Superpolynomial quantum enhancement in polaritonic neuromorphic computing

Xu, Huawen; Krisnanda, Tanjung; Verstraelen, Wouter; Liew, Timothy Chi Hin; Ghosh, Sanjib

doi:10.1103/physrevb.103.195302

Cited by 21 publications

(20 citation statements)

References 70 publications

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“…Despite these flexibilities, quantum reservoir computers were shown to perform tasks such as classification of quantum states, quantum state tomography, and state preparation, which are considered key computational tasks in quantum information theory. Recently, a polariton-based quantum reservoir computer was proposed to exhibit exponential quantum enhancement in image classification tasks [392] .…”

Section: Discussionmentioning

confidence: 99%

Microcavity exciton polaritons at room temperature

Ghosh

Zhao

et al. 2022

Photonics Insights

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The quest for realizing novel fundamental physical effects and practical applications in ambient conditions has led to tremendous interest in microcavity exciton polaritons working in the strong coupling regime at room temperature. In the past few decades, a wide range of novel semiconductor systems supporting robust exciton polaritons have emerged, which has led to the realization of various fascinating phenomena and practical applications. This paper aims to review recent theoretical and experimental developments of exciton polaritons operating at room temperature, and includes a comprehensive theoretical background, descriptions of intriguing phenomena observed in various physical systems, as well as accounts of optoelectronic applications. Specifically, an in-depth review of physical systems achieving room temperature exciton polaritons will be presented, including the early development of ZnO and GaN microcavities and other emerging systems such as organics, halide perovskite semiconductors, carbon nanotubes, and transition metal dichalcogenides. Finally, a perspective of outlooking future developments will be elaborated.

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Section: Discussionmentioning

confidence: 99%

Microcavity exciton polaritons at room temperature

Ghosh

Zhao

et al. 2022

Photonics Insights

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“…For time-dependent tasks, one study on quantum reservoir computing suggested that dissipation increases the processing capacity and the non-linearity of the embedding, at the price of a reduced memory capacity of the system [31]. An advantageous scaling of the performance of a quantum reservoir-computing scheme, as compared to its classical counterpart, was recently reported [32]. However, a systematic study of the dissipation and decoherence on quantum machine-learning models is missing.…”

Section: Introductionmentioning

confidence: 99%

Noisy Quantum Kernel Machines

Heyraud¹,

Li²,

Denis³

et al. 2022

Preprint

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“…The utmost example of this is provided by genuinely quantum tasks with no classical counterparts, that involve quantum inputs. This has stimulated many original works, ranging from quantum metrology [82,83] and quantum state control [84][85][86] to classical image recognition tasks with quantum hardware [87], under the name of quantum neuromorphic computing [88],…”

Section: Introductionmentioning

confidence: 99%

Photonic kernel machine learning for ultrafast spectral analysis

Denis,

Favero,

Ciuti

2021

Preprint

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We introduce photonic kernel machines, a scheme for ultrafast spectral analysis of noisy radiofrequency signals from single-shot optical intensity measurements. The approach combines the versatility of machine learning and the speed of photonic hardware to reach unprecedented throughput rates. We theoretically describe some of the key underlying principles, and then numerically illustrate the reached performances on a photonic lattice-based implementation. We apply the technique both to picosecond pulsed radio-frequency signals, on energy-spectral-density estimation and a shape classification task, and to continuous signals, on a frequency tracking task. The presented optical computing scheme is resilient to noise while requiring minimal control on the photonic-lattice parameters, making it readily implementable in realistic state-of-the-art photonic platforms.

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Superpolynomial quantum enhancement in polaritonic neuromorphic computing

Cited by 21 publications

References 70 publications

Microcavity exciton polaritons at room temperature

Microcavity exciton polaritons at room temperature

Noisy Quantum Kernel Machines

Photonic kernel machine learning for ultrafast spectral analysis

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