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Related papers: Bayesian estimation in homodyne interferometry

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Many statistical applications involve models for which it is difficult to evaluate the likelihood, but from which it is relatively easy to sample. Approximate Bayesian computation is a likelihood-free method for implementing Bayesian…

Methodology · Statistics 2017-11-29 Wentao Li , Paul Fearnhead

Quantum phase estimation based on Gaussian states plays a crucial role in many application fields. In this paper, we study the precision bound for the scheme using two-mode squeezed Gaussian states. The quantum Fisher information is…

Quantum Physics · Physics 2024-11-27 Jian-Dong Zhang , Chuang Li , Lili Hou , Shuai Wang

The measurement problem for the optical phase has been traditionally attacked for noiseless schemes or in the presence of amplitude or detection noise. Here we address estimation of phase in the presence of phase diffusion and evaluate the…

Quantum Physics · Physics 2015-03-17 Marco G. Genoni , Stefano Olivares , Matteo G. A. Paris

This paper is concerned with the optimal identification problem of dynamical systems in which only quantized output observations are available under the assumption of fixed thresholds and bounded persistent excitations. Based on a…

Systems and Control · Electrical Eng. & Systems 2023-09-12 Ying Wang , Yanlong Zhao , Ji-Feng Zhang

To improve the phase sensitivity, multi-photon subtraction schemes within the SU(1,1) interferometer are proposed. The input states are the coherent state and the vacuum state, and the detection method is homodyne detection. The effects of…

Quantum Physics · Physics 2023-11-27 Q. Q. Kang , Z. K. Zhao , Y. K. Xu , T. Zhao , C. J. Liu , L. Y. Hu

Bayesian predictive inference propagates parameter uncertainty to quantities of interest through the posterior-predictive distribution. In practice, this is typically performed using a two-stage procedure: first approximating the posterior…

Machine Learning · Statistics 2026-05-06 Nan Feng , Xun Huan

Bayesian methods are developed for the multivariate nonparametric regression problem where the domain is taken to be a compact Riemannian manifold. In terms of the latter, the underlying geometry of the manifold induces certain symmetries…

Statistics Theory · Mathematics 2007-06-13 Jean-François Angers , Peter T. Kim

Approximate Bayesian Computation is a family of likelihood-free inference techniques that are well-suited to models defined in terms of a stochastic generating mechanism. In a nutshell, Approximate Bayesian Computation proceeds by computing…

Computation · Statistics 2010-07-28 Michael Blum

We consider a nonparametric Bayesian approach to estimation and testing for a multivariate monotone density. Instead of following the conventional Bayesian route of putting a prior distribution complying with the monotonicity restriction,…

Statistics Theory · Mathematics 2023-06-09 Kang Wang , Subhashis Ghosal

We investigate the scaling of the phase sensitivity of a nonideal Heisenberg-limited interferometer with the particle number N, in the case of the Bayesian detection procedure proposed by Holland and Burnett [p.r.l. 71, p. 1355 (1993)] for…

Quantum Physics · Physics 2009-11-10 Raphael Pooser , Olivier Pfister

We derive, and experimentally demonstrate, an interferometric scheme for unambiguous phase estimation with precision scaling at the Heisenberg limit that does not require adaptive measurements. That is, with no prior knowledge of the phase,…

Quantum Physics · Physics 2010-09-01 B. L. Higgins , D. W. Berry , S. D. Bartlett , M. W. Mitchell , H. M. Wiseman , G. J. Pryde

We revisit the problem of estimating an unknown parameter of a pure quantum state, and investigate `null-measurement' strategies in which the experimenter aims to measure in a basis that contains a vector close to the true system state.…

Quantum Physics · Physics 2023-10-11 Federico Girotti , Alfred Godley , Mădălin Guţă

In the present paper we consider the varying coefficient model which represents a useful tool for exploring dynamic patterns in many applications. Existing methods typically provide asymptotic evaluation of precision of estimation…

Statistics Theory · Mathematics 2013-02-07 Olga Klopp , Marianna Pensky

We address a phase estimation scheme using Gaussian states in the presence of non-Gaussian phase noise. At variance with previous analysis, we analyze situations in which the noise occurs before encoding phase information. In particular, we…

Quantum Physics · Physics 2020-12-17 Giacomo Carrara , Marco G. Genoni , Simone Cialdi , Matteo G. A. Paris , Stefano Olivares

We apply nonparametric Bayesian methods to study the problem of estimating the intensity function of an inhomogeneous Poisson process. We exhibit a prior on intensities which both leads to a computationally feasible method and enjoys…

Statistics Theory · Mathematics 2013-11-28 Eduard Belitser , Paulo Serra , Harry van Zanten

Due to the potential of quantum advantage to surpass the standard quantum limit (SQL), the nonlinear interferometers have garnered significant attention from researchers in the field of precision measurement. However, many practical…

Quantum Physics · Physics 2025-05-20 Mengyao Zhou , Hongmei Ma , Liqing Chen , Weiping Zhang , Chun-Hua Yuan

We experimentally analyzed the statistical errors in quantum-state estimation and examined whether their lower bound, which is derived from the Cramer-Rao inequality, can be truly attained or not. In the experiments, polarization states of…

Quantum Physics · Physics 2013-05-29 Koji Usami , Yoshihiro Nambu , Yoshiyuki Tsuda , Keiji Matsumoto , Kazuo Nakamura

Optical phase measurement is a simple example of a quantum--limited measurement problem with important applications in metrology such as gravitational wave detection. The formulation of optimal strategies for such measurements is an…

Quantum Physics · Physics 2012-12-18 K. R. W. Jones

We investigated the estimation of an unknown Gaussian process (containing displacement, squeezing and phase-shift) applied to a matter system. The state of the matter system is not directly measured; instead, we measure an optical mode…

Quantum Physics · Physics 2017-08-09 László Ruppert , Radim Filip

In this paper we consider a network of agents monitoring a spatially distributed arrival process. Each node measures the number of arrivals seen at its monitoring point in a given time-interval with the objective of estimating the unknown…

Optimization and Control · Mathematics 2017-02-17 Angelo Coluccia , Giuseppe Notarstefano