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Characterizing quantum dynamics is essential for quantifying arbitrary properties of a quantum process -- such as its ability to exhibit quantum-mechanical dynamics or generate entanglement. However, current methods require a number of…

Nonparametric regression is a standard statistical tool with increased importance in the Big Data era. Boundary points pose additional difficulties but local polynomial regression can be used to alleviate them. Local linear regression, for…

Other Statistics · Statistics 2017-04-04 Srinjoy Das , Dimitris N. Politis

We extend a recently established asymptotic normality theorem for generalized linear mixed models to include the dispersion parameter. The new results show that the maximum likelihood estimators of all model parameters have asymptotically…

Statistics Theory · Mathematics 2022-08-11 Aishwarya Bhaskaran , Matt P. Wand

This article discusses the problem of estimation of parameters in finite mixtures when the mixture components are assumed to be symmetric and to come from the same location family. We refer to these mixtures as semi-parametric because no…

Statistics Theory · Mathematics 2007-08-07 David R. Hunter , Shaoli Wang , Thomas P. Hettmansperger

We address continuous weak linear quantum measurement and argue that it is best understood in terms of statistics of the outcomes of the linear detectors measuring a quantum system, for example, a qubit. We mostly concentrate on a setup…

Mesoscale and Nanoscale Physics · Physics 2008-07-14 Hongduo Wei , Yuli V. Nazarov

The estimation of more than one parameter in quantum mechanics is a fundamental problem with relevant practical applications. In fact, the ultimate limits in the achievable estimation precision are ultimately linked with the…

Quantum Physics · Physics 2020-10-28 Sholeh Razavian , Matteo G. A. Paris , Marco G. Genoni

Nonparametric estimation of a mixing density based on observations from the corresponding mixture is a challenging statistical problem. This paper surveys the literature on a fast, recursive estimator based on the predictive recursion…

Methodology · Statistics 2022-09-15 Ryan Martin

We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is…

Quantum Physics · Physics 2017-12-12 Beili Gong , Wei Cui

Quantum scrambling describes the spreading of local information into many degrees of freedom in quantum systems. This provides the conceptual connection among diverse phenomena ranging from thermalizing quantum dynamics to models of black…

We address several estimation problems in quantum optics by means of the maximum-likelihood principle. We consider Gaussian state estimation and the determination of the coupling parameters of quadratic Hamiltonians. Moreover, we analyze…

Quantum Physics · Physics 2009-11-06 G. Mauro D'Ariano , Matteo G. A. Paris , Massimiliano F. Sacchi

We present a protocol for probing the state of a quantum system by its resonant coupling and entanglement with a meter system. By continuous measurement of a time evolving meter observable, we infer the evolution of the entangled systems…

Quantum Physics · Physics 2022-10-05 A. L. Andersen , K. Mølmer

In quantum metrology schemes, one generally needs to prepare $m$ copies of $N$ entangled particles, such as entangled photon states, and then they are detected in a destructive process to estimate an unknown parameter. Here, we present a…

Quantum Physics · Physics 2015-06-18 Yu-Ran Zhang , Jie-Dong Yue , Heng Fan

The simultaneous estimation of multiple unknown parameters is the most general scenario in quantum sensing. Quantum multi-parameter estimation theory provides fundamental bounds on the achievable precision of simultaneous estimation.…

Quantum Physics · Physics 2025-12-02 Yaoling Yang , Victor Montenegro , Abolfazl Bayat

The exact statistics of an arbitrary quantum observable is analytically obtained. Due to the probabilistic nature of a sequence of intermediate measurements and stochastic fluctuations induced by the interaction with the environment, the…

Statistical Mechanics · Physics 2019-06-19 Stefano Gherardini

The basic goal of quantization for probability distribution is to reduce the number of values, which is typically uncountable, describing a probability distribution to some finite set and thus approximation of a continuous probability…

Probability · Mathematics 2021-01-27 Mrinal Kanti Roychowdhury

No physical measurement can be performed with infinite precision. This leaves a loophole in the standard no-go arguments against non-contextual hidden variables. All such arguments rely on choosing special sets of quantum-mechanical…

Quantum Physics · Physics 2009-10-31 Rob Clifton , Adrian Kent

This paper deals with nonparametric maximum likelihood estimation for Gaussian locally stationary processes. Our nonparametric MLE is constructed by minimizing a frequency domain likelihood over a class of functions. The asymptotic behavior…

Statistics Theory · Mathematics 2011-11-10 Rainer Dahlhaus , Wolfgang Polonik

The continuous quantum measurement within the probability representation of quantum mechanics is discussed. The partial classical propagator of the symplectic tomogram associated to a particular measurement outcome is introduced, for which…

Quantum Physics · Physics 2021-08-03 Yan Przhiyalkovskiy

In this work, we consider the problem of online (real-time, single-shot) estimation of static or slow-varying parameters along quantum trajectories in quantum dynamical systems. Based on the measurement signal of a continuously-monitored…

Quantum Physics · Physics 2024-06-19 Henrik Glavind Clausen , Pierre Rouchon , Rafal Wisniewski

Measuring the polarisation of a single photon typically results in its destruction. We propose, demonstrate, and completely characterise a \emph{quantum non-demolition} (QND) scheme for realising such a measurement non-destructively. This…

Quantum Physics · Physics 2008-11-26 G. J. Pryde , J. L. O'Brien , A. G. White , S. D. Bartlett , T. C. Ralph