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We derive an asymptotic lower bound on the Bayes risk when N identical quantum systems whose state depends on a vector of unknown parameters are jointly measured in an arbitrary way and the parameters of interest estimated on the basis of…

Statistics Theory · Mathematics 2023-05-02 Richard D. Gill

Quantum phase estimation is a fundamental subroutine in many quantum algorithms, including Shor's factorization algorithm and quantum simulation. However, so far results have cast doubt on its practicability for near-term, non-fault…

In a seminal paper [8] it was shown that Heisenberg-limited measurements could be achieved without using entangled states by coupling the quantum resources to a common environment that could be measured, at least, in part. The authors also…

Quantum Physics · Physics 2025-09-25 D. Ballester , Yu. V. Arkhipov , I. M. Tkachenko

The estimation of multiple parameters in quantum metrology is important for a vast array of applications in quantum information processing. However, the unattainability of fundamental precision bounds for incompatible observables has…

Quantum Physics · Physics 2021-02-17 Jasminder S. Sidhu , Yingkai Ouyang , Earl T. Campbell , Pieter Kok

In quantum metrology, the Holevo Cram\'er-Rao bound has attracted renewed interest in recent years due to its superiority over the Helstrom Cram\'er-Rao bound and its asymptotic attainability for multi-parameter estimation. Its evaluation,…

Quantum Physics · Physics 2021-11-01 Mankei Tsang

We summarise important recent advances in quantum metrology, in connection to experiments in cold gases, trapped cold atoms and photons. First we review simple metrological setups, such as quantum metrology with spin squeezed states, with…

Quantum Physics · Physics 2015-01-27 Geza Toth , Iagoba Apellaniz

Quantum estimation theory provides optimal observations for various estimation problems for unknown parameters in the state of the system under investigation. However, the theory has been developed under the assumption that every observable…

Quantum Physics · Physics 2009-11-10 M. Hotta , M. Ozawa

We address the question whether the super-Heisenberg scaling for quantum estimation is realizable. We unify the results of two approaches. In the first one, the original system is compared with its copy rotated by the parameter dependent…

Quantum Physics · Physics 2018-04-25 Marek M. Rams , Piotr Sierant , Omjyoti Dutta , Paweł Horodecki , Jakub Zakrzewski

The Heisenberg time-energy relation prevents determination of an atomic transition to better than the inverse of the measurement time. The relation generally applies to frequency estimation of a near-resonant field [1-3], since information…

Quantum Physics · Physics 2021-06-08 Liam P. McGuinness

We propose a protocol to overcome the shot noise limit and reach the Heisenberg scaling limit for parameter estimation by using quantum optimal control and a time-reversal strategy. Exemplified through the phase estimation, which can play…

Quantum Physics · Physics 2023-12-25 Da-Wei Luo , Ting Yu

Gradient-based optimization is a key ingredient of variational quantum algorithms, with applications ranging from quantum machine learning to quantum chemistry and simulation. The parameter-shift rule provides a hardware-friendly method for…

Quantum Physics · Physics 2025-10-08 Leonardo Banchi , Dominic Branford , Chetan Waghela

A number of authors have suggested that nonlinear interactions can enhance resolution of phase shifts beyond the usual Heisenberg scaling of 1/n, where n is a measure of resources such as the number of subsystems of the probe state or the…

Quantum Physics · Physics 2012-11-05 Michael J. W. Hall , Howard M. Wiseman

Estimating the overlap between an approximate wavefunction and a target eigenstate of the system Hamiltonian is essential for the efficiency of quantum phase estimation. In this work, we derive upper and lower bounds on this overlap using…

Quantum Physics · Physics 2025-03-18 Junan Lin , Artur F. Izmaylov

We find a large class of pure and mixed input states with which the phase estimation precision saturates the Cramer-Rao bound under the compound measurements of parity and particle number. We further propose a quantum-phase-estimation…

Quantum Physics · Physics 2019-04-23 Haijun Xing , Libin Fu , Su Yi

Purpose: To develop neural network (NN)-based quantitative MRI parameter estimators with minimal bias and a variance close to the Cram\'er-Rao bound. Theory and Methods: We generalize the mean squared error loss to control the bias and…

Medical Physics · Physics 2024-05-07 Andrew Mao , Sebastian Flassbeck , Jakob Assländer

Multiparameter quantum estimation theory aims to determine simultaneously the ultimate precision of all parameters contained in the state of a given quantum system. Determining this ultimate precision depends on the quantum Fisher…

Quantum Physics · Physics 2020-09-15 Lahcen Bakmou , Mohammed Daoud , Rachid ahl laamara

We provide evidence that the uncertainty in detection of small and deterministic phase-shift deviations from a working point can be lower than the Heisenberg bound, for fixed finite mean number of photons. We achieve that by exploiting…

Quantum Physics · Physics 2012-09-28 Ángel Rivas , Alfredo Luis

Uncertainty relations in quantum mechanics express bounds on our ability to simultaneously obtain knowledge about expectation values of non-commuting observables of a quantum system. They quantify trade-offs in accuracy between…

Quantum Physics · Physics 2020-03-16 Ilya Kull , Philippe Allard Guérin , Frank Verstraete

Achieving the ultimate precisions for multiple parameters simultaneously is an outstanding challenge in quantum physics, because the optimal measurements for incompatible parameters cannot be performed jointly due to the Heisenberg…

Quantum Physics · Physics 2023-10-12 Binke Xia , Jingzheng Huang , Hongjing Li , Han Wang , Guihua Zeng

The Cram\'er-Rao bound (CRB), a well-known lower bound on the performance of any unbiased parameter estimator, has been used to study a wide variety of problems. However, to obtain the CRB, requires an analytical expression for the…

Machine Learning · Computer Science 2022-10-11 Hai Victor Habi , Hagit Messer , Yoram Bresler