Feedback-control of quantum systems using continuous state-estimation

We present a formulation of feedback in quantum systems in which the best estimates of the dynamical variables are obtained continuously from the measurement record, and fed back to control the system. We apply this method to the problem of cooling and confining a single quantum degree of freedom, and compare it to current schemes in which the measurement signal is fed back directly in the manner usually considered in existing treatments of quantum feedback. Direct feedback may be combined with feedback by estimation, and the resulting combination, performed on a linear system, is closely analogous to classical LQG control theory with residual feedback.Comment: 12 pages, multicol revtex, revised and extende

Comparing diagnoses from expert systems and human experts

This paper discusses a comparison of one heuristic and two Bayesian belief network based expert systems used to aid veterinarians in the process of differential diagnoses of equine diseases where coughing is the presenting clinical sign. Each implementation infers the likelihood of the presence of a number of diseases based on information on the presence or absence of certain clinical signs. The Bayesian belief network approaches are similar except that one includes the use of prior information in the form of disease prevalence estimates. Both are implemented using the Hugin software package. The three approaches were compared using test cases and the lists of resulting diagnoses were examined for agreement using a measure of concordance. The results indicated a difference between the heuristic approach which used the rule-based scoring mechanism and the Bayesian systems. There was, however, little difference between the diagnoses produced by the two Bayesian implementations, indicating that the incorporation of prevalence data makes little difference in diagnostic systems of this type. The findings were also compared with those of clinical experts. The analysis indicated that clinicians were not always in agreement. Moreover, using the same set of test cases the experts were more in agreement with the Bayesian approaches than with the heuristic approach. (C) 2002 Elsevier Science Ltd. All rights reserved.PT: J; NR: 17; TC: 3; J9: AGR SYST; PG: 12; GA: 688CJSource type: Electronic(1