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Conference on Lasers and Electro-Optics

Optimization of Broadband Λ-type Quantum Memory Using Gaussian Pulses

Kai Shinbrough, B. D. Hunt, Virginia O. Lorenz

Published Jan 1, 2021• 1 citation
Publisher

Abstract

We optimize the efficiency of broadband Λ-type quantum memories under the restriction of Gaussian-shape optical fields. We demonstrate an experimentally-simple path to enhancing memory efficiency over a wide range of broadband memory parameters.
DOI
10.1364/cleo_at.2021.jtu3a.57

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Optical quantum memory--the ability to store photonic quantum states and retrieve them on demand--is an essential resource for emerging quantum technologies and photonic quantum information protocols. Simultaneously achieving high efficiency and high-speed, broadband operation is an important task necessary for enabling these applications. In this work, we investigate the optimization of a large class of optical quantum memory protocols based on resonant interaction with ensembles of Λ\LambdaΛ-type level systems with the restriction that the temporal envelope of all optical fields must be Gaussian, which reduces experimental complexity. We show that for overlapping signal and control fields there exists a unique and broadband pulse duration that optimizes the memory efficiency, and that this optimized efficiency can be close to the protocol-independent bound. We further optimize over the control field temporal delay and pulse duration, demonstrating saturation of this efficiency bound over a broad range of pulse durations while clarifying the underlying physics of the quantum memory interaction.
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
Photonic quantum memory is a crucial elementary operation in photonic quantum information processing. While many physically distinct memory protocols and hardware implementations have been applied to this task, the development of a quantum memory performant in all relevant metrics simultaneously (e.g., efficiency, bandwidth, lifetime, etc.) is still an open challenge. In this work, we focus on inhomogeneously broadened ensembles of ΛΛΛ-type quantum emitters, which have long coherence lifetimes and broad bandwidth compatibility, but tend to exhibit low efficiency, in part due to technical constraints on medium growth and preparation, and in part due to inefficient use of a key resource in these systems: the inhomogeneously broadened excited state lineshape. We investigate the properties of electromagnetically induced transparency (EIT) for a survey of inhomogeneous lineshapes that are straightforward to realize experimentally, and optimize the memory efficiency for each lineshape over a large range of experimental parameters. We compare the optimal EIT efficiency to the well-known atomic frequency comb (AFC) protocol, which also relies on spectral shaping of the inhomogeneous broadening, and observe that with sufficient control field power the optimized lineshapes allow more efficient storage. Finally, we optimize over the inhomogeneous lineshape in a protocol agnostic fashion by numerically constructing the linear integral kernel describing the memory interaction and using a singular value decomposition and interpolation procedure to ensure optimality of the resulting lineshape.
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.