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In quantum theory, the inescapable interaction between a system and its surroundings would lead to a loss of coherence and leakage of information into the environment. An effective approach to retain the quantum characteristics of the…

Quantum Physics · Physics 2025-08-29 Guohui Dong , Yao Yao

We review the introduction of likelihood functions and Fisher information in classical estimation theory, and we show how they can be defined in a very similar manner within quantum measurement theory. We show that the stochastic master…

Quantum Physics · Physics 2013-04-03 Søren Gammelmark , Klaus Mølmer

Recent years have seen unprecedented advance in the design and control of quantum computers. Nonetheless, their applicability is still restricted and access remains expensive. Therefore, a substantial amount of quantum algorithms research…

Quantum Physics · Physics 2020-12-11 Thomas Grurl , Richard Kueng , Jürgen Fuß , Robert Wille

The most widely used approach for simulating the dynamics of time-dependent Hamiltonians via quantum computation depends on the quantum-classical hybrid variational quantum time evolution algorithm, in which ordinary differential equations…

Quantum Physics · Physics 2026-03-19 Minchen Qiao , Zi-Ming Li , Yu-xi Liu

We describe a simple quantum algorithm to simulate time-dependent Hamiltonian, extending the methodology of quantum signal processing. The framework achieves optimal scaling up to some factor with respect to other parameters, and nearly…

Quantum Physics · Physics 2025-03-11 Nhat A. Nghiem

While quantum simulation is one of the most promising applications of modern quantum devices, accessible simulation times are fundamentally limited by finite coherence times due to omnipresent noise. Based on the ideas of relational…

Quantum Physics · Physics 2025-09-03 Sebastian Gemsheim , Felix Fritzsch

A variational principle enabling one to compute individual Floquet states of a periodically time-dependent quantum system is formulated, and successfully tested against the benchmark system provided by the analytically solvable model of a…

Quantum Physics · Physics 2020-10-29 Nils Krüger

We propose a method for constructing $\texttt{PREPARE}$ circuits for quantum phase estimation of a molecular Hamiltonian in quantum chemistry by using variational optimization of quantum circuits solely on classical computers. The…

Quantum Physics · Physics 2025-05-02 Hayata Morisaki , Kosuke Mitarai , Keisuke Fujii , Yuya O. Nakagawa

Electronic structure simulation is an anticipated application for quantum computers. Due to high-dimensional quantum entanglement in strongly correlated systems, the quantum resources required to perform such simulations are far beyond the…

Quantum Physics · Physics 2022-01-25 Jie Liu , Zhenyu Li , Jinlong Yang

The Quantum Fisher Information matrix (QFIM) is a central metric in promising algorithms, such as Quantum Natural Gradient Descent and Variational Quantum Imaginary Time Evolution. Computing the full QFIM for a model with $d$ parameters,…

Quantum Physics · Physics 2021-10-20 Julien Gacon , Christa Zoufal , Giuseppe Carleo , Stefan Woerner

Variational quantum circuits build the foundation for various classes of quantum algorithms. In a nutshell, the weights of a parametrized quantum circuit are varied until the empirical sampling distribution of the circuit is sufficiently…

Efficiently characterising quantum systems, verifying operations of quantum devices and validating underpinning physical models, are central challenges for the development of quantum technologies and for our continued understanding of…

The characterization of the Hamiltonian parameters defining a quantum walk is of paramount importance when performing a variety of tasks, from quantum communication to computation. When dealing with physical implementations of quantum…

Quantum Physics · Physics 2024-03-15 Ilaria Gianani , Claudia Benedetti

Hamiltonian Monte Carlo (HMC) is an efficient Bayesian sampling method that can make distant proposals in the parameter space by simulating a Hamiltonian dynamical system. Despite its popularity in machine learning and data science, HMC is…

Machine Learning · Statistics 2020-09-02 Ziming Liu , Zheng Zhang

Learning quantum Hamiltonians with high precision is important for quantum physics and quantum information science. We propose a multi-stage neural network framework that significantly enhances Hamiltonian learning precision through…

Quantum Physics · Physics 2025-03-11 Zhengjie Kang , Hao Li , Shuo Wang , Jiaojiao Li , Yuanjie Zhang , Zhihuang Luo

In this work we propose an approach for implementing time-evolution of a quantum system using product formulas. The quantum algorithms we develop have provably better scaling (in terms of gate complexity and circuit depth) than a naive…

A pivotal task in quantum metrology, and quantum parameter estimation in general, is to de- sign schemes that achieve the highest precision with given resources. Standard models of quantum metrology usually assume the dynamics is fixed, the…

Quantum Physics · Physics 2017-07-18 Jing Liu , Haidong Yuan

There is a prevalent effort to achieve quantum-enhanced metrology using criticality. However, the extent to which estimation precision is enhanced through criticality still needs further exploration under the constraint of finite time…

Quantum Physics · Physics 2024-07-31 Rui Zhang , Wenkui Ding , Zhucheng Zhang , Lei Shao , Yuyu Zhang , Xiaoguang Wang

Quantum metrology based on quantum entanglement and quantum coherence improves the accuracy of measurement. In this paper, we briefly review the schemes of quantum metrology in various complex systems, including non-Markovian noise,…

Quantum Physics · Physics 2024-01-18 Qing Ai , Yang-Yang Wang , Jing Qiu

Observations or measurements taken of a quantum system (a small number of fundamental particles) are inherently random. If the state of the system depends on unknown parameters, then the distribution of the outcome depends on these…

Statistics Theory · Mathematics 2007-06-13 Richard D. Gill
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