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The Fisher information $F$ gives a limit to the ultimate precision achievable in a phase estimation protocol. It has been shown recently that the Fisher information for a linear two-mode interferometer cannot exceed the number of particles…

In recent times, distributed sensing has been extensively studied using squeezed states. While this is an excellent development, it is desirable to investigate the use of other quantum probes, such as entangled states of light. In this…

Quantum Physics · Physics 2025-01-14 Jiaxuan Wang , Girish Agarwal

Quantum state estimation is an important task of many quantum information protocols. We consider two families of unitary evolution operators, one with a one-parameter and the other with a two-parameter, which enable the estimation of a…

Quantum Physics · Physics 2023-01-27 Cristian A. Galvis Florez , J. Martínez-Cifuentes , K. M. Fonseca-Romero

We propose a quantum metrology protocol based on a two-step joint evolution of the probe system and an ancillary qubit and quantum measurement. With a proper initial state of the ancillary qubit and an optimized evolution time, the quantum…

Quantum Physics · Physics 2025-01-06 Peng Chen , Jun Jing

We derive ultimate precision bounds for estimating parameters encoded in \emph{time-dependent} Hamiltonians in the presence of general Markovian noise, allowing for arbitrary adaptive protocols with fast controls and noiseless ancillas.…

Quantum Physics · Physics 2026-05-19 Luca Previdi , Francesco Albarelli

We introduce a canonical decomposition of the quantum Fisher information (QFI) for centered multimode Gaussian states into two additive pieces: an even part that captures changes in the symplectic spectrum and an odd part associated with…

We provide a new expression of the quantum Fisher information(QFI) for a general system. Utilizing this expression, the QFI for a non-full rank density matrix is only determined by its support. This expression can bring convenience for a…

Quantum Physics · Physics 2014-01-31 Jing Liu , Xiao-Xing Jing , Wei Zhong , Xiaoguang Wang

In recent years, significant progress has been made in utilizing the divergence of spectrum response rate at the exceptional point (EP) for sensing in classical systems, while the use and characterization of quantum EPs for sensing have…

Quantum Physics · Physics 2024-04-08 Chun-Hui Liu , Fu Li , Shengwang Du , Jianming Wen , Lan Yang , Chuanwei Zhang

Quantum metrology is a rapidly developing branch of quantum technologies. While various theories have been established on quantum metrology for Markovian processes, i.e., quantum channel estimation, quantum metrology for non-Markovian…

Quantum Physics · Physics 2021-08-04 Anian Altherr , Yuxiang Yang

We develop a quantum metrological framework for resonant nanophotonic sensors based on subwavelength Fabry--Perot slit cavities. Building on classical Fisher-information analyses of resonant transmission sensors, we model parameter encoding…

Quantum Physics · Physics 2025-12-18 J. Sumaya-Martinez

We introduce a technique to estimate error-mitigated expectation values on noisy quantum computers. Our technique performs shadow tomography on a logical state to produce a memory-efficient classical reconstruction of the noisy density…

Quantum Physics · Physics 2022-03-15 Hong-Ye Hu , Ryan LaRose , Yi-Zhuang You , Eleanor Rieffel , Zhihui Wang

Critical properties of a quantum system are recognized as valuable resources for quantum metrology. In this work, we investigate the criticality-enhanced sensing in a quantum Rabi triangle system, which exhibits multiple phases. Around the…

Quantum Physics · Physics 2025-11-04 Yuyang Tang , Yu Yang , Min An , Fuli Li

The Quantum Fisher Information Matrix (QFIM) is a fundamental quantity in various subfields of quantum physics. It plays a crucial role in the study of parameterized quantum states, as it quantifies their sensitivity to variations in its…

Quantum Physics · Physics 2025-05-16 Rafael Gómez-Lurbe

Quantum Fisher information places the fundamental limit to the accuracy of estimating an unknown parameter. Here we shall provide the quantum Fisher information an operational meaning: a mixed state can be so prepared that a given…

Quantum Physics · Physics 2013-02-22 Sixia Yu

Shadow estimation is a recent protocol that allows estimating exponentially many expectation values of a quantum state from ``classical shadows'', obtained by applying random quantum circuits and computational basis measurements. In this…

Quantum Physics · Physics 2023-12-27 Jonas Helsen , Michael Walter

Constrained least squares problems arise in a variety of applications, and many iterative methods are already available to compute their solutions. This paper proposes a new efficient approach to solve nonnegative linear least squares…

Numerical Analysis · Mathematics 2017-01-09 Silvia Gazzola , Yves Wiaux

In this contribution, quantum Fisher information is utilized to estimate the parameters of a central qubit interacting with a single-spin qubit. The effect of the longitudinal, transverse and the rotating strengths of the magnetic field on…

Quantum Physics · Physics 2018-04-04 N. Metwally

We present shadow spectroscopy as a simulator-agnostic quantum algorithm for estimating energy gaps using very few circuit repetitions (shots) and no extra resources (ancilla qubits) beyond performing time evolution and measurements. The…

Quantum Physics · Physics 2025-04-10 Hans Hon Sang Chan , Richard Meister , Matthew L. Goh , Bálint Koczor

In quantum multi-parameter estimation, the precision of estimating unknown parameters is bounded by the Cramer-Rao bound (CRB), defined via the inverse of the Fisher information matrix (FIM). However, in certain scenarios such as…

Quantum Physics · Physics 2025-11-18 Min Namkung , Changhyoup Lee , Hyang-Tag Lim

Symmetric logarithmic derivative (SLD) is a key quantity to obtain quantum Fisher information (QFI) and to construct the corresponding optimal measurements. Here we develop a method to calculate the SLD and QFI via anti-commutators. This…

Quantum Physics · Physics 2016-05-25 Jing Liu , Jie Chen , Xiao-Xing Jing , Xiaoguang Wang