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Related papers: Variational quantum process tomography

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At large scales, quantum systems may become advantageous over their classical counterparts at performing certain tasks. Developing tools to analyse these systems at the relevant scales, in a manner consistent with quantum mechanics, is…

Quantum Physics · Physics 2024-11-12 Timon Schapeler , Robert Schade , Michael Lass , Christian Plessl , Tim J. Bartley

The process of translating a quantum algorithm into a form suitable for implementation on a quantum computing platform is crucial but yet challenging. This entails specifying quantum operations with precision, a typically intricate task. In…

Quantum Physics · Physics 2024-08-26 M. Zomorodi , H. Amini , M. Abbaszadeh , J. Sohrabi , V. Salari , P. Plawiak

In quantum information theory, the evolution of an open quantum system -- a unitary evolution followed by a measurement -- is described by a quantum channel or, more generally, a quantum instrument. In this work, we formulate spin and…

High Energy Physics - Phenomenology · Physics 2025-04-24 Clelia Altomonte , Alan J. Barr , Michał Eckstein , Paweł Horodecki , Kazuki Sakurai

Quantum computers promise to enhance machine learning for practical applications. Quantum machine learning for real-world data has to handle extensive amounts of high-dimensional data. However, conventional methods for measuring quantum…

Quantum Physics · Physics 2023-02-10 Tobias Haug , Chris N. Self , M. S. Kim

We review single-qubit quantum process tomography for trace-preserving and nontrace-preserving processes, and derive explicit forms of the general constraints for fitting experimental data. These forms provide additional insight into the…

Quantum Physics · Physics 2015-02-05 Ramesh Bhandari , Nicholas A. Peters

We introduce the concept of quantum field tomography, the efficient and reliable reconstruction of unknown quantum fields based on data of correlation functions. At the basis of the analysis is the concept of continuous matrix product…

Quantum Physics · Physics 2015-06-22 A. Steffens , C. A. Riofrío , R. Hübener , J. Eisert

Quantum machine learning aims to release the prowess of quantum computing to improve machine learning methods. By combining quantum computing methods with classical neural network techniques we aim to foster an increase of performance in…

High Energy Physics - Phenomenology · Physics 2021-03-17 Andrew Blance , Michael Spannowsky

Quantum computing has emerged as a transformative paradigm, capable of tackling complex computational problems that are infeasible for classical methods within a practical timeframe. At the core of this advancement lies the concept of…

Quantum Physics · Physics 2025-02-10 Hyunju Lee , Kyungtaek Jun

Quantum state tomography is an essential tool for the characterization and verification of quantum states. However, as it cannot be directly applied to systems with more than a few qubits, efficient tomography of larger states on mid-sized…

Quantum Physics · Physics 2023-02-01 Yotam Y. Lifshitz , Eyal Bairey , Eli Arbel , Gadi Aleksandrowicz , Haggai Landa , Itai Arad

In this report we present a general approach for estimating quantum circuits by means of measurements. We apply the developed general approach for estimating the quality of superconducting and optical quantum chips. Using the methods of…

Quantum Physics · Physics 2019-06-18 Yu. I. Bogdanov , N. A. Bogdanova , B. I. Bantysh , D. V. Fastovets , V. F. Lukichev

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…

Complex processes often arise from sequences of simpler interactions involving a few particles at a time. These interactions, however, may not be directly accessible to experiments. Here we develop the first efficient method for unravelling…

Quantum Physics · Physics 2022-06-24 Ge Bai , Ya-Dong Wu , Yan Zhu , Masahito Hayashi , Giulio Chiribella

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…

Physical processes in the quantum regime possess non-classical properties of quantum mechanics. However, methods for quantitatively identifying such processes are still lacking. Accordingly, in this study, we develop a framework for…

Quantum Physics · Physics 2020-01-01 Chung-Cheng Kuo , Shih-Hsuan Chen , Wei-Ting Lee , Hung-Ming Chen , He Lu , Che-Ming Li

Modern day quantum simulators can prepare a wide variety of quantum states but the accurate estimation of observables from tomographic measurement data often poses a challenge. We tackle this problem by developing a quantum state tomography…

Quantum Physics · Physics 2022-09-27 Tobias Schmale , Moritz Reh , Martin Gärttner

We present a new method for quantum process tomography. The method enables us to efficiently estimate, with fixed precision, any of the parameters characterizing a quantum channel. It is selective since one can choose to estimate the value…

Quantum Physics · Physics 2008-01-08 Ariel Bendersky , Fernando Pastawski , Juan Pablo Paz

We present an algorithm for projecting superoperators onto the set of completely positive, trace-preserving maps. When combined with gradient descent of a cost function, the procedure results in an algorithm for quantum process tomography:…

Quantum Physics · Physics 2019-01-07 George C. Knee , Eliot Bolduc , Jonathan Leach , Erik M. Gauger

Characterization of quantum objects, being them states, processes, or measurements, complemented by previous knowledge about them is a valuable approach, especially as it leads to routine procedures for real-life components. To this end,…

Quantum Physics · Physics 2023-06-28 Massimiliano Guarneri , Ilaria Gianani , Marco Barbieri , Andrea Chiuri

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 mechanics fundamentally forbids deterministic discrimination of quantum states and processes. However, the ability to optimally distinguish various classes of quantum data is an important primitive in quantum information science. In…

Quantum Physics · Physics 2021-03-10 Hongxiang Chen , Leonard Wossnig , Simone Severini , Hartmut Neven , Masoud Mohseni
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