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We study quantum process tomography given the prior information that the map is a unitary or close to a unitary process. We show that a unitary map on a $d$-level system is completely characterized by a minimal set of $d^2{+}d$ elements…

Quantum Physics · Physics 2014-07-23 Charles H. Baldwin , Amir Kalev , Ivan H. Deutsch

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

Compressive sensing (CS) combines data acquisition with compression coding to reduce the number of measurements required to reconstruct a sparse signal. In optics, this usually takes the form of projecting the field onto sequences of random…

Information Theory · Computer Science 2018-10-24 Davood Mardani , H. Esat Kondakci , Lane Martin , Ayman F. Abouraddy , George K. Atia

We present a novel method to perform quantum state tomography for many-particle systems which are particularly suitable for estimating states in lattice systems such as of ultra-cold atoms in optical lattices. We show that the need for…

Quantum Physics · Physics 2015-06-04 M. Ohliger , V. Nesme , J. Eisert

The estimation of all the parameters in an unknown quantum state or measurement device, commonly known as quantum state tomography (QST) and quantum detector tomography (QDT), is crucial for comprehensively characterizing and controlling…

Quantum Physics · Physics 2025-02-18 Shuixin Xiao , Weichao Liang , Yuanlong Wang , Daoyi Dong , Ian R. Petersen , Valery Ugrinovskii

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…

We present a protocol that allows the estimation of any density matrix element for continuous-variable quantum states, without resorting to the complete reconstruction of the full density matrix. The algorithm adaptatively discretizes the…

Quantum Physics · Physics 2024-09-25 Virginia Feldman , Ariel Bendersky

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--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

We introduce the concept of selective quantum state tomography or SQST, a tomographic scheme that enables a user to estimate arbitrary elements of an unknown quantum state using a fixed measurement record. We demonstrate how this may be…

Quantum Physics · Physics 2020-06-12 Joshua Morris , Borivoje Dakić

Compressive Sensing (CS) is a new technique for the efficient acquisition of signals, images, and other data that have a sparse representation in some basis, frame, or dictionary. By sparse we mean that the N-dimensional basis…

Information Theory · Computer Science 2015-05-18 Chinmay Hegde , Richard G. Baraniuk

Electron tomography has achieved higher resolution and quality at reduced doses with recent advances in compressed sensing. Compressed sensing (CS) theory exploits the inherent sparse signal structure to efficiently reconstruct…

Computational Physics · Physics 2020-12-02 Jonathan Schwartz , Huihuo Zheng , Marcus Hanwell , Yi Jiang , Robert Hovden

Accurately characterizing multipartite entangled states is a critical challenge in quantum information processing. In this work, we focus on applying compressed sensing techniques to efficiently estimate the fidelity of…

Quantum Physics · Physics 2026-05-01 Farrokh Labib , David Nicholaeff , Vincent Russo , William J. Zeng

Coherent-state quantum process tomography (csQPT) is a method of completely characterizing a quantum-optical "black box" by probing it with coherent states and performing homodyne measurements on the output [M. Lobino et al, Science 322,…

Quantum Physics · Physics 2013-03-15 Aamir Anis , A. I. Lvovsky

The impressive pace of advance of quantum technology calls for robust and scalable techniques for the characterization and validation of quantum hardware. Quantum process tomography, the reconstruction of an unknown quantum channel from…

High-dimensional quantum information processing has become a mature field of research with several different approaches being adopted for the encoding of $D$-dimensional quantum systems. Such progress has fueled the search of reliable…

Quantum Physics · Physics 2019-01-30 D. Martínez , M. A. Solís-Prosser , G. Cañas , O. Jiménez , A. Delgado , G. Lima

The possible state space dimension increases exponentially with respect to the number of qubits. This feature makes the quantum state tomography expensive and impractical for identifying the state of merely several qubits. The recent…

Information Theory · Computer Science 2014-01-28 Kezhi Li , Shuang Cong

Quantum state tomography is the task of inferring the state of a quantum system by appropriate measurements. Since the frequency distributions of the outcomes of any finite number of measurements will generally deviate from their asymptotic…

Quantum Physics · Physics 2012-11-08 Matthias Christandl , Renato Renner

To improve the efficiency of the state tomography strategy via weak value, we have searched the optimal coupling strength between the system and measuring device. For an arbitrary d-dimensional quantum system, the optimal strengths being…

Quantum Physics · Physics 2024-02-23 Xuanmin Zhu , Dezheng Zhang , Runping Gao , Qun wei , Lixia Liu , Zijiang Luo

A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribution, and achieving accurate reconstruction on average, is…

Computer Vision and Pattern Recognition · Computer Science 2015-05-27 Guoshen Yu , Guillermo Sapiro