Adaptive quantum state estimation book

This book begins with background formalism in estimation theory to establish the necessary prerequisites. The second one is sequential mc smc 7an importance sampling based algorithmrecently used for adaptive quantum state tomography 8. Dan simon file specification extension pdf pages 530 size 37. 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. 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. Achieving quantum precision limit in adaptive qubit state. 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 book is the first comprehensive treatment of modern quantum measurement and measurementbased quantum control, which are vital elements for realizing quantum technology. 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. For a repeated measurement on the chains output we show that. Back and forth nudging for quantum state estimation by. Experimental adaptive quantum tomography of twoqubit.

Adaptive quantum state estimation aqse provides the best possible estimation of unknown parameters of quantum states. Controlling adaptive quantumphase estimation with scalable. Optimal state estimation kalman, h infinity, and nonlinear approaches authors. A generalized circuit for the hamiltonian dynamics through. Quantum state tomography qst aims to determine an unknown quantum state from the outcome of mea. Computational mechanics is a scientific discipline that marries physics, computers, and mathematics to emulate natural physical phenomena. 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. We compared the neural network state reconstruction protocol with a protocol. 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. 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.

The first experimental demonstration of an adaptive quantum state estimation aqse is reported. This text takes the unique approach that change detection is a natural extension of. Saki nohara1, ryo okamoto1,2, koichi yamagata3, akio fujiwara4,5 and. Change detection is another kind of adaptive filtering for nonstationary signals, and is the basic tool in fault detection and diagnosis.

Quantum state tomography with twostep adaptive strategy. Efficient estimation of banach parameters in semiparametric models klaassen, chris a. Experimental adaptive quantum tomography of twoqubit states. Adaptive estimation algorithms iowa state university. Recently, quantum information theory has been developing through a fusion of results from various research fields. Adaptive quantum state tomography via linear regression. Experimental demonstration of adaptive quantum state estimation. Proceedings of the 2011 american control conference, 43344339. Experimental neural network enhanced quantum tomography npj. The sp ectr al the or em for a self a dj o in t op erat or a sa y s tha t. In this chapter, we propose an adaptive experimental design whose expected losses are smaller than those of standard quantum state tomography. The strong consistency and asymptotic efficiency of aqse have been mathematically. Adaptive estimator estimates the parameter of interest equally well regardless whether the value of the nuisance parameter is known or not. Experiments of multiphoton entanglement have been performed by several groups.

Localmeasurementbased quantum state tomography via neural. 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. 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. 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. Recommended citation hariri, ali mohamad, identification, state estimation, and adaptive control of type i diabetic patients 2011. 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. As discussed below, this estimator differs from the technique used in.

Shigeki takeuchi the first experimental demonstration of an adaptive quantum state estimation aqse is reported. 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. Adaptive measurements have shown more powerful capability than nonadaptive measurements in quantum phase estimation, 26,27,28 phase tracking, 29. Oct 07, 2018 optimal state estimation kalman, h infinity, and nonlinear approaches authors. Quantum state tomography allows the estimation of an unknown quantum state that is available in many identical copies. We design an observer, which is an estimation of the quantum systems. Adaptive methods for state estimation daniele francesco magnani phd thesis university of pavia printed in pavia, italy, november 2009 isbn 9788895767307 the histogr. This paper proposes an adaptive soc estimation method based on unscented kalman filter algorithms for lithium liion batteries.

Identification, state estimation, and adaptive control of. Realization of highspeed adaptive quantum state estimation. Any reader with a solid foundation in quantum mechanics, linear algebra and calculus would be able to follow the book comfortably. 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. Spectral estimation, signal modeling, adaptive filtering and array processing authors. State tomography of qubit systems using linear regression. 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. First, an enhanced battery model is proposed to include the impacts due to different discharge rates and temperatures. A novel qgaukf algorithm for dynamic state estimation of. The necessary condition for a regular parametric model to have an adaptive estimator is that.

Diversity of quantum optimizations for training adaptive. In this paper, we consider a similar setting to the one in 4, 5, 6. A book containing tomography articles from groups around the world, including the second book chapter presented above. Kogon file specification extension pdf pages 814 size 11. Introduction to quantumstate estimation ebook by yong siah. A basic example of this is quantum state tomography, where a quantum state is learned from measurement. In particular, we consider adaptive quantumenhanced metrology, which performs sequential mea. The control of individual quantum systems promises a new technology for the 21st century quantum technology. Quantum tomography is a valuable tool in quantum information processing, being essential for characterisation of quantum states, gates, and measurement equipment. 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. Weidong liu is faculty member, department of mathematics and institute of natural sciences, shanghai jiao tong. 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. 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.

Pdf download adaptive atmospheric modeling free unquote. The retrospective cost state estimation rcse technique proposed in the present paper is based on an adaptive lter whose input is the innovations. Yu liu, yuzhang lin and junbo zhao, advanced grid operational tools based on state estimation, for book new technologies for power system. The oxford solid state basics steven simon optimal.

Adaptive quantization linear quantization instantaneous companding. Even though the performances of three kinds of quantum optimizations in fact are almost very closely one another, in. Improvement of estimation precision by adaptive design of. Quantum state tomography is the process by which a quantum state is reconstructed using measurements on an ensemble of identical quantum states. Performing quantum state estimation implies the reconstruction of the density. 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. Fisher information and asymptotic normality in system. In this paper, a novel quantum genetic algorithm qga is combined with unscented kalman filter ukf for dynamic state estimation of power systems. Bayesian models were used to optimize the data collection process by adaptive measurements in state reconstruction, 7,8,22. 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. Tw o imp orta n t typ es o f nor mal op erat ors are selfadjoint a a.

This paper further investigates the adaptive linear regression estimation alre. This requires that understanding of basic results on diverse topics, and derived from different disciplinary perspectives, is required for appreciating the overall picture. Quantum state tomography is a daunting challenge of experimental. 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. Parallel computing has been the enabling technology of highend machines for many years. The strong consistency and asymptotic efficiency of aqse have been mathematically proven a. The experiment in 8 relied on a single adaptive step. Quantumstate estimation is an important field in quantum information theory that deals with the characterization of states of affairs for quantum sources. In particular, its asymptotic theory has been developed during this period. In our raqst protocol, no prior assumption is made on the state to be reconstructed. Adaptive strategy shows decreased sn and time requirements for a given accuracy. This book is a comprehensive survey of most of the theoretical and experimental achievements in the field of quantum estimation of states and operations. Quantum state tomography and fidelity estimation via.

Adaptive quantum state estimation for dynamic quantum. Quantum states can be used to achieve powerlaw scaling better than 0. 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. 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. 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. Statistical and adaptive signal processing dimitris. The update criterion is based on averagevariance optimality aoptimality in classical statistics, and it has low computational cost for onequbit state estimation. Adaptive state of charge estimation for liion batteries. The retrospective cost state estimation rcse technique proposed in the present paper is based on an adaptive lter whose input is. 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. It is a technology that allows scientists to study and predict the performance of various productsimportant for research and development in the industrialized world. 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. Pdf experimental demonstration of adaptive quantum state.