Quantum state estimation

New algorithm for quantum state estimation based on the maximum likelihood estimation is proposed. Existing techniques for state reconstruction based on the inversion of measured data are shown to be overestimated since they do not guarantee the positive definiteness of the reconstructed density matrix.Comment: 4 pages, twocolumn Revte

State estimation of a solar direct steam generation mono-tube cavity receiver using a modified Extended Kalman Filtering scheme

State estimation plays a key role in the development of advanced control strategies for Concentrating Solar Thermal Power (CSP) systems, by providing an estimate of process variables that are otherwise infeasible to measure. The present study proposes a state estimation scheme for a once-through direct steam generation plant, the SG4 steam generation system at the Australian National University. The state estimation scheme is a modified Extended Kalman Filter that computes an estimate of the internal variables of the mono-tube cavity receiver in the SG4 system, from a dynamic non-linear model of the receiver. The proposed scheme augments the capabilities of a Continuous-Direct Extended Kalman Filter to deal with the switched nature of the receiver, in order to produce estimates during system start-up, cloud transients and operation of the plant. The estimation process runs at regular sample intervals and happens in two stages, a prediction and a correction stage. The prediction stage uses the receiver model to calculate the evolution of the system and the correction stage modifies the predicted estimate from measurements of the SG4 system. The resulting estimate is a set of internal variables describing the current state of the receiver, termed the state vector. This paper presents a description of the modified Extended Kalman Filter and an evaluation of the scheme using computer simulations and experimental runs in the SG4 system. Simulations and experimental results in this paper show that the filtering scheme improves a receiver state vector estimation purely based on the receiver model and provides estimates of a quality sufficient for closed loop control.This work has been supported by the Australian Renewable Energy Agency (ARENA)

Cross-Modal Health State Estimation

Individuals create and consume more diverse data about themselves today than any time in history. Sources of this data include wearable devices, images, social media, geospatial information and more. A tremendous opportunity rests within cross-modal data analysis that leverages existing domain knowledge methods to understand and guide human health. Especially in chronic diseases, current medical practice uses a combination of sparse hospital based biological metrics (blood tests, expensive imaging, etc.) to understand the evolving health status of an individual. Future health systems must integrate data created at the individual level to better understand health status perpetually, especially in a cybernetic framework. In this work we fuse multiple user created and open source data streams along with established biomedical domain knowledge to give two types of quantitative state estimates of cardiovascular health. First, we use wearable devices to calculate cardiorespiratory fitness (CRF), a known quantitative leading predictor of heart disease which is not routinely collected in clinical settings. Second, we estimate inherent genetic traits, living environmental risks, circadian rhythm, and biological metrics from a diverse dataset. Our experimental results on 24 subjects demonstrate how multi-modal data can provide personalized health insight. Understanding the dynamic nature of health status will pave the way for better health based recommendation engines, better clinical decision making and positive lifestyle changes.Comment: Accepted to ACM Multimedia 2018 Conference - Brave New Ideas, Seoul, Korea, ACM ISBN 978-1-4503-5665-7/18/1

State Estimation in the Cerebellum

An exciting hypothesis about the cerebellum is that its role is one of state estimation—a process that combines afferent copies of motor commands with afferent sensory signals to produce a representation of the current status of the peripheral motor system. Sensory inputs alone cannot provide a perfect state signal because of inevitable delays in their afferent pathways. We have recently reported the effects of transcranial magnetic stimulation (TMS) over the ipsilateral cerebellum as healthy subjects made rapid reaching movements towards visually defined targets (Miall et al. in PLoS Biology 5:2733–2744, 2007). Errors in the initial direction and in the final finger position of this reachto-target movement were consistent with the reaching movements being planned and initiated from an estimated hand position that was about 138 ms out of date. This interval is consistent with estimates of the delays in sensory motor pathways that would inform the central nervous system of the peripheral status. We now report new data using the same paradigm, testing the effects of varying the TMS stimulus train from one, two, or three pulses. We show that the errors in movement are relatively insensitive to the TMS pulse-train duration. The estimated time interval by which the hand position is mislocalized varied by only 12 ms as the TMS train duration increased by 100 ms. Thus, this interval is likely to reflect physiological processes within the cerebellum rather than the TMSstimulus duration. This new evidence supports our earlier claim that the cerebellum is responsible for predictively updating a central state estimate over an interval of about 120–140 ms. Dysfunction of the cerebellum, whether through disease or experimental procedures, leads to motor errors consistent with a loss of knowledge of the true state of the motor system

Probability-guaranteed set-membership state estimation for polynomially uncertain linear time-invariant systems

2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksConventional deterministic set-membership (SM) estimation is limited to unknown-but-bounded uncertainties. In order to exploit distributional information of probabilistic uncertainties, a probability-guaranteed SM state estimation approach is proposed for uncertain linear time-invariant systems. This approach takes into account polynomial dependence on probabilistic uncertain parameters as well as additive stochastic noises. The purpose is to compute, at each time instant, a bounded set that contains the actual state with a guaranteed probability. The proposed approach relies on the extended form of an observer representation over a sliding window. For the offline observer synthesis, a polynomial-chaos-based method is proposed to minimize the averaged H2 estimation performance with respect to probabilistic uncertain parameters. It explicitly accounts for the polynomial uncertainty structure, whilst most literature relies on conservative affine or polytopic overbounding. Online state estimation restructures the extended observer form, and constructs a Gaussian mixture model to approximate the state distribution. This enables computationally efficient ellipsoidal calculus to derive SM estimates with a predefined confidence level. The proposed approach preserves time invariance of the uncertain parameters and fully exploits the polynomial uncertainty structure, to achieve tighter SM bounds. This improvement is illustrated by a numerical example with a comparison to a deterministic zonotopic method.Peer ReviewedPostprint (author's final draft

Asymptotic quantum cloning is state estimation

The impossibility of perfect cloning and state estimation are two fundamental results in Quantum Mechanics. It has been conjectured that quantum cloning becomes equivalent to state estimation in the asymptotic regime where the number of clones tends to infinity. We prove this conjecture using two known results of Quantum Information Theory: the monogamy of quantum correlations and the properties of entanglement breaking channels.Comment: 4 pages, REVTE