Adaptive quantum state estimation book

In this dissertation, two adaptive estimation algorithms are devised for the case where the signal processes are char acterized as state variables of a known first order, linear. Introduction to quantumstate estimation ebook by yong siah. Firstly, an innovation matrix is used to improve the estimation accuracy by constructing an adaptive correction factor for correcting the prediction covariance matrix in real time. In particular, its asymptotic theory has been developed during this period. Adaptive quantum state estimation for dynamic quantum. Efficient estimation of banach parameters in semiparametric models klaassen, chris a. Accurate estimation of the state of charge soc of batteries is one of the key problems in a battery management system. Belavkin v 20 quantum quasimarkov processes in eventum mechanics dynamics, observation, filtering and control, quantum information processing, 12. Performing quantum state estimation implies the reconstruction of the density. Proceedings of the 2011 american control conference, 43344339. Statistical and adaptive signal processing dimitris. Quantum state tomography and fidelity estimation via.

The sp ectr al the or em for a self a dj o in t op erat or a sa y s tha t. State tomography of qubit systems using linear regression. A generalized circuit for the hamiltonian dynamics through. Bayesian models were used to optimize the data collection process by adaptive measurements in state reconstruction, 7,8,22. This paper further investigates the adaptive linear regression estimation alre. The second one is sequential mc smc 7an importance sampling based algorithmrecently used for adaptive quantum state tomography 8. In this chapter, we propose an adaptive experimental design whose expected losses are smaller than those of standard quantum state tomography. Identification, state estimation, and adaptive control of. Spectral estimation, signal modeling, adaptive filtering and array processing authors. First, an enhanced battery model is proposed to include the impacts due to different discharge rates and temperatures. Adaptive thresholding for sparse covariance matrix estimation. Experimental demonstration of adaptive quantum state estimation ryo okamoto,1,2 minako iefuji,1,2 satoshi oyama,1,2 koichi yamagata,3 hiroshi imai,4 akio fujiwara,3, and shigeki takeuchi1,2, 1research institute for electronic science, hokkaido university, kitaku, sapporo 0010020, japan. Quantum state tomography is a daunting challenge of experimental.

The necessary condition for a regular parametric model to have an adaptive estimator is that. A basic example of this is quantum state tomography, where a quantum state is learned from measurement. Change detection is another kind of adaptive filtering for nonstationary signals, and is the basic tool in fault detection and diagnosis. Adaptive estimator estimates the parameter of interest equally well regardless whether the value of the nuisance parameter is known or not. Pdf download adaptive atmospheric modeling free unquote.

Albeit still quite young, this field has already been recognized as a necessary tool for research in quantum optics and quantum information, beyond being a fascinating subject on its own as it. Quantum state tomography allows the estimation of an unknown quantum state that is available in many identical copies. Adaptive measurements have shown more powerful capability than nonadaptive measurements in quantum phase estimation, 26,27,28 phase tracking, 29. Quantum tomography is a valuable tool in quantum information processing, being essential for characterisation of quantum states, gates, and measurement equipment. A book containing tomography articles from groups around the world, including the second book chapter presented above. Controlling adaptive quantumphase estimation with scalable. In this paper, we consider a similar setting to the one in 4, 5, 6. Dan simon file specification extension pdf pages 530 size 37. Recommended citation hariri, ali mohamad, identification, state estimation, and adaptive control of type i diabetic patients 2011. The control of individual quantum systems promises a new technology for the 21st century quantum technology. In our raqst protocol, no prior assumption is made on the state to be reconstructed. Pdf experimental demonstration of adaptive quantum state. Any reader with a solid foundation in quantum mechanics, linear algebra and calculus would be able to follow the book comfortably.

Measurement projects an initially prepared quantum state onto the eigenstate of a given hamiltonian, and the probability to obtain a particular outcome is proportional to. Adaptive thresholding for sparse covariance matrix estimation tony cai and weidong liu tony cai is dorothy silberberg professor, department of statistics, the wharton school, university of pennsylvania, philadelphia, pa 19104. Kogon file specification extension pdf pages 814 size 11. A novel qgaukf algorithm for dynamic state estimation of.

Adaptive filtering is a branch of digital signal processing which enables the selective enhancement of desired elements of a signal and the reduction of undesired elements. Oct 07, 2018 optimal state estimation kalman, h infinity, and nonlinear approaches authors. Experimental adaptive quantum tomography of twoqubit. The retrospective cost state estimation rcse technique proposed in the present paper is based on an adaptive lter whose input is. Localmeasurementbased quantum state tomography via neural.

Quantum algorithms by optimal state estimation andrew childs caltech institute for quantum information in collaboration with dave bacon university of washington wim van dam uc santa barbara quantph0501044, quantph0504083, quantph0507190. Parallel computing has been the enabling technology of highend machines for many years. It has been experimentally demonstrated for a variety of physical systems, among them the quantum state of a light mode 75, the vibrational state of a single ion 76, and the wave packets of atoms of an atomic beam 77. A seminar on adaptive quantization methods presented by mahesh pawar 2. Optimal state estimation kalman, h infinity, and nonlinear approaches authors. Back and forth nudging for quantum state estimation by. Even though the performances of three kinds of quantum optimizations in fact are almost very closely one another, in. Shigeki takeuchi the first experimental demonstration of an adaptive quantum state estimation aqse is reported. In implementations of aqse, half wave plates hwps driven by mechanical rotators are used to change the measurement basis, but these significantly limit the overall speed of the system. Adaptive state of charge estimation for liion batteries. Now, it has finally become the ubiquitous key to the efficient use of any kind of multiprocessor computer architecture, from smart phones, tablets, embedded systems and cloud computing up to exascale computers. Quantum states can be used to achieve powerlaw scaling better than 0. Saki nohara1, ryo okamoto1,2, koichi yamagata3, akio fujiwara4,5 and. We compared the neural network state reconstruction protocol with a protocol.

Stabilizing feedback controls for quantum systems siam. Applying classical methods of machine learning to the study of quantum systems sometimes called quantum machine learning is the focus of an emergent area of physics research. The approach is based on the quantum phase estimation algorithm qpea proposed by abrams and lloyd, and it relies on projective measurements with an electronic hamiltonian h. This paper proposes an adaptive soc estimation method based on unscented kalman filter algorithms for lithium liion batteries. Adaptive quantum state estimation aqse provides the best possible estimation of unknown parameters of quantum states. This text takes the unique approach that change detection is a natural extension of. Weidong liu is faculty member, department of mathematics and institute of natural sciences, shanghai jiao tong. Adaptive quantization linear quantization instantaneous companding. Quantum state tomography qst aims to determine an unknown quantum state from the outcome of mea.

Yu liu, yuzhang lin and junbo zhao, advanced grid operational tools based on state estimation, for book new technologies for power system. The strong consistency and asymptotic efficiency of aqse have been mathematically proven a. This book is a comprehensive survey of most of the theoretical and experimental achievements in the field of quantum estimation of states and operations. The experiment in 8 relied on a single adaptive step. The first experimental demonstration of an adaptive quantum state estimation aqse is reported. This page is intended to be useful to a variety of visitors, from experimental research groups setting up quantum tomography systems, to students learning about the theory of characterizing quantum states. Tw o imp orta n t typ es o f nor mal op erat ors are selfadjoint a a. Jun 26, 2019 in this paper, a novel quantum genetic algorithm qga is combined with unscented kalman filter ukf for dynamic state estimation of power systems. This book is intended to serve as an instructive and selfcontained medium for advanced undergraduate and postgraduate students to grasp the basics of quantumstate estimation. The update criterion is based on averagevariance optimality aoptimality in classical statistics, and it has low computational cost for onequbit state estimation. This paper proposes a multisensory joint adaptive kalman filter jakf through extending innovationbased adaptive estimation iae to estimate the motion state of the moving vehicles ahead. Experimental neural network enhanced quantum tomography npj. Diversity of quantum optimizations for training adaptive. In this paper, a novel quantum genetic algorithm qga is combined with unscented kalman filter ukf for dynamic state estimation of power systems.

Experimental adaptive quantum tomography of twoqubit states. For a repeated measurement on the chains output we show that. Adaptive methods for state estimation daniele francesco magnani phd thesis university of pavia printed in pavia, italy, november 2009 isbn 9788895767307 the histogr. Quantum statistical inference, a research field with deep roots in the foundations of both quantum physics and mathematical statistics, has made remarkable progress since 1990. However, concerning the problem about the computational complexity as listed in table 3, applying logarithmic search with quantum existence testing to training adaptive support vector regression may cost the least iterations. Experiments of multiphoton entanglement have been performed by several groups.

Quantum state tomography with twostep adaptive strategy. Adaptive quantum state tomography via linear regression. Quantumstate estimation is an important field in quantum information theory that deals with the characterization of states of affairs for quantum sources. This type of estimator will be termed an adaptive estimator since it has the ability to adapt to the initially unknown portion of the statistical model. The circuit complexity depends on the number of summation terms composing the hamiltonian and requires oln number of quantum gates for the simulation of a molecular hamiltonian. Realization of highspeed adaptive quantum state estimation. Adaptive strategy shows decreased sn and time requirements for a given accuracy. We propose a new approach inspired of the bfn method used in geophysical data assimilation 1 to reconstruct the state of the system from the measured data. Achieving quantum precision limit in adaptive qubit state. Jakf views lidar and radar data as the source of the local filters, which aims to adaptively adjust the measurement noise variancecovariance vc matrix r and the system noise vc matrix q. This book begins with background formalism in estimation theory to establish the necessary prerequisites. Fisher information and asymptotic normality in system. The oxford solid state basics steven simon optimal.

The oxford solid state basics steven simon optimal control. Improvement of estimation precision by adaptive design of. In this paper, we call it recursively adaptive quantum state tomography raqst because the parameter estimation is recursively updated and adaptive measurements are used. This requires that understanding of basic results on diverse topics, and derived from different disciplinary perspectives, is required for appreciating the overall picture. Adaptive estimation algorithms iowa state university. The retrospective cost state estimation rcse technique proposed in the present paper is based on an adaptive lter whose input is the innovations. It is a technology that allows scientists to study and predict the performance of various productsimportant for research and development in the industrialized world. Quantum state tomography is the process by which a quantum state is reconstructed using measurements on an ensemble of identical quantum states. Computational mechanics is a scientific discipline that marries physics, computers, and mathematics to emulate natural physical phenomena. Experimental demonstration of adaptive quantum state estimation. Apr 24, 2017 adaptive measurements have shown more powerful capability than nonadaptive measurements in quantum phase estimation, 26,27,28 phase tracking, 29 quantum state discrimination, 30, 31 and. Obviously, an increase on the photon number for fidelity estimation and quantum state tomography causes a dramatic increase in the elements of the positive operator valued measures povms, which results in a great consumption of time in measurements.

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