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We present a detailed analysis of slowly driven quantum thermal machines based on interacting qubits within the framework of the Lindblad master equation. By implementing a systematic expansion in the driving rate, we derive explicit…

Quantum Physics · Physics 2026-05-27 Gerónimo J. Caselli , Luis O. Manuel , Liliana Arrachea

Open quantum systems exhibit dynamics ranging from unitary evolution to irreversible dissipation. While the Gorini--Kossakowski--Sudarshan--Lindblad (GKSL) equation uniquely characterizes Markovian CPTP evolution, many physical platforms…

Quantum Physics · Physics 2026-03-05 Bo Peng , Yu Zhang

Recent experimental tests of Bell inequalities confirm that entangled quantum systems cannot be described by local classical theories but still do not answer the question whether or not quantum systems could in principle be modelled by…

Quantum Physics · Physics 2024-03-07 Kawthar Al Rasbi , Lewis A. Clark , Almut Beige

Understanding dissipation in open quantum systems is crucial for the development of robust quantum technologies. In this work, we introduce a Transformer-based machine learning framework to infer time-dependent dissipation rates in quantum…

Quantum Physics · Physics 2025-05-13 Chi-Sheng Chen , En-Jui Kuo

Quantum Recurrent Neural Networks (QRNNs) are robust candidates for modelling and predicting future values in multivariate time series. However, the effective implementation of some QRNN models is limited by the need for mid-circuit…

Quantum Physics · Physics 2025-01-31 José Daniel Viqueira , Daniel Faílde , Mariamo M. Juane , Andrés Gómez , David Mera

In this work, we develop a protocol for learning a time-independent Lindblad model for operations that can be applied repeatedly on a quantum computer. The protocol is highly scalable for models with local interactions and is in principle…

Quantum Physics · Physics 2025-12-10 Ewout van den Berg , Brad Mitchell , Ken Xuan Wei , Moein Malekakhlagh

We present a quantum algorithm for simulating open quantum systems coupled to Gaussian environments valid for any configuration and coupling strength. The algorithm is applicable to problems with strongly coupled, or non-Markovian,…

Quantum Physics · Physics 2025-11-20 Hans Michael Christensen , Johannes Agerskov , Frederik Nathan

Recent advancements in quantum hardware and classical computing simulations have significantly enhanced the accessibility of quantum system data, leading to an increased demand for precise descriptions and predictions of these systems.…

Quantum Physics · Physics 2025-03-31 Zheng An , Jiahui Wu , Zidong Lin , Xiaobo Yang , Keren Li , Bei Zeng

This paper continues on the program of developing a relativistic quantum information theory in terms of unequal-time correlation functions in quantum field theory (QFT)[arXiv:2208.03696]. Here, we focus on the definition of quantum…

Quantum Physics · Physics 2024-11-19 Charis Anastopoulos , Konstantina Savvidou

Quantum coherence and quantum correlations are studied in the strongly interacting system composed of two qubits and an oscillator with the presence of a parametric medium. To analytically solve the system, we employ the adiabatic…

Quantum Physics · Physics 2021-12-14 V. Yogesh , Prosenjit Maity

In this article we reconsider a version of quantum trajectory theory based on the stochastic Schr\"odinger equation with stochastic coefficients, which was mathematically introduced in the '90s, and we develop it in order to describe the…

Quantum Physics · Physics 2012-10-30 Alberto Barchielli , Matteo Gregoratti

We propose a nonlinear function-on-function regression model where both the covariate and the response are random functions. The nonlinear regression is carried out in two steps: we first construct Hilbert spaces to accommodate the…

Methodology · Statistics 2022-07-19 Peijun Sang , Bing Li

The computation of dynamical response functions is central to many problems in condensed matter physics. Owing to the rapid growth of quantum correlations following a quench, classical methods face significant challenges even if an…

Quantum Physics · Physics 2025-05-09 Esther Cruz , Dominik S. Wild , Mari Carmen Bañuls , J. Ignacio Cirac

The field of artificial neural networks is expected to strongly benefit from recent developments of quantum computers. In particular, quantum machine learning, a class of quantum algorithms which exploit qubits for creating trainable neural…

Quantum Physics · Physics 2022-01-12 Marco Maronese , Claudio Destri , Enrico Prati

Estimating the dissipativity of nonlinear systems from empirical data is useful for the analysis and control of nonlinear systems, especially when an accurate model is unavailable. Based on a Koopman operator model of the nonlinear system…

Systems and Control · Electrical Eng. & Systems 2026-04-03 Xiuzhen Ye , Wentao Tang

Response functions of quantum systems, such as electron Green's functions, magnetic, or charge susceptibilities, describe the response of a system to an external perturbation. They are the central objects of interest in field theories and…

Quantum Physics · Physics 2024-02-01 Alexander F. Kemper , Chao Yang , Emanuel Gull

Quantum reservoir computing is a class of quantum machine learning algorithms involving a reservoir of an echo state network based on a register of qubits, but the dependence of its memory capacity on the hyperparameters is still rather…

Quantum Physics · Physics 2023-02-24 Riccardo Molteni , Claudio Destri , Enrico Prati

We propose a simple method to estimate the parameters of a continuously measured quantum system, by fitting correlation functions of the measured signal. We demonstrate the approach in simulation, both on toy examples and on a recent…

Quantum Physics · Physics 2024-10-17 Pierre Guilmin , Pierre Rouchon , Antoine Tilloy

We analyse nonperturbatively signal transmission patterns in Green's functions of interacting quantum fields. Quantum field theory is re-formulated in terms of the nonlinear quantum-statistical response of the field. This formulation…

Quantum Physics · Physics 2008-11-26 L. I. Plimak , S. Stenholm

Out-of-equilibrium quantum many-body systems exhibit rapid correlation buildup that underlies many emerging phenomena. Exact wave-function methods to describe this scale exponentially with particle number; simpler mean-field approaches…

Machine Learning · Computer Science 2026-05-06 Patrick Egenlauf , Iva Březinová , Sabine Andergassen , Miriam Klopotek