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We propose a high efficiency tomographic scheme to reconstruct an unknown quantum state of the qubits by using a series of quantum nondemolition (QND) measurements. The proposed QND measurements of the qubits are implemented by probing the…

Quantum Physics · Physics 2015-05-20 J. S. Huang , L. F. Wei , C. H. Oh

We propose an efficient protocol to fully reconstruct a set of high-fidelity quantum gates. Usually, the efficiency of reconstructing high-fidelity quantum gates is limited by the sampling noise. Our protocol is based on a perturbative…

Quantum Physics · Physics 2021-03-24 Ruyu Yang , Ying Li

As the method to completely characterize quantum dynamical processes, quantum process tomography (QPT) is vitally important for quantum information processing and quantum control, where the faithfulness of quantum devices plays an essential…

Quantum Physics · Physics 2013-09-24 Yu-Xiang Zhang , Shengjun Wu , Zeng-Bing Chen

We present a compressive quantum process tomography scheme that fully characterizes any rank-deficient completely-positive process with no a priori information about the process apart from the dimension of the system on which the process…

We investigate the evolution of open quantum systems in the presence of initial correlations with an environment. Here the standard formalism of describing evolution by completely positive trace preserving (CPTP) quantum operations can fail…

Quantum Physics · Physics 2016-09-08 Christopher J. Wood

Reconstructing quantum states is an important task for various emerging quantum technologies. The process of reconstructing the density matrix of a quantum state is known as quantum state tomography. Conventionally, tomography of arbitrary…

Quantum Physics · Physics 2020-08-17 Sanjib Ghosh , Andrzej Opala , Michał Matuszewski , Tomasz Paterek , Timothy C. H. Liew

Quantum process tomography is a powerful tool for understanding quantum channels and characterizing properties of quantum devices. Inspired by recent advances using classical shadows in quantum state tomography [H.-Y. Huang, R. Kueng, and…

Quantum Physics · Physics 2024-02-12 Ryan Levy , Di Luo , Bryan K. Clark

Quantum computing crucially relies on the ability to efficiently characterize the quantum states output by quantum hardware. Conventional methods which probe these states through direct measurements and classically computed correlations…

We apply the method of compressed sensing (CS) quantum process tomography (QPT) to characterize quantum gates based on superconducting Xmon and phase qubits. Using experimental data for a two-qubit controlled-Z gate, we obtain an estimate…

Current and imminent quantum hardware lacks reliability and applicability due to noise and limited qubit counts. Quantum circuit cutting -- a technique dividing large quantum circuits into smaller subcircuits with sizes appropriate for the…

Quantum Physics · Physics 2022-12-05 Daniel Chen , Betis Baheri , Vipin Chaudhary , Qiang Guan , Ning Xie , Shuai Xu

We introduce two methods for quantum process and detector tomography. In the quantum process tomography method, we develop an analytical procedure for projecting the linear inversion estimation of a quantum channel onto the set of…

Quantum Physics · Physics 2025-01-10 Júlia Barberà-Rodríguez , Leonardo Zambrano , Antonio Acín , Donato Farina

We propose a practical strategy for choosing sets of input coherent states that are near-optimal for reconstructing single-mode Gaussian quantum processes with output-state heterodyne measurements. We first derive analytical expressions for…

Quantum Physics · Physics 2020-12-29 Yong Siah Teo , Kimin Park , Seongwook Shin , Hyunseok Jeong , Petr Marek

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

Quantum process tomography (QPT), used to estimate the linear map that best describes a quantum operation, is usually performed using a priori assumptions about state preparation and measurement (SPAM), which yield a biased and inconsistent…

Quantum Physics · Physics 2025-03-14 Robin Blume-Kohout , Kenneth Rudinger , Timothy Proctor

Quantum state tomography (QST) for reconstructing pure states requires exponentially increasing resources and measurements with the number of qubits by using state-of-the-art quantum compressive sensing (CS) methods. In this article, QST…

Quantum Physics · Physics 2021-11-16 Burhan Gulbahar

Well-controlled quantum devices with their increasing system size face a new roadblock hindering further development of quantum technologies: The effort of quantum tomography---the characterization of processes and states within a quantum…

Quantum Physics · Physics 2017-05-26 C. A. Riofrio , D. Gross , S. T. Flammia , T. Monz , D. Nigg , R. Blatt , J. Eisert

Compressive sensing is a sensing protocol that facilitates reconstruction of large signals from relatively few measurements by exploiting known structures of signals of interest, typically manifested as signal sparsity. Compressive…

Quantum Physics · Physics 2022-08-10 Kyle Sherbert , Naveed Naimipour , Haleh Safavi , Harry Shaw , Mojtaba Soltanalian

We propose a method for precision statistical control of quantum processes based on superconductor phase qubits. Using the universal quantum tomography method, we provide a detailed analysis of accuracy of tomography for a 2-qubit gate…

Quantum Physics · Physics 2017-07-26 Yu. I. Bogdanov , S. A. Nuyanzin

Quantum computing can provide speedups in solving many problems as the evolution of a quantum system is described by a unitary operator in an exponentially large Hilbert space. Such unitary operators change the phase of their eigenstates…

Quantum Physics · Physics 2024-01-23 Youle Wang , Lei Zhang , Zhan Yu , Xin Wang

We revisit quantum tomography in an informationally incomplete scenario and propose improved state reconstruction methods using deep neural networks. In the first approach, the trained network predicts an optimal linear or quadratic…

Quantum Physics · Physics 2026-01-21 Mateusz Krawczyk , Pavel Baláž , Katarzyna Roszak , Jarosław Pawłowski