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We propose and evaluate experimentally an approach to quantum process tomography that completely removes the scaling problem plaguing the standard approach. The key to this simplification is the incorporation of prior knowledge of the class…

Quantum Physics · Physics 2015-05-14 M. P. A. Branderhorst , J. Nunn , I. A. Walmsley , R. L. Kosut

Estimating thermal expectation values of observables is a fundamental task in quantum physics, quantum chemistry, and materials science. While recent quantum algorithms have enabled efficient quantum preparation of thermal states,…

Quantum Physics · Physics 2026-02-16 Jiaqing Jiang , Jiaqi Leng , Lin Lin

We explore the main processes involved in the evolution of general quantum systems by means of Diagrams of States, a novel method to graphically represent and analyze how quantum information is elaborated during computations performed by…

Quantum Physics · Physics 2009-12-02 Sara Felloni , Alberto Leporati , Giuliano Strini

This paper investigates a new formalism to describe real time evolution of quantum systems at finite temperature. A time correlation function among subsystems will be derived which allows for a probabilistic interpretation. Our derivation…

High Energy Physics - Theory · Physics 2009-10-31 E. Mendel , M. Nest

We develop a rigorous system-agnostic method to predict quantum thermalization in an overwhelming fraction of accessible pure states in a many-body system, entirely in terms of certain out-of-time-ordered correlators of few-body…

Quantum Physics · Physics 2026-04-06 Amit Vikram

Quantifying and verifying the control level in preparing a quantum state are central challenges in building quantum devices. The quantum state is characterized from experimental measurements, using a procedure known as tomography, which…

Quantum Physics · Physics 2021-12-28 Quoc Hoan Tran , Kohei Nakajima

When the dynamics of a quantum system of interest is known, an informationally-complete set of observables is not needed for state reconstruction via tomographic techniques: letting the system evolve before performing the measurement allows…

Quantum Physics · Physics 2026-02-17 Marco Peruzzo , Tommaso Grigoletto , Francesco Ticozzi

The experimental realisation of large scale many-body systems has seen immense progress in recent years, rendering full tomography tools for state identification inefficient, especially for continuous systems. In order to work with these…

The characterization of a quantum device is a crucial step in the development of quantum experiments. This is accomplished via Quantum Process Tomography, which combines the outcomes of different projective measurements to deliver a…

Quantum Physics · Physics 2025-06-26 Francesco Di Colandrea , Nazanin Dehghan , Alessio D'Errico , Ebrahim Karimi

We present a novel, non-parametric form for compactly representing entangled many-body quantum states, which we call a `Gaussian Process State'. In contrast to other approaches, we define this state explicitly in terms of a configurational…

Strongly Correlated Electrons · Physics 2020-11-11 Aldo Glielmo , Yannic Rath , Gabor Csanyi , Alessandro De Vita , George H. Booth

Two identical finite quantum systems prepared initially at different temperatures, isolated from the environment, and subsequently brought into contact are demonstrated to relax towards Gibbs-like quasi-equilibrium states with a common…

Statistical Mechanics · Physics 2011-01-10 Alexey V. Ponomarev , Sergey Denisov , Peter Hänggi

An arbitrary quantum-optical process (channel) can be completely characterized by probing it with coherent states using the recently developed coherent-state quantum process tomography (QPT) [Lobino et al., Science 322, 563 (2008)]. In…

Quantum Physics · Physics 2013-08-09 Xiang-Bin Wang , Zong-Wen Yu , Jia-Zhong Hu , Adam Miranowicz , Franco Nori

Progress in automatic control of thermal processes and real-time estimation of heat penetration into live tissue has long been limited by the difficulty of obtaining high-fidelity thermodynamic models. Traditionally, in complex…

Computer Vision and Pattern Recognition · Computer Science 2022-07-20 Hamza El-Kebir , Yongseok Lee , Joseph Bentsman

Problems in the field of open quantum systems often involve an environment that strongly influences the dynamics of excited states. Here we present a numerical method to model optical spectra of non-Markovian open quantum systems. The…

Quantum Physics · Physics 2025-05-01 Roosmarijn de Wit , Jonathan Keeling , Brendon W. Lovett , Alex W. Chin

Concerning state estimation, we will compare two cases. In one case we cannot use the quantum correlations between samples. In the other case, we can use them. In addition, under the later case, we will propose a method which simultaneously…

Quantum Physics · Physics 2007-05-23 Masahito Hayashi

Using coherent states in optical quantum process tomography is a practically-relevant approach. Here, we develop a framework for complete characterization of quantum-optical processes in terms of normally-ordered moments by using coherent…

Quantum Physics · Physics 2017-04-11 M. Ghalaii , A. T. Rezakhani

Adaptive measurements were recently shown to significantly improve the performance of quantum state tomography. Utilizing information about the system for the on-line choice of optimal measurements allows to reach the ultimate bounds of…

Quantum process tomography conventionally uses a multitude of initial quantum states and then performs state tomography on the process output. Here we propose and study an alternative approach which requires only a single (or few) known…

Quantum Physics · Physics 2023-11-09 Irene López Gutiérrez , Felix Dietrich , Christian B. Mendl

Quantum process tomography is a procedure by which the unknown dynamical evolution of an open quantum system can be fully experimentally characterized. We demonstrate explicitly how this procedure can be implemented with a nuclear magnetic…

Quantum Physics · Physics 2007-05-23 Andrew M. Childs , Isaac L. Chuang , Debbie W. Leung

Spatiotemporal dynamics models are fundamental for various domains, from heat propagation in materials to oceanic and atmospheric flows. However, currently available neural network-based spatiotemporal modeling approaches fall short when…

Machine Learning · Computer Science 2025-02-11 Valerii Iakovlev , Harri Lähdesmäki
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