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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 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

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

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

The present short review article illustrates the latest theoretical developments on quantum tomography, regarding general optimization methods for both data-processing and setup. The basic theoretical tool is the informationally complete…

Quantum state tomography (QST) aims at estimating a quantum state from averaged quantum measurements made on copies of the state. Most quantum algorithms rely on QST at some point and it is a well explored topic in the literature, mostly…

Quantum Physics · Physics 2023-01-18 François Verdeil , Yannick Deville

Many quantum algorithms rely on the measurement of complex quantum amplitudes. Standard approaches to obtain the phase information, such as the Hadamard test, give rise to large overheads due to the need for global controlled-unitary…

Quantum Physics · Physics 2024-05-29 Yilun Yang , Arthur Christianen , Mari Carmen Bañuls , Dominik S. Wild , J. Ignacio Cirac

Quantum computing shows promise for addressing computationally intensive problems but is constrained by the exponential resource requirements of general quantum state tomography (QST), which fully characterizes quantum states through…

Quantum Physics · Physics 2025-09-12 Hao Su , Shiying Xiong , Yue Yang

Quantum state tomography (QST) represents an essential tool for the characterization, verification, and validation (QCVV) of quantum processors. Only for a few idealized scenarios, there are analytic results for the optimal measurement set…

Quantum Physics · Physics 2022-12-27 Violeta N. Ivanova-Rohling , Niklas Rohling , Guido Burkard

In this paper we describe in detail and generalize a method for quantum process tomography that was presented in [A. Bendersky, F. Pastawski, J. P. Paz, Physical Review Letters 100, 190403 (2008)]. The method enables the efficient…

Quantum Physics · Physics 2015-05-13 Ariel Bendersky , Fernando Pastawski , Juan Pablo Paz

Quantum information has been drawing a wealth of research in recent years, shedding light on questions at the heart of quantum mechanics, as well as advancing fields such as complexity theory, cryptography, key distribution, and chemistry.…

Quantum Physics · Physics 2017-04-25 Dikla Oren , Maor Mutzafi , Yonina C. Eldar , Mordechai Segev

Quantum computers have a potential for solving quantum chemistry problems with higher accuracy than classical computers. Quantum computing quantum Monte Carlo (QC-QMC) is a QMC with a trial state prepared in quantum circuit, which is…

Quantum Physics · Physics 2024-06-07 Shu Kanno , Hajime Nakamura , Takao Kobayashi , Shigeki Gocho , Miho Hatanaka , Naoki Yamamoto , Qi Gao

Quantum process tomography is a necessary tool for verifying quantum gates and diagnosing faults in architectures and gate design. We show that the standard approach of process tomography is grossly inaccurate in the case where the states…

Image-based data is a popular arena for testing quantum machine learning algorithms. A crucial factor in realizing quantum advantage for these applications is the ability to efficiently represent images as quantum states. Here we present a…

Quantum Physics · Physics 2023-10-10 Jason Iaconis , Sonika Johri

Measurement in quantum simulations provides a means for extracting meaningful information from a complex quantum state, and for quantum computing reducing the complexity of measurement will be vital for near-term applications. For most…

Quantum Physics · Physics 2021-05-11 Scott E. Smart , David A. Mazziotti

Combining quantum sensing with quantum computing can lead to quantum computational sensors that are able to more efficiently extract task-specific information from physical signals than is possible otherwise. Early examples of quantum…

Quantum Physics · Physics 2025-07-22 Saeed A. Khan , Sridhar Prabhu , Logan G. Wright , Peter L. McMahon

Quantum tomography makes it possible to obtain comprehensive information about certain logical elements of a quantum computer. In this regard, it is a promising tool for debugging quantum computers. The practical application of tomography,…

Quantum Physics · Physics 2020-12-23 B. I. Bantysh , Yu. I. Bogdanov

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

As the connection between classical and quantum worlds, quantum measurements play a unique role in the era of quantum information processing. Given an arbitrary function of quantum measurements, how to obtain its optimal value is often…

Quantum Physics · Physics 2023-02-16 Jing Luo , Jiangwei Shang

The aim of this paper is to develop novel quantum algorithms for Gaussian process quadrature methods. Gaussian process quadratures are numerical integration methods where Gaussian processes are used as functional priors for the integrands…

Computation · Statistics 2025-02-21 Cristian A. Galvis-Florez , Ahmad Farooq , Simo Särkkä
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