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Tracing out the environmental degrees of freedom is a necessary procedure when simulating open quantum systems. While being an essential step in deriving a tractable master equation it represents a loss of information. In situations where…

Quantum Physics · Physics 2022-11-02 Dominic Gribben , Aidan Strathearn , Gerald E. Fux , Peter Kirton , Brendon W. Lovett

The dynamics of open quantum system are often modeled by non-Markovian processes that account for memory effects arising from interactions with the environment. It is well-known that the memory provided by the environment can be classical…

Quantum Physics · Physics 2025-10-22 Charlotte Bäcker , Konstantin Beyer , Walter T. Strunz

Quantum non-Markovianity represents memory during the system dynamics, which is typically weakened by the temperature. We here study the effects of environmental temperature on the non-Markovianity of an open quantum system by virtue of…

Quantum Physics · Physics 2018-06-13 Zhong-Xiao Man , Yun-Jie Xia , Rosario Lo Franco

We employ the theoretical framework of positive operator valued measures, to study Markovian open quantum systems. In particular, we discuss how a quantum system influences its environment. Using the theory of indirect measurements, we then…

Quantum Physics · Physics 2010-09-23 Ingo Kamleitner

Understanding how external driving and dissipation jointly influence the dynamics of open quantum systems is essential for advancing the study of non-equilibrium quantum phenomena and developing quantum technologies. The present study…

Quantum Physics · Physics 2025-05-14 Roie Dann

In the current era of noisy intermediate-scale quantum (NISQ) devices, research in the theory of open system dynamics has a crucial role to play. In particular, understanding and quantifying memory effects in quantum systems is critical to…

Quantum Physics · Physics 2023-06-01 U. Shrikant , Prabha Mandayam

In the last years, the application of machine learning methods has become increasingly relevant in different fields of physics. One of the most significant subjects in the theory of open quantum systems is the study of the characterization…

Quantum Physics · Physics 2021-03-03 Felipe F. Fanchini , Göktuğ Karpat , Daniel Z. Rossatto , Ariel Norambuena , Raúl Coto

Machine learning methods have proved to be useful for the recognition of patterns in statistical data. The measurement outcomes are intrinsically random in quantum physics, however, they do have a pattern when the measurements are performed…

Quantum Physics · Physics 2020-04-14 I. A. Luchnikov , S. V. Vintskevich , D. A. Grigoriev , S. N. Filippov

We consider the dynamics of a collisional model in which both the system and environment are embodied by spin-$1/2$ particles. In order to include non-Markovian features in our model we introduce interactions among the environmental qubits…

Quantum Physics · Physics 2017-08-15 B. Çakmak , M. Pezzutto , M. Paternostro , Ö. E. Müstecaplıoğlu

The dynamics of systems subjected to noise is called Markovian in the absence of memory effects, i.e. when its immediate future only depends on its present. Time correlations in the noise source may generate non-Markovian effects that,…

Quantum Physics · Physics 2017-03-22 Nadja K. Bernardes , Andre R. R. Carvalho , C. H. Monken , Marcelo F. Santos

We study quantum non-Markovian dynamics of the Caldeira-Leggett model, a prototypical model for quantum Brownian motion describing a harmonic oscillator linearly coupled to a reservoir of harmonic oscillators. Employing the exact analytical…

Quantum Physics · Physics 2020-09-02 Simon Einsiedler , Andreas Ketterer , Heinz-Peter Breuer

Discovering interaction effects on a response of interest is a fundamental problem faced in biology, medicine, economics, and many other scientific disciplines. In theory, Bayesian methods for discovering pairwise interactions enjoy many…

Computation · Statistics 2022-11-15 Raj Agrawal , Jonathan H. Huggins , Brian Trippe , Tamara Broderick

A collision model (CM) is a framework to describe open quantum dynamics. In its {\it memoryless} version, it models the reservoir $\mathcal R$ as consisting of a large collection of elementary ancillas: the dynamics of the open system…

Quantum Physics · Physics 2017-09-13 Salvatore Lorenzo , Francesco Ciccarello , G. Massimo Palma

Collision models (CMs) describe an open system interacting in sequence with elements of an environment, termed ancillas. They have been established as a useful tool for analyzing non-Markovian open quantum dynamics based on the ability to…

Quantum Physics · Physics 2025-11-06 Graeme Pleasance , Angel E. Neira , Marco Merkli , Francesco Petruccione

Gaussian processes are arguably the most important class of spatiotemporal models within machine learning. They encode prior information about the modeled function and can be used for exact or approximate Bayesian learning. In many…

We present a comprehensive and up to date review on the concept of quantum non-Markovianity, a central theme in the theory of open quantum systems. We introduce the concept of quantum Markovian process as a generalization of the classical…

Quantum Physics · Physics 2014-08-26 Ángel Rivas , Susana F. Huelga , Martin B. Plenio

We present an extended collision model to simulate the dynamics of an open quantum system. In our model, the unit to represent the environment is, instead of a single particle, a block which consists of a number of environment particles.…

Quantum Physics · Physics 2018-05-11 Jiasen Jin , Chang-shui Yu

An operational (measurement based) scheme that connects measurement invasiveness and the presence of non-classical memory effects in open quantum systems is defined. Its underlying theoretical basis relies on a non-invasive measurability of…

Quantum Physics · Physics 2025-07-09 Adrián A. Budini

We study discrete quantum dynamics where single evolution step consists of unitary system transformation followed by decoherence via coupling to an environment. Often non-Markovian memory effects are attributed to structured environments…

Quantum Physics · Physics 2016-06-22 Kimmo Luoma , Jyrki Piilo

Gaussian processes provide a flexible, non-parametric framework for the approximation of functions in high-dimensional spaces. The covariance kernel is the main engine of Gaussian processes, incorporating correlations that underpin the…

Machine Learning · Statistics 2024-03-20 Dionissios T. Hristopulos