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Bounding overwatch
About: Bounding overwatch is a research topic. Over the lifetime, 966 publications have been published within this topic receiving 15156 citations.
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01 Jan 1989
49 citations
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TL;DR: A variational quantum algorithm called Variational Quantum Fisher Information Estimation (VQFIE) is presented, which estimates lower and upper bounds on the QFI, based on bounding the fidelity, and outputs a range in which the actual QFI lies.
Abstract: The Quantum Fisher information (QFI) quantifies the ultimate precision of estimating a parameter from a quantum state, and can be regarded as a reliability measure of a quantum system as a quantum sensor. However, estimation of the QFI for a mixed state is in general a computationally demanding task. In this work we present a variational quantum algorithm called Variational Quantum Fisher Information Estimation (VQFIE) to address this task. By estimating lower and upper bounds on the QFI, based on bounding the fidelity, VQFIE outputs a range in which the actual QFI lies. This result can then be used to variationally prepare the state that maximizes the QFI, for the application of quantum sensing. In contrast to previous approaches, VQFIE does not require knowledge of the explicit form of the sensor dynamics. We simulate the algorithm for a magnetometry setup and demonstrate the tightening of our bounds as the state purity increases. For this example, we compare our bounds to literature bounds and show that our bounds are tighter.
49 citations
TL;DR: In this paper, the computation of parameter bounds for models of linear, time-varying systems is considered, and three methods are discussed, all with counterparts in conventional least squares or statistical parameter estimation: fixed-memory bounding, scalar bound inflation and bound incrementing.
49 citations
TL;DR: A bounding algorithm for computing two-terminal reliability based on decomposition technique originally used in computing multi-state reliability is considered, which can sequentially improve the quality of approximation according to a predetermined value @e.
Abstract: Two-terminal reliability, which is defined as the probability that there exists at least one path from source node to sink node, is an important performance measure in network system. However, it is well known that the complexity of exact two-terminal reliability evaluation is NP-hard. This paper considers a bounding algorithm for computing two-terminal reliability based on decomposition technique originally used in computing multi-state reliability. Compared with traditional bounding algorithms, the proposed algorithm requires neither all MPs/MCs to be enumerated in advance, nor all arcs to have the same state probabilities. It can sequentially improve the quality of approximation according to a predetermined value @e. Especially, it may be an exact algorithm if it runs into completion. An example shows that the proposed algorithm is practical and effective.
48 citations
TL;DR: In this paper, a new property of Markov chains, called variance bounding, was introduced, which is weaker than geometric ergodicity and is equivalent to the existence of usual central limit theorems for all L 2 functionals.
Abstract: We introduce a new property of Markov chains, called variance bounding. We prove that, for reversible chains at least, variance bounding is weaker than, but closely related to, geometric ergodicity. Furthermore, vari- ance bounding is equivalent to the existence of usual central limit theorems for all L 2 functionals. Also, variance bounding (unlike geometric ergodicity) is preserved under the Peskun order. We close with some applications to Metropolis-Hastings algorithms.
47 citations