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quant-ph2026

A Single Atom in Front of a Mirror is a Universal Reservoir Computer

Peter J. Ehlers, Phi Hung Nguyen, Kanu Sinha +4

Universal approximation in reservoir computing is typically associated with a class of reservoirs. We show that universality can be associated with a single reservoir, considering…

quant-ph2026

Computational Superiority of Non-Markovian Kerr Feedback in Continuous-Variable Quantum Reservoir Computing

Daniel Soh

A linear optical medium can delay, mix, and superpose light, but never make two pulses multiply: multiplication is nonlinear, and a linear system has no such operation. This roots…

quant-ph2025

Quantum optical neural networks using atom-cavity interactions to provide all-optical nonlinearity

Chuanzhou Zhu, Tianyu Wang, Peter L. McMahon +1

Optical neural networks (ONNs) have been developed to enhance processing speed and energy efficiency in machine learning by leveraging optical devices for nonlinear activation and…

quant-ph2025

Minimalistic and Scalable Quantum Reservoir Computing Enhanced with Feedback

Chuanzhou Zhu, Peter J. Ehlers, Hendra I. Nurdin +1

Quantum Reservoir Computing (QRC) leverages quantum systems to perform complex computational tasks with exceptional efficiency and reduced energy consumption. We introduce a minima…

quant-ph2025

Practical Few-Atom Quantum Reservoir Computing

Chuanzhou Zhu, Peter J. Ehlers, Hendra I. Nurdin +1

Quantum Reservoir Computing (QRC) harnesses quantum systems to tackle intricate computational problems with exceptional efficiency and minimized energy usage. This paper presents a…

quant-ph2025

Optical Gottesman-Kitaev-Preskill qubit generation via approximate squeezed coherent state superposition breeding

Andrew J. Pizzimenti, Daniel Soh

Gottesman-Kitaev-Preskill (GKP) qubits, known for their exceptional error-correction capabilities, are highly coveted in quantum computing. However, generating optical GKP qubits h…