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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

Exact simulations of quantum circuits (QCs) are currently limited to $\sim$50 qubits because the memory and computational cost required to store the QC wave function scale exponentially with qubit number. Therefore, developing efficient…

Quantum Physics · Physics 2025-02-18 Marco Bernardi

The use of special quantum states to achieve sensitivities below the limits established by classically behaving states has enjoyed immense success since its inception. In bosonic interferometers, squeezed states, number states and cat…

An extended quadratic function is a quadratic function plus the indicator function of an affine set, that is, a quadratic function with embedded linear equality constraints. We show that, under some technical conditions, random convex…

Optimization and Control · Mathematics 2018-11-02 Shane Barratt , Stephen Boyd

We derive stochastic master equations for a quantum system interacting with a Bose field prepared in a superposition of continuous-mode coherent states. To determine a conditional evolution of the quantum system we use a collision model…

Quantum Physics · Physics 2020-02-11 Anita Dabrowska

The fully entangled fraction (FEF) measures the proximity of a quantum state to maximally entangled states. FEF $>\frac{1}{d}$, in $d \otimes d$ systems is a significant benchmark for various quantum information processing protocols…

Quantum Physics · Physics 2025-03-07 Komal Kumar , Indranil Chakrabarty , Nirman Ganguly

Bosonic codes utilize the infinite-dimensional Hilbert space of harmonic oscillators to encode quantum information, offering a hardware-efficient approach to quantum error correction. Designing these codes requires precise geometric…

Quantum Physics · Physics 2025-12-01 Yaoling Yang , Andrew Tanggara , Tobias Haug , Kishor Bharti

Bayesian estimation is a vital tool in robotics as it allows systems to update the robot state belief using incomplete information from noisy sensors. To render the state estimation problem tractable, many systems assume that the motion and…

Robotics · Computer Science 2025-01-13 Miguel Saavedra-Ruiz , Steven A. Parkison , Ria Arora , James Richard Forbes , Liam Paull

Quantum Amplitude Estimation (QAE) can achieve a quadratic speed-up for applications classically solved by Monte Carlo simulation. A key requirement to realize this advantage is efficient state preparation. If state preparation is too…

Quantum Physics · Physics 2021-03-17 Almudena Carrera Vazquez , Stefan Woerner

This article presents an up-to-date tutorial review of nonlinear Bayesian estimation. State estimation for nonlinear systems has been a challenge encountered in a wide range of engineering fields, attracting decades of research effort. To…

Systems and Control · Computer Science 2017-12-15 Huazhen Fang , Ning Tian , Yebin Wang , MengChu Zhou , Mulugeta A. Haile

The quantum-phase-estimation algorithm (QPEA) is widely used to find estimates of unknown phases. The original algorithm relied on an input state in a uniform superposition of all possible bit strings. However, it is known that other input…

Quantum Physics · Physics 2025-05-05 Joseph G. Smith , Crispin H. W. Barnes , David R. M. Arvidsson-Shukur

Traditional state estimation (SE) methods that are based on nonlinear minimization of the sum of localized measurement error functionals are known to suffer from non-convergence and large residual errors. In this paper we propose an…

Systems and Control · Electrical Eng. & Systems 2020-09-01 Shimiao Li , Amritanshu Pandey , Soummya Kar , Larry Pileggi

Exotic stochastic processes are shown to emerge in the quantum evolution of complex systems. Using influence function techniques, we consider the dynamics of a system coupled to a chaotic subsystem described through random matrix theory. We…

chao-dyn · Physics 2009-10-31 Dimitri Kusnezov , Aurel Bulgac , Giu Do Dang

This paper studies uniform stabilization and social optimality for linear quadratic (LQ) mean field control problems with multiplicative noise, where agents are coupled via dynamics and individual costs. The state and control weights in…

Optimization and Control · Mathematics 2022-03-31 Bingchang Wang , Huanshui Zhang

We investigate the generation of quantum states for precision metrology in noisy two-level systems. These states are obtained by optimizing a variational quantum circuit to maximize the quantum Fisher information (QFI) of the output state…

The resonant state expansion, a rigorous perturbation theory, recently developed in electrodynamics, is applied to non-relativistic quantum mechanical systems in one dimension. The method is used here for finding the resonant states in…

Quantum Physics · Physics 2019-05-08 A. Tanimu , E. A. Muljarov

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

We study the problem of estimating the Schwarzschild radius of a massive body using Gaussian quantum probe states. Previous calculations assumed that the probe state remained pure after propagating a large distance. In a realistic scenario,…

Quantum Physics · Physics 2016-05-18 Sebastian P. Kish , Timothy C. Ralph

We derive the form of the quantum filter equation describing the continuous observation of the phase of a quantum system in an arm of an interferometer via non-demolition measurements when the statistics of an input field used for the…

Quantum Physics · Physics 2016-01-19 John Gough

To explore the limits of a stochastic gradient method, it may be useful to consider an example consisting of an infinite number of quadratic functions. In this context, it is appropriate to determine the expected value and the covariance…

Optimization and Control · Mathematics 2022-12-14 Melinda Hagedorn