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We propose an iterative algorithm for incomplete quantum process tomography, with the help of quantum state estimation, based on the combined principles of maximum-likelihood and maximum-entropy. The algorithm yields a unique estimator for…

Quantum Physics · Physics 2012-01-04 Yong Siah Teo , Berthold-Georg Englert , Jaroslav Rehacek , Zdenek Hradil

In the last years several estimation strategies have been formulated to determine the value of an unknown parameter in the most precise way, taking into account the presence of noise. These strategies typically rely on the use of quantum…

Quantum Physics · Physics 2021-08-31 Andrea Smirne , Andreas Lemmer , Martin B. Plenio , Susana F. Huelga

We address the problem of estimating the inputs of a dynamical system from measurements of the system's outputs. To this end, we introduce a novel estimation algorithm that explicitly trades off bias and variance to optimally reduce the…

Machine Learning · Computer Science 2019-09-20 Sebastian Curi , Kfir Y. Levy , Andreas Krause

Optical absorption measurements characterize a wide variety of systems from atomic gases to \emph{in-vivo} diagnostics of living organisms. Here we study the potential of non-classical techniques to reduce statistical noise below the…

In this technical communique, we propose a novel observer-based adaptive scheme to deal with the parameter estimation problem of biased sinusoidal signals. Different from the existing adaptive frequency estimation scheme, the proposed…

Dynamical Systems · Mathematics 2020-12-29 Shang Shi , Huifang Min , Shihong Ding

This paper considers sequential adaptive estimation of sparse signals under a constraint on the total sensing effort. The advantage of adaptivity in this context is the ability to focus more resources on regions of space where signal…

Methodology · Statistics 2013-04-03 Dennis Wei , Alfred O. Hero

Using Bayesian experimental design techniques, we have shown that for a single two-level quantum mechanical system under strong (projective) measurement, the dynamical parameters of a model Hamiltonian can be estimated with exponentially…

Quantum Physics · Physics 2012-06-05 Christopher Ferrie , Christopher E. Granade , D. G. Cory

The super-sensitivity attained in quantum phase estimation is known to be compromised in the presence of decoherence. This is particularly patent at blind spots -- phase values at which sensitivity is totally lost. One remedy is to use a…

Quantum Physics · Physics 2017-10-25 Walker Larson , Bahaa Saleh

We consider the phase sensing via weak optical coherent state at quantum limit precision. A new detection scheme for the phase estimation is proposed which is inspired by the suboptimal quantum measurement in coherent optical communication.…

Quantum Physics · Physics 2016-09-28 Shuro Izumi , Masahiro Takeoka , Kentaro Wakui , Mikio Fujiwara , Kazuhiro Ema , Masahide Sasaki

We propose an approach to measure the quantum phase of an electron in a non-Abelian system using the algorithm of Quantum Phase Estimation (QPE). The discrete-path systems were previously studied in the context of square or rectangular…

Quantum Physics · Physics 2025-09-15 Seng Ghee Tan , Son-Hsien Chen , Ying-Cheng Yang , Yen-Fu Chen , Yen-Lin Chen , Chia-Hsiu Hsieh

In this letter we revisit the problem of optimal design of quantum tomographic experiments. In contrast to previous approaches where an optimal set of measurements is decided in advance of the experiment, we allow for measurements to be…

Quantum Physics · Physics 2017-02-28 Ferenc Huszár , Neil M. T. Houlsby

Bayesian error analysis paves the way to the construction of credible and plausible error regions for a point estimator obtained from a given dataset. We introduce the concept of region accuracy for error regions (a generalization of the…

Quantum Physics · Physics 2019-07-15 Changhun Oh , Yong Siah Teo , Hyunseok Jeong

Quantum metrology promises greater sensitivity for optical phase measurements than could ever be achieved classically. Here we present a theory of the phase sensitivity for the general case where the detection probability is given by an $N$…

After a derivation of the quantum Bayes theorem, and a discussion of the reconstruction of the unknown state of identical spin systems by repeated measurements, the main part of this paper treats the problem of determining the unknown phase…

Quantum Physics · Physics 2009-11-11 Filippo Neri

Various phase concepts may be treated as special cases of the maximum likelihood estimation. For example the discrete Fourier estimation that actually coincides with the operational phase of Noh, Fouge`res and Mandel is obtained for…

Quantum Physics · Physics 2009-10-31 Jaroslav Rehacek , Zdenek Hradil , Michael Zawisky , Saverio Pascazio , Helmut Rauch , Jan Perina

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

High precision measurements are essential to solve major scientific and technological challenges, from gravitational wave detection to healthcare diagnostics. Quantum sensing delivers greater precision, but an in-depth optimisation of…

The preparation stage of optical qubits is an essential task in all the experimental setups employed for the test and demonstration of Quantum Optics principles. We consider a deterministic protocol for the preparation of qubits as a…

Quantum Physics · Physics 2015-06-19 Nicola Dalla Pozza , Howard M. Wiseman , Elanor H. Huntington

Quantum-enhanced metrology aims to estimate an unknown parameter such that the precision scales better than the shot-noise bound. Single-shot adaptive quantum-enhanced metrology (AQEM) is a promising approach that uses feedback to tweak the…

Quantum Physics · Physics 2016-10-17 Pantita Palittapongarnpim , Peter Wittek , Barry C. Sanders

Suppose a process yields independent observations whose distributions belong to a family parameterized by \theta\in\Theta. When the process is in control, the observations are i.i.d. with a known parameter value \theta_0. When the process…

Statistics Theory · Mathematics 2007-06-13 Gary Lorden , Moshe Pollak