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Related papers: Reductive Quantum Phase Estimation

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We discuss the implementation of an iterative quantum phase estimation algorithm, with a single ancillary qubit. We suggest using this algorithm as a benchmark for multi-qubit implementations. Furthermore we describe in detail the smallest…

Quantum Physics · Physics 2010-03-26 M. Dobsicek , G. Johansson , V. S. Shumeiko , G. Wendin

Since the publication of the Quantum Amplitude Estimation (QAE) algorithm by Brassard et al., 2002, several variations have been proposed, such as Aaronson et al., 2019, Grinko et al., 2019, and Suzuki et al., 2020. The main difference…

Quantum Physics · Physics 2020-08-06 Pooja Rao , Kwangmin Yu , Hyunkyung Lim , Dasol Jin , Deokkyu Choi

We present efficient circuits that can be used for the phase space tomography of quantum states. The circuits evaluate individual values or selected averages of the Wigner, Kirkwood and Husimi distributions. These quantum gate arrays can be…

Quantum Physics · Physics 2009-11-10 Juan Pablo Paz , Augusto J. Roncaglia , Marcos Saraceno

We study the simultaneous estimation of multiple phases as a discretised model for the imaging of a phase object. We identify quantum probe states that provide an enhancement compared to the best quantum scheme for the estimation of each…

Quantum Physics · Physics 2013-09-10 Peter C. Humphreys , Marco Barbieri , Animesh Datta , Ian A. Walmsley

The general-purpose interactive theorem-proving assistant called Prove-It was used to verify the Quantum Phase Estimation (QPE) algorithm, specifically claims about its outcome probabilities. Prove-It is unique in its ability to express…

Quantum Physics · Physics 2024-03-26 Wayne M. Witzel , Warren D. Craft , Robert Carr , Deepak Kapur

Quantum phase estimation is one of the most important tools in quantum algorithms. It can be made non-adaptive (meaning all applications of the unitary $U_\phi$ happen simultaneously) without using more applications of $U_\phi$, albeit at…

Quantum Physics · Physics 2025-11-10 Noah Linden , Ronald de Wolf

Quantum Amplitude Estimation (QAE) is a key primitive in quantum computing, but its standard implementation using Quantum Phase Estimation is resource-intensive, requiring a large number of coherent qubits in a single circuit block to…

Quantum Physics · Physics 2025-08-11 Alok Shukla , Prakash Vedula

Quantum detector tomography is a fundamental technique for calibrating quantum devices and performing quantum engineering tasks. In this paper, a novel quantum detector tomography method is proposed. First, a series of different probe…

The number of measurements demanded by hybrid quantum-classical algorithms such as the variational quantum eigensolver (VQE) is prohibitively high for many problems of practical value. For such problems, realizing quantum advantage will…

Quantum Physics · Physics 2021-03-24 Guoming Wang , Dax Enshan Koh , Peter D. Johnson , Yudong Cao

In this thesis, attention is paid to small experimental testbed applications with respect to the quantum phase estimation algorithm, the core approach for finding energy eigenvalues. An iterative scheme for quantum phase estimation (IPEA)…

Quantum Physics · Physics 2008-03-07 Miroslav Dobšíček

We introduce the Real Quantum Amplitude Estimation (RQAE) algorithm, an extension of Quantum Amplitude Estimation (QAE) which is sensitive to the sign of the amplitude. RQAE is an iterative algorithm which offers explicit control over the…

Quantum Physics · Physics 2022-05-26 Alberto Manzano , Daniele Musso , Álvaro Leitao

We propose a quantum algorithm based on ridge regression model, which get the optimal fitting parameters w and a regularization hyperparameter {\alpha} by analysing the training dataset. The algorithm consists of two subalgorithms. One is…

Quantum Physics · Physics 2021-04-28 Menghan Chen , Chaohua Yu , Gongde Guo , Song Lin

Quantum phase estimation is a central primitive in quantum algorithms and sensing, where performance is governed by the sensitivity of measurement signals to the target parameter. While existing methods have developed increasingly…

Quantum Physics · Physics 2026-04-02 Zikang Jia , Suying Liu , Yulong Dong

Under suitable assumptions, the quantum phase estimation (QPE) algorithm is able to achieve Heisenberg-limited precision scaling in estimating the ground state energy. However, QPE requires a large number of ancilla qubits and large circuit…

Quantum Physics · Physics 2022-02-04 Lin Lin , Yu Tong

There is no unique way to encode a quantum algorithm into a quantum circuit. With limited qubit counts, connectivities, and coherence times, circuit optimization is essential to make the best use of near-term quantum devices. We introduce…

Quantum effects like entanglement and coherent amplification can be used to drastically enhance the accuracy of quantum parameter estimation beyond classical limits. However, challenges such as decoherence and time-dependent errors hinder…

Quantum Physics · Physics 2025-02-18 Yulong Dong , Jonathan A. Gross , Murphy Yuezhen Niu

Phase estimation is used in many quantum algorithms, particularly in order to estimate energy eigenvalues for quantum systems. When using a single qubit as the probe (used to control the unitary we wish to estimate the eigenvalue of), it is…

Quantum Physics · Physics 2023-03-23 Peyman Najafi , Pedro C. S. Costa , Dominic W. Berry

Quantum computers are special purpose machines that are expected to be particularly useful in simulating strongly correlated chemical systems. The quantum computer excels at treating a moderate number of orbitals within an active space in a…

In the noisy intermediate-scale quantum (NISQ) era, quantum error mitigation (QEM) is essential for producing reliable outputs from quantum circuits. We present a statistical signal processing approach to QEM that estimates the most likely…

Efficient simulation of quantum computers is essential for the development and validation of near-term quantum devices and the research on quantum algorithms. Up to date, two main approaches to simulation were in use, based on either full…

Computational Complexity · Computer Science 2020-05-06 Roman Schutski , Danil Lykov , Ivan Oseledets
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