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The combination of machine learning and quantum computing has emerged as a promising approach for addressing previously untenable problems. Reservoir computing is an efficient learning paradigm that utilizes nonlinear dynamical systems for…

Quantum Physics · Physics 2020-08-26 Jiayin Chen , Hendra I. Nurdin , Naoki Yamamoto

We investigate a long time asymptotic state of periodically driven open quantum systems analytically. The model we consider in this paper is a free fermionic system coupled to an energy and particle reservoir. We clarify some generic…

Statistical Mechanics · Physics 2016-11-14 Koudai Iwahori , Norio Kawakami

The use of quantum scissors, as candidates for non-deterministic amplifiers, in continuous-variable quantum key distribution systems is investigated. Such devices rely on single-photon sources for their operation and as such, they do not…

Quantum Physics · Physics 2020-07-16 Masoud Ghalaii , Carlo Ottaviani , Rupesh Kumar , Stefano Pirandola , Mohsen Razavi

Losses are ubiquitous in physics and are usually regarded as harmful in quantum information processing. Here, we propose a loss-induced scheme to achieve nonreciprocity and nonreciprocal entanglement in a superconducting platform, where two…

Quantum Physics · Physics 2026-05-27 Yu-Meng Ren , Peng-Bo Li

Quantum reservoir computing employs fixed quantum dynamics as a feature map for machine learning. Integrating multiple quantum reservoirs, however, raises a key question: how few inter-module connections are sufficient to match the…

Quantum Physics · Physics 2025-11-17 Hon Wai Lau , Aoi Hayashi , Akitada Sakurai , William John Munro , Kae Nemoto

The characterization of irreversibility in general quantum processes is an open problem of increasing techno- logical relevance. Yet, the tools currently available to this aim are mostly limited to the assessment of dynamics induced by…

Quantum Physics · Physics 2017-06-06 Jader P. Santos , Gabriel T. Landi , Mauro Paternostro

Novel categories of electronic devices and quantum materials are obtained by pipelining the unitary evolution of electron quantum states as described by Schroedinger's equation with non-unitary processes that interrupt the coherent…

Mesoscale and Nanoscale Physics · Physics 2021-03-24 J. Mannhart , H. Boschker , P. Bredol

In active fluids and active solids the constituents individually generate movement by each extracting energy from their environment or from their own source. Non-reciprocal interactions among these active constituents then enable novel…

Soft Condensed Matter · Physics 2025-03-18 Brady Wu , Qinghao Mao , Bryan VanSaders , Heinrich M. Jaeger

We propose a general approach of protecting a two-level system against decoherence via quantum engineering of non-classical multiple superpositions of coherent states in a non-Markovian reservoir. The scheme surprisingly only uses the…

Mesoscale and Nanoscale Physics · Physics 2015-06-15 Katarzyna Roszak , Radim Filip , Tomáš Novotný

Measurement-based quantum computation with optical time-domain multiplexing is a promising method to realize a quantum computer from the viewpoint of scalability. Fault tolerance and universality are also realizable by preparing appropriate…

A general formalism to describe the dynamics of quantum emitters in structured reservoirs is introduced. As an application, we investigate the optical coherence of an atom-like emitter diagonally coupled via a link-boson to a structured…

Quantum Physics · Physics 2019-05-14 Nikolett Német , Scott Parkins , Andreas Knorr , Alexander Carmele

We propose an effective Hamiltonian approach to investigate decoherence of a quantum system in a non-Markovian reservoir, naturally imposing the complete positivity on the reduced dynamics of the system. The formalism is based on the notion…

Quantum Physics · Physics 2007-05-23 Jinhyoung Lee , Inbo Kim , Helen McAneney , M. S. Kim , Doyeol Ahn

We present a general framework for evolutionary learning to emergent unbiased state representation without any supervision. Evolutionary frameworks such as self-play converge to bad local optima in case of multi-agent reinforcement learning…

Machine Learning · Statistics 2023-02-03 Shohei Ohsawa

In this paper, we investigate preservation of quantum coherence of a single-qubit interacting with a zero-temperature thermal reservoir through the addition of noninteracting qubits in the reservoir. Moreover, we extend this scheme to…

Quantum Physics · Physics 2017-11-22 Naghi Behzadi , Bahram Ahansaz , Esfandyar Faizi

Device-independent protocols use nonlocality to certify that they are performing properly. This is achieved via Bell experiments on entangled quantum systems, which are kept isolated from one another during the measurements. However, with…

Quantum Physics · Physics 2013-03-26 Jonathan Silman , Stefano Pironio , Serge Massar

We investigate the dynamics of giant atom(s) in a waveguide QED scenario, where the atom couples to the coupled resonator waveguide via two sites. For a single giant atom setup, we find that the atomic dissipation rate can be adjusted by…

Quantum Physics · Physics 2021-08-04 Hongwei Yu , Zhihai Wang , Jin-Hui Wu

We investigate perfect optical nonreciprocal transmission in a hybrid optomechanical system that incorporates an atomic ensemble. By introducing complex coupling strengths between the atomic ensemble and a mechanical oscillator,…

Microwave-optical entanglement is essential for efficient quantum communication, secure information transfer, and integrating microwave and optical quantum systems to advance hybrid quantum technologies. In this work, we demonstrate how the…

Quantum Physics · Physics 2025-04-30 Ming-Yue Liu , Yuan Gong , Jiaojiao Chen , Yan-Wei Wang , Wei Xiong

Out of equilibrium, the lack of reciprocity is the rule rather than the exception. Non-reciprocal interactions occur, for instance, in networks of neurons, directional growth of interfaces, and synthetic active materials. While wave…

Soft Condensed Matter · Physics 2021-04-20 Michel Fruchart , Ryo Hanai , Peter B. Littlewood , Vincenzo Vitelli

Quantum reservoir computing has emerged as a promising paradigm within the field of quantum machine learning, harnessing the inherent properties of quantum systems to optimise and enhance information processing capabilities. Here, we…

Quantum Physics · Physics 2025-09-03 Adam Burgess , Marian Florescu