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Characterizing the memory properties of the environment has become critical for the high-fidelity control of qubits and other advanced quantum systems. However, current non-Markovian tomography techniques are either limited to discrete…

We consider a class of quantum dissipative systems governed by a one parameter completely positive maps on a von-Neumann algebra. We introduce a notion of recurrent and metastable projections for the dynamics and prove that the unit…

Operator Algebras · Mathematics 2007-05-23 Anilesh Mohari

We investigate the emergence of non-Markovian dynamics in finite-dimensional open quantum systems governed by Weyl dynamical maps and their convex combinations. Using the Hermite normal form, we provide a complete classification of the…

Quantum Physics · Physics 2026-05-25 Wen Xu , Vinayak Jagadish

We develop a data-driven framework for identifying non-Markovian dynamical equations of motion for open quantum systems. Starting from the Nakajima--Zwanzig formalism, we vectorize the reduced density matrix into a four-dimensional state…

Quantum Physics · Physics 2026-01-15 Jimmie Adriazola , Katarzyna Roszak

Coupling between quantum and classical systems is consistent, provided the evolution is linear in the state space, preserves the split of systems into quantum and classical degrees of freedom, and preserves probabilities. The evolution law…

Quantum Physics · Physics 2022-03-04 Jonathan Oppenheim , Carlo Sparaciari , Barbara Šoda , Zachary Weller-Davies

We address the problem of quantifying the non-Markovian character of quantum time-evolutions of general systems in contact with an environment. We introduce two different measures of non-Markovianity that exploit the specific traits of…

Quantum Physics · Physics 2010-07-29 Ángel Rivas , Susana F. Huelga , Martin B. Plenio

By modeling the interaction of a system with an environment through a renewal approach, we demonstrate that completely positive non-Markovian dynamics may develop some unexplored non-standard statistical properties. The renewal approach is…

Quantum Physics · Physics 2009-08-07 Adrian A. Budini Paolo Grigolini

We analyze the non-Markovianity degree for random unitary evolution of d-level quantum systems. It is shown how non-Markovianity degree is characterized in terms of local decoherence rates. In particular we derive a sufficient condition for…

Quantum Physics · Physics 2016-11-18 Dariusz Chruściński , Filip A. Wudarski

We analyze recent approaches to quantum Markovianity and how they relate to the proper definition of quantum memory. We point out that the well-known criterion of information backflow may not correctly report character of the memory falsely…

Quantum Physics · Physics 2020-08-31 Michal Banacki , Marcin Marciniak , Karol Horodecki , Pawel Horodecki

Quantum systems coupled to environments exhibit intricate dynamics. The master equation gives a Markov approximation of the dynamics, allowing for analytic and numerical treatments. It is ubiquitous in theoretical and applied quantum…

Quantum Physics · Physics 2021-12-17 Marco Merkli

A novel framework for the analysis of observation statistics on time discrete linear evolutions in Banach space is presented. The model differs from traditional models for stochastic processes and, in particular, clearly distinguishes…

Statistics Theory · Mathematics 2017-01-24 Ulrich Faigle , Gerhard Gierz

The Wigner-Liouville equation is reformulated using a spectral decomposition of the classical force field instead of the potential energy. The latter is shown to simplify the Wigner-Liouville kernel both conceptually and numerically as the…

Mesoscale and Nanoscale Physics · Physics 2018-01-29 Maarten L. Van de Put , Bart Sorée , Wim Magnus

The simulation of quantum processes is a key goal for the grand programme aiming at grounding quantum technologies as the way to explore complex phenomena that are inaccessible through standard, classical calculators. Some interesting steps…

Quantum Physics · Physics 2013-06-12 Andrea Chiuri , Chiara Greganti , Laura Mazzola , Mauro Paternostro , Paolo Mataloni

Quantum machine learning is a growing research field that aims to perform machine learning tasks assisted by a quantum computer. Kernel-based quantum machine learning models are paradigmatic examples where the kernel involves quantum…

Quantum Physics · Physics 2023-02-06 Diego Tancara , Hossein T. Dinani , Ariel Norambuena , Felipe F. Fanchini , Raúl Coto

Markovian master equations (formally known as quantum dynamical semigroups) can be used to describe the evolution of a quantum state $\rho$ when in contact with a memoryless thermal bath. This approach has had much success in describing the…

Quantum Physics · Physics 2017-08-18 Álvaro M. Alhambra , Mischa P. Woods

Quantum simulation is a powerful tool to study the properties of quantum systems. The dynamics of open quantum systems are often described by Completely Positive (CP) maps, for which several quantum simulation schemes exist. We present a…

Quantum Physics · Physics 2023-12-22 Mirko Rossini , Dominik Maile , Joachim Ankerhold , Brecht I. C Donvil

It is known that the dynamical evolution of a system, from an initial tensor product state of system and environment, to any two later times, t1,t2 (t2>t1), are both completely positive (CP) but in the intermediate times between t1 and t2…

Quantum Physics · Physics 2013-05-07 A. R. Usha Devi , A. K. Rajagopal , Sudha , R. W. Rendell

Quantum states can be described equivalently by density matrices, Wigner functions or quantum tomograms. We analyze the accuracy and performance of three related semiclassical approaches to quantum dynamics, in particular with respect to…

Quantum Physics · Physics 2009-08-27 G. Schubert , V. S. Filinov , K. Matyash , R. Schneider , H. Fehske

Entropy, and its temporal evolution, play a central role in the foundations of quantum theory and in modern quantum technologies. Here we study, in particular, the relations between the --- in general, non-Markovian --- evolution of an open…

Quantum Physics · Physics 2018-09-18 Paolo Aniello , Joonwoo Bae , Dariusz Chruscinski

We propose a principled method for kernel learning, which relies on a Fourier-analytic characterization of translation-invariant or rotation-invariant kernels. Our method produces a sequence of feature maps, iteratively refining the SVM…

Machine Learning · Computer Science 2018-02-28 Brian Bullins , Cyril Zhang , Yi Zhang
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