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Related papers: Bayesian estimation in homodyne interferometry

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We study a model of a two-level system (i.e. a qubit) in interaction with the electromagnetic field. By means of homodyne detection, one field-quadrature is observed continuously in time. Due to the interaction, information about the…

Quantum Physics · Physics 2009-11-11 Bas Janssens , Luc Bouten

We introduce a methodology for robust Bayesian estimation with robust divergence (e.g., density power divergence or {\gamma}-divergence), indexed by a single tuning parameter. It is well known that the posterior density induced by robust…

Methodology · Statistics 2022-07-04 Shouto Yonekura , Shonosuke Sugasawa

The quantum Fisher information for a two-mode, Gaussian product state in an interferometer subject to photon loss is studied. We obtain the quantum Cramer-Rao bound on the achievable precision in phase estimation using such states. The…

Quantum Physics · Physics 2016-08-30 Noufal Jaseem , Anil Shaji

The Bayesian Cram\'er-Rao bound (CRB) provides a lower bound on the mean square error of any Bayesian estimator under mild regularity conditions. It can be used to benchmark the performance of statistical estimators, and provides a…

Machine Learning · Statistics 2024-09-09 Evan Scope Crafts , Xianyang Zhang , Bo Zhao

The Cram\'er-Rao bound and the quantum Fisher information have been tools used extensively for interferometric phase sensitivity. Most scenarios considering a Mach-Zehnder interferometer with two input sources focused on the phase-matched…

Quantum Physics · Physics 2019-05-08 Anca Preda , Stefan Ataman

The tilted-wave interferometer is a promising technique for the development of a reference measurement system for the highly accurate form measurement of aspheres and freeform surfaces. The technique combines interferometric measurements,…

We analyse the precision limits for simultaneous estimation of a pair of conjugate parameters in a displacement channel using Gaussian probes. Having a set of squeezed states as an initial resource, we compute the Holevo Cram\'er-Rao bound…

Quantum Physics · Physics 2020-05-27 Syed M. Assad , Jiamin Li , Yuhong Liu , Ningbo Zhao , Wen Zhao , Ping Koy Lam , Z. Y. Ou , Xiaoying Li

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

We apply a Kennedy-type detection scheme, which was originally proposed for a binary communications system, to interferometric sensing devices. We show that the minimum detectable perturbation of the proposed system reaches the ultimate…

Quantum Physics · Physics 2009-11-07 Masahiro Takeoka , Masashi Ban , Masahide Sasaki

Existing optimal estimators of nonequilibrium path-ensemble averages are shown to fall within the framework of extended bridge sampling. Using this framework, we derive a general minimal-variance estimator that can combine nonequilibrium…

Statistical Mechanics · Physics 2011-12-06 David D. L. Minh , John D. Chodera

This paper introduces a quasi-Bayesian method that integrates frequentist nonparametric estimation with Bayesian inference in a two-stage process. Applied to an endogenous discrete choice model, the approach first uses kernel or sieve…

Econometrics · Economics 2025-05-20 Ruixuan Liu , Zhengfei Yu

Achieving ultimate bounds in estimation processes is the main objective of quantum metrology. In this context, several problems require measurement of multiple parameters by employing only a limited amount of resources. To this end,…

We identify the critical deviation scale governing Bayesian evidence accumulation in regular parametric testing. Under integrated Bayes risk with zero-one loss, the risk-optimal rejection boundary lies in a moderate deviation regime, with a…

Statistics Theory · Mathematics 2026-03-23 Jyotishka Datta , Nicholas G. Polson , Vadim Sokolov , Daniel Zantedeschi

This article introduces a nonparametric approach to spectral analysis of a high-dimensional multivariate nonstationary time series. The procedure is based on a novel frequency-domain factor model that provides a flexible yet parsimonious…

Methodology · Statistics 2019-10-29 Zeda Li , Ori Rosen , Fabio Ferrarelli , Robert T. Krafty

In recent years there has been substantial development in algorithms for quantum phase estimation. In this work we provide a new approach to online Bayesian phase estimation that achieves Heisenberg limited scaling that requires…

Quantum Physics · Physics 2022-08-10 Cassandra Granade , Nathan Wiebe

High-precision frequency estimation is an ubiquitous issue in fundamental physics and a critical task in spectroscopy. Here, we propose a quantum Ramsey interferometry to realize high-precision frequency estimation in spin-1 Bose-Einstein…

Quantum Physics · Physics 2021-09-06 Min Zhuang , Hongtao Huo , Yuxiang Qiu , Wenjie Liu , Jiahao Huang , Chaohong Lee

We address the joint estimation of the two defining parameters of a displacement operation in phase space. In a measurement scheme based on a Gaussian probe field and two homodyne detectors, it is shown that both conjugated parameters can…

Quantum Physics · Physics 2013-01-16 M. G. Genoni , M. G. A. Paris , G. Adesso , H. Nha , P. L. Knight , M. S. Kim

Atom interferometers are reaching sensitivities fundamentally constrained by quantum fluctuations. A main challenge is to integrate entanglement into quantum sensing protocols to enhance precision while ensuring robustness against noise and…

I propose an approach to adaptive homodyne detection of digitally modulated quantum optical pulses in which the phase of the local oscillator is chosen to maximize the average information gain, i.e., the mutual information, at each step of…

Quantum Physics · Physics 2007-05-23 Igor Bargatin

This paper presents a new performance bound for estimation problems where the parameter to estimate lies in a Riemannian manifold (a smooth manifold endowed with a Riemannian metric) and follows a given prior distribution. In this setup,…

Statistics Theory · Mathematics 2024-09-10 Florent Bouchard , Alexandre Renaux , Guillaume Ginolhac , Arnaud Breloy
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