Quantum memory devices with high storage efficiency and bandwidth are essential elements for future quantum networks. Solid-state quantum memories can provide broadband storage, but they primarily suffer from low storage efficiency. We use passive optimization and algorithmic optimization techniques to demonstrate nearly a sixfold enhancement in quantum memory efficiency. In this regime, we demonstrate coherent and single-photon-level storage with a high signal-to-noise ratio. The optimization technique presented here can be applied to most solid-state quantum memories to significantly improve the storage efficiency without compromising the memory bandwidth. Published by the American Physical Society 2024
Quantum memory devices with high storage efficiency and bandwidth are essential elements for future quantum networks. Solid-state quantum memories can provide broadband storage, but they primarily suffer from low storage efficiency. We use passive optimization and algorithmic optimization techniques to demonstrate nearly a sixfold enhancement in quantum memory efficiency. In this regime, we demonstrate coherent and single-photon-level storage with a high signal-to-noise ratio. The optimization technique presented here can be applied to most solid-state quantum memories to significantly improve the storage efficiency without compromising the memory bandwidth. Published by the American Physical Society 2024
Quantum memory devices with high storage efficiency and bandwidth are essential elements for future quantum networks. Solid-state quantum memories can provide broadband storage, but they primarily suffer from low storage efficiency. We use passive optimization and machine learning techniques to demonstrate nearly a 6-fold enhancement in quantum memory efficiency. In this regime, we demonstrate coherent and single-photon-level storage with a high signal-to-noise ratio. The optimization technique presented here can be applied to most solid-state quantum memories to significantly improve the storage efficiency without compromising the memory bandwidth.
Quantum memory devices with high storage efficiency and bandwidth are essential elements for future quantum networks. Solid-state quantum memories can provide broadband storage, but they primarily suffer from low storage efficiency. We use passive optimization and machine learning techniques to demonstrate more than 6-fold enhancement in quantum memory efficiency. In this regime, we demonstrate coherent and single-photon-level storage with a high signal-to-noise ratio. The optimization technique presented here can be applied to most solid-state quantum memories to significantly improve the storage efficiency without compromising the memory bandwidth.
A major challenge in quantum technologies is to build an efficient and long-lived quantum memory, particularly using solid-state devices. I will here report on an experiment where we combine the AFC optical memory with spin-echo techniques to extend the memory time from a few microseconds to about 1 ms, using an Europium-doped crystal. In general the spin-echo technique allows one to control the inhomogeneous spin dephasing which often sets the storage-time limit both in solid-state systems and laser-cooled gases. However, theoretically it is has been argued that spin-echo techniques would be extremely difficult to apply without creating noise in the case of a single quanta stored in a large spin ensemble. We here show how this noise can be limited and demonstrate high signal-to-noise ratio in the output mode when storing pulses at the single-photon level. Furthermore we stored polarization qubits encoded onto weak coherent , with fidelities surpassing a classical storage scheme.
Photonic quantum information processing is a key element for scalable quantum technologies, and has applications in secure long-distance quantum communication and connecting nodes of a quantum computation network. However, logical photon-photon gates and state-of-the-art single photon sources rely on probabilistic processes. Quantum memories are devices that enable storage and on-demand recall of quantum states of light, and have been highlighted as a vital component in photonic networks to overcome the scaling problem by synchronising probabilistic processes. The Raman memory has a large storage bandwidth and high synchronising capacity, and is an ideal candidate for local synchronisation. However, previous demonstrations of the Raman memory suffer from four-wave mixing noise, which prohibits quantum level operation. In this thesis I investigate methods to increase the signal to noise ratio in the Raman memory. I investigate increasing the light-matter coupling strength to boost the memory efficiency, and then explore two different methods to suppress four-wave mixing noise. I demonstrate that operating the Raman memory in a cavity is successful in reducing four-wave mixing, but it is technically challenging to maintain a high memory efficiency. I investigate a new method of noise suppression by introducing an absorption feature at the frequency of the unwanted noise field. This technically simple method is successful in reducing the noise by an order of magnitude, and will be applicable to many quantum memory protocols. In the final section of this thesis I explore the temporal mode properties of the Raman memory. I demonstrate that the Raman memory is single mode and can be used to separate and manipulate temporal modes of light. This positions the Raman memory as a key device for enabling high-dimensional photonic quantum information processing, and enhancing light-matter interactions. These results pave the way towards an efficient, low-noise, mode-selective quantum memory.
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.
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 a new 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 three-fold 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 new protocol is applicable to various memory architectures, paving the way toward scalable, efficient, low-noise, and high-bandwidth quantum memories.