan Sağlamyürek , Mustafa Gündoğan , Markus Krutzik

We introduce a hybrid optomechanical system containing an annularly trapped Bose-Einstein condensate (BEC) inside an optical cavity driven by Lauguerre-Gaussian (LG) modes. Spiral phase elements serve as the end mirrors of the cavity such…

Quantum Physics · Physics 2024-07-03 Sanket Das , Pardeep Kumar , M. Bhattacharya , Tarak N. Dey

In this paper, we present a neural network system related to about memory and recall that consists of one neuron group (the "cue ball") and a one-layer neural net (the "recall net"). This system realizes the bidirectional memorization…

Neural and Evolutionary Computing · Computer Science 2022-10-11 Hiroshi Inazawa

The recently increasing explorations for cavity optomechanical coupling assisted by a single atom or an atomic ensemble have opened an experimentally accessible fashion to interface quantum optics and nano (micro) -mechanical systems. In…

Quantum Physics · Physics 2015-05-13 Yue Chang , H. Ian , C. P. Sun

Many-body cavity QED experiments are established platforms to tailor and control the collective responses of ensembles of atoms, interacting through one or more common photonic modes. The rich diversity of dynamical phases they can host,…

Effective multi-mode photon echo based quantum memory on multi-atomic ensemble in the QED cavity is proposed. Analytical solution is obtained for the quantum memory efficiency that can be equal unity when optimal relations for the cavity…

Quantum Physics · Physics 2025-02-06 Sergey A. Moiseev , Sergey N. Andrianov , Firdus F. Gubaidullin

Atoms coupled to cavities provide an exciting playground for the study of fundamental interactions of atoms mediated through a common channel. Many of the applications of cavity-QED and cold-atom experiments more broadly, suffer from…

Krotov and Hopfield (2021) proposed a biologically plausible two-layer associative memory network with memory storage capacity exponential in the number of visible neurons. However, the capacity was only linear in the number of hidden…

Neurons and Cognition · Quantitative Biology 2026-03-11 Mohadeseh Shafiei Kafraj , Dmitry Krotov , Peter E. Latham

The efficiency of an ensemble-based optical quantum memory depends critically on the strength of the atom-light coupling. An optical cavity is an effective method to enhance atom-light coupling strength, with the drawback that cavities can…

Quantum reservoir computing (QRC) offers a promising framework for online quantum-enhanced machine learning tailored to temporal tasks, yet practical implementations with native memory capabilities remain limited. Here, we demonstrate an…