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Accurately inferring the state of a quantum device from the results of measurements is a crucial task in building quantum information processing hardware. The predominant state estimation procedure, maximum likelihood estimation (MLE),…

Quantum Physics · Physics 2010-05-04 Robin Blume-Kohout

A simple yet efficient method of linear regression estimation (LRE) is presented for quantum state tomography. In this method, quantum state reconstruction is converted into a parameter estimation problem of a linear regression model and…

Quantum Physics · Physics 2013-12-18 Bo Qi , Zhibo Hou , Li Li , Daoyi Dong , Guoyong Xiang , Guangcan Guo

In this paper, we focus on alternate forms of the T-matrix used in the Maximum Likelihood Estimate (MLE) procedure for fitting the experimental data collected in quantum state tomography experiments. In particular, we analyze the single…

Quantum Physics · Physics 2014-10-28 Ramesh Bhandari

Maximum likelihood quantum state tomography yields estimators that are consistent, provided that the likelihood model is correct, but the maximum likelihood estimators may have bias for any finite data set. The bias of an estimator is the…

Quantum Physics · Physics 2017-02-15 G. B. Silva , S. Glancy , H. M. Vasconcelos

This paper proposes and analyzes a new method for quantum state estimation, called hedged maximum likelihood (HMLE). HMLE is a quantum version of Lidstone's Law, also known as the "add beta" rule. A straightforward modification of maximum…

Quantum Physics · Physics 2010-11-11 Robin Blume-Kohout

Quantum tomography requires repeated measurements of many copies of the physical system, all prepared by a source in the unknown state. In the limit of very many copies measured, the often-used maximum-likelihood (ML) method for converting…

Quantum Physics · Physics 2014-10-09 Hui Khoon Ng , Berthold-Georg Englert

In this paper, we derive analytic expressions for the starting (initial) values of the parameters of the T-matrix that is frequently employed in the construction of a theoretical density matrix in a Maximum Likelihood Estimate (MLE)…

Quantum Physics · Physics 2014-07-25 Ramesh Bhandari

Quantum state tomography (QST) is typically performed from a frequentist viewpoint using maximum likelihood estimation (MLE) which seeks to find the best plausible state consistent with the data by maximizing a likelihood function /…

Quantum Physics · Physics 2022-12-22 Daniel J. Lum , Yaakov Weinstein

In quantum state tomography, the estimated frequencies do not correspond directly to a physical quantum state, due to statistical fluctuations. Thus, one resorts to point estimators that return the state that matches observations the best,…

Quantum Physics · Physics 2018-11-09 Sacha Schwarz , Bruno Eckmann , Denis Rosset , André Stefanov

Maximum likelihood estimation is one of the most used methods in quantum state tomography, where the aim is to reconstruct the density matrix of a physical system from measurement results. One strategy to deal with positivity and unit trace…

Because of the constraint that the estimators be bona fide physical states, any quantum state tomography scheme - including the widely used maximum likelihood estimation - yields estimators that may have a bias, although they are consistent…

Quantum Physics · Physics 2014-05-22 Jiangwei Shang , Hui Khoon Ng , Berthold-Georg Englert

Quantum state tomography (QST), the task of estimating an unknown quantum state given measurement outcomes, is essential to building reliable quantum computing devices. Whereas computing the maximum-likelihood (ML) estimate corresponds to…

Machine Learning · Computer Science 2022-08-30 Chien-Ming Lin , Yu-Ming Hsu , Yen-Huan Li

We undertake a detailed study of the performance of maximum likelihood (ML) estimators of the density matrix of finite-dimensional quantum systems, in order to interrogate generic properties of frequentist quantum state estimation. Existing…

Quantum Physics · Physics 2011-11-16 Raj Chakrabarti , Anisha Ghosh

A number of problems in quantum state and system identification are addressed. Specifically, it is shown that the maximum likelihood estimation (MLE) approach, already known to apply to quantum state tomography, is also applicable to…

Quantum Physics · Physics 2007-05-23 Robert Kosut , Ian A. Walmsley , Herschel Rabitz

Conventional methods for computing maximum-likelihood estimators (MLE) often converge slowly in practical situations, leading to a search for simplifying methods that rely on additional assumptions for their validity. In this work, we…

Quantum Physics · Physics 2017-06-28 Jiangwei Shang , Zhengyun Zhang , Hui Khoon Ng

The tomographic reconstruction of the state of a quantum-mechanical system is an essential component in the development of quantum technologies. We present an overview of different tomographic methods for determining the quantum-mechanical…

Quantum Physics · Physics 2016-02-09 Roman Schmied

This paper defines a Maximum Likelihood Estimator (MLE) for the admittance matrix estimation of distribution grids, utilising voltage magnitude and power measurements collected only from common, unsychronised measuring devices (Smart…

Systems and Control · Electrical Eng. & Systems 2022-10-06 Lisa Laurent , Jean-Sébastien Brouillon , Giancarlo Ferrari-Trecate

Maximum likelihood estimation is applied to the determination of an unknown quantum measurement. The measuring apparatus performs measurements on many different quantum states and the positive operator-valued measures governing the…

Quantum Physics · Physics 2009-11-07 Jaromir Fiurasek

The maximum likelihood estimator (MLE) is pivotal in statistical inference, yet its application is often hindered by the absence of closed-form solutions for many models. This poses challenges in real-time computation scenarios,…

Methodology · Statistics 2025-04-16 Pedro L. Ramos , Eduardo Ramos , Francisco A. Rodrigues , Francisco Louzada

Tomography of a quantum state is usually based on positive operator-valued measure (POVM) and on their experimental statistics. Among the available reconstructions, the maximum-likelihood (MaxLike) technique is an efficient one. We propose…

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