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Related papers: Quantum State Smoothing for Linear Gaussian System…

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In this paper, we study the problem of estimating the state of a dynamic state-space system where the output is subject to quantization. We compare some classical approaches and a new development in the literature to obtain the filtering…

Systems and Control · Electrical Eng. & Systems 2021-12-16 Angel L. Cedeño , Ricardo Albornoz , Boris I. Godoy , Rodrigo Carvajal , Juan C. Agüero

Standard quantum state tomography assumes sufficient control of a system to measure an informationally complete set of observables. Dynamical quantum state tomography (DQST) presents an alternative: given a system with known dynamics and a…

Quantum Physics · Physics 2026-02-23 Hjalmar Rall

Smoothing algorithms for state-space models, i.e., fixed-interval smoothing, fixed-lag smoothing, and two-filter formula for smoothing, are examined using real examples. For linear and Gaussian state-space models, it is observed that…

Computation · Statistics 2023-07-10 G. Kitagawa

Robust, accurate and efficient quantum tomography is key for future quantum technologies. Traditional methods are impractical for even medium sized systems and are not robust against noise and errors. Here we report on an experimental…

Quantum Physics · Physics 2016-07-27 Robert J. Chapman , Christopher Ferrie , Alberto Peruzzo

Quantum optical Gaussian states are a type of important robust quantum states which are manipulatable by the existing technologies. So far, most of the important quantum information experiments are done with such states, including bright…

Quantum Physics · Physics 2009-11-13 X. -B. Wang , T. Hiroshima , A. Tomita , M. Hayashi

Quantum state tomography (QST) is an essential technique for characterizing quantum states. However, practical implementations of QST are significantly challenged by factors such as shot noise, attenuation, and Raman scattering, especially…

Quantum Physics · Physics 2024-11-26 Artur Czerwinski

Here, we are concerned with comparing estimation schemes for the quantum state under continuous measurement (quantum trajectories), namely quantum state filtering and, as introduced by us [Phys. Rev. Lett. 115, 180407 (2015)], quantum state…

Quantum Physics · Physics 2020-11-18 Ivonne Guevara , Howard M. Wiseman

Quantum state tomography, the ability to deduce the density matrix of a quantum system from measured data, is of fundamental importance for the verification of present and future quantum devices. It has been realized in systems with few…

Quantum Physics · Physics 2010-02-22 M. Cramer , M. B. Plenio

Quantum State Tomography (QST) is a fundamental technique in Quantum Information Processing (QIP) for reconstructing unknown quantum states. However, the conventional QST methods are limited by the number of measurements required, which…

Quantum state purification, which operates not by identifying and correcting specific errors but by repeatedly projecting multiple noisy copies onto special subspaces, provides a syndrome-free alternative to quantum error correction.…

Quantum Physics · Physics 2026-04-17 Xing-Chen Guo , Benchi Zhao , Xin Wang

Quantum state tomography--the practice of estimating a quantum state by performing measurements on it--is useful in a variety of contexts. We introduce "gentle tomography" as a version of tomography that preserves the measured quantum data.…

Quantum Physics · Physics 2007-05-23 Charles H. Bennett , Aram W. Harrow , Seth Lloyd

Understanding quantum systems is of significant importance for assessing the performance of quantum hardware and software, as well as exploring quantum control and quantum sensing. An efficient representation of quantum states enables…

Quantum Physics · Physics 2024-10-10 Yuchen Guo , Shuo Yang

Continuous-variable quantum systems are foundational to quantum computation, communication, and sensing. While traditional representations using wave functions or density matrices are often impractical, the tomographic picture of quantum…

Quantum Physics · Physics 2026-03-17 Liubov A. Markovich , Xiaoyu Liu , Jordi Tura

Quantum state tomography, aimed at deriving a classical description of an unknown state from measurement data, is a fundamental task in quantum physics. In this work, we analyse the ultimate achievable performance of tomography of…

We study the problem of quantum-state tomography under the assumption that the state of the system is close to pure. In this context, an efficient measurements that one typically formulates uniquely identify a pure state from within the set…

Quantum Physics · Physics 2016-05-11 Amir Kalev , Charles H. Baldwin , Ivan H. Deutsch

Quantum state tomography (QST) is the process of reconstructing the state of a quantum system (mathematically described as a density matrix) through a series of different measurements, which can be solved by learning a parameterized…

Quantum Physics · Physics 2025-03-31 Hailan Ma , Zhenhong Sun , Daoyi Dong , Chunlin Chen , Herschel Rabitz

Quantum state purification is the functionality that, given multiple copies of an unknown state, outputs a state with increased purity. This will be an essential building block for near- and middle-term quantum ecosystems before the…

Quantum Physics · Physics 2024-06-14 Bo Yang , Elham Kashefi , Dominik Leichtle , Harold Ollivier

Quantum tomography is a fundamental technique for characterizing, benchmarking, and verifying quantum states and devices. It plays a crucial role in advancing quantum technologies and deepening our understanding of quantum mechanics.…

Quantum state tomography is the experimental procedure of determining an unknown state. It is not only essential for the verification of resources and processors of quantum information but is also important in its own right with regard to…

Quantum Physics · Physics 2022-07-20 Mahn-Soo Choi

Quantum state tomography (QST) aims at reconstructing the state of a quantum system. However in conventional QST the number of measurements scales exponentially with the number of qubits. Here we propose a QST protocol, in which the…

Quantum Physics · Physics 2024-08-23 Daniele Binosi , Giovanni Garberoglio , Diego Maragnano , Maurizio Dapor , Marco Liscidini