English
Related papers

Related papers: Fisher Information in Noisy Intermediate-Scale Qua…

200 papers

Giving a convincing experimental evidence of the quantum supremacy over classical simulations is a challenging goal. Noise is considered to be the main problem in such a demonstration, hence it is urgent to understand the effect of noise.…

Quantum Physics · Physics 2022-03-08 Valery Shchesnovich

The importance of Fisher information is increasing in nonequilibrium thermodynamics, as it has played a fundamental role in trade-off relations such as thermodynamic uncertainty relations and speed limits. In this work, we investigate…

Quantum Physics · Physics 2026-03-05 Tomohiro Nishiyama , Yoshihiko Hasegawa

By utilizing quantum mechanical effects, such as superposition and entanglement, quantum metrology promises higher precision than the classical strategies. It is, however, practically challenging to realize the quantum advantages. This is…

Quantum Physics · Physics 2025-03-13 Ran Liu , Ze Wu , Xiaodong Yang , Yuchen Li , Hui Zhou , Zhaokai Li , Yuquan Chen , Haidong Yuan , Xinhua Peng

Preconditioning with the quantum Fisher information matrix (QFIM) is a popular approach in quantum variational algorithms. Yet the QFIM is costly to obtain directly, usually requiring more state preparation than its classical counterpart:…

Quantum Physics · Physics 2026-04-09 Jianfeng Lu , Kecen Sha

With the rapid deployment of quantum computers and quantum satellites, there is a pressing need to design and deploy quantum and hybrid classical-quantum networks capable of exchanging classical information. In this context, we conduct the…

Quantum Physics · Physics 2023-06-29 Indrakshi Dey , Harun Siljak , Nicola Marchetti

This paper deals with the problem of estimating the coupling constant $\theta$ of a mixing quantum Markov chain. For a repeated measurement on the chain's output we show that the outcomes' time average has an asymptotically normal…

Quantum Physics · Physics 2011-06-23 Madalin Guta

Quantum machine learning is emerging as a promising application of quantum computing due to its distinct way of encoding and processing data. It is believed that large-scale quantum machine learning demonstrates substantial advantages over…

Quantum Physics · Physics 2025-01-15 Kiwmann Hwang , Hyang-Tag Lim , Yong-Su Kim , Daniel K. Park , Yosep Kim

Quantum metrology promises precision beyond classical limits, yet environmental noise typically degrades the quantum resources required for such enhancement. In this work, we investigate frequency estimation in noisy continuous-variable…

Quantum Physics · Physics 2026-05-08 Ayan Patra , Manju , Aditi Sen De , Matteo G. A. Paris

Quantum computing uses the physical principles of very small systems to develop computing platforms which can solve problems that are intractable on conventional supercomputers. There are challenges not only in building the required…

Quantum Physics · Physics 2024-11-19 Dieter Jaksch , Peyman Givi , Andrew J. Daley , Thomas Rung

The Fisher-matrix formalism is used routinely in the literature on gravitational-wave detection to characterize the parameter-estimation performance of gravitational-wave measurements, given parametrized models of the waveforms, and…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Michele Vallisneri

Recently, increased computational power and data availability, as well as algorithmic advances, have led machine learning techniques to impressive results in regression, classification, data-generation and reinforcement learning tasks.…

The quantum Fisher information (QFI) represents a fundamental concept in quantum physics. On the one hand, it quantifies the metrological potential of quantum states in quantum-parameter-estimation measurements. On the other hand, it is…

The state-of-the-art machine learning approaches are based on classical von Neumann computing architectures and have been widely used in many industrial and academic domains. With the recent development of quantum computing, researchers and…

Machine Learning · Computer Science 2020-07-21 Samuel Yen-Chi Chen , Chao-Han Huck Yang , Jun Qi , Pin-Yu Chen , Xiaoli Ma , Hsi-Sheng Goan

Quantum sensing is an important application of emerging quantum technologies. We explore whether a hybrid system of quantum sensors and quantum circuits can surpass the classical limit of sensing. In particular, we use optimization…

We address the characterization of classical fractional random noise via quantum probes. In particular, we focus on estimation and discrimination problems involving the fractal dimension of the trajectories of a system subject to fractional…

Quantum Physics · Physics 2015-06-18 Matteo G. A. Paris

We study the changes in quantum Fisher information (QFI) values for one quantum system consisting of a superposition of W and GHZ states. In a recent work [6], QFI values of this mentioned system studied. In this work, we extend this…

Quantum Physics · Physics 2017-04-26 Volkan Erol

We propose to use the quantum Fisher information in characterizing the information flow of open quantum systems. This information-theoretic approach provides a quantitative measure to statistically distinguish Markovian and non-Markovian…

Quantum Physics · Physics 2010-10-12 Xiao-Ming Lu , Xiaoguang Wang , C. P. Sun

In this paper, we show recent results indicating that using electrical noise as information carrier offers outstanding potentials reminding of quantum informatics. One example is noise-based computing and logic that shows certain…

General Physics · Physics 2008-12-01 Laszlo B. Kish

We examine metrological scenarios where the parameter of interest is encoded onto a quantum state through the action of a noisy quantum gate and investigate the ultimate bound to precision by analyzing the behaviour of the Quantum Fisher…

Quantum Physics · Physics 2025-02-18 Giovanni Ragazzi , Simone Cavazzoni , Paolo Bordone , Matteo G. A. Paris

The Fisher information matrix is a quantity of fundamental importance for information geometry and asymptotic statistics. In practice, it is widely used to quickly estimate the expected information available in a data set and guide…

Methodology · Statistics 2023-06-06 William R. Coulton , Benjamin D. Wandelt