Survey of control performance in quantum information processing

There is a rich variety of physics underlying the fundamental gating operations for quantum information processing (QIP). A key aspect of a QIP system is how noise may enter during quantum operations and how suppressing or correcting its effects can best be addressed. Quantum control techniques have been developed to specifically address this effort, although a detailed classification of the compatibility of controls schemes with noise sources found in common quantum systems has not yet been performed. This work numerically examines the performance of modern control methods for suppressing decoherence in the presence of noise forms found in viable quantum systems. The noise-averaged process matrix for controlled one-qubit and two-qubit operations are calculated across noise found in systems driven by Markovian open quantum dynamics. Rather than aiming to describe the absolute best control scheme for a given physical circumstance, this work serves instead to classify quantum control behavior across a large class of noise forms so that opportunities for improving QIP performance may be identified.     

Quantum state transfer between an optomechanical cavity and a diamond nuclear spin ensemble

We explore an efficient scheme for transferring quantum state between an optomechanical cavity and nuclear spins of nitrogen-vacancy centers in diamond, where quantum information can be efficiently stored (retrieved) into (from) the nuclear spin ensemble assisted by a mechanical resonator in a dispersive regime. Our scheme works for a broad range of cavity frequencies and might have potential applications in employing the nuclear spin ensemble as a memory in quantum information processing. The feasibility of our protocol is analyzed using currently available parameters.     

A modular designed bolt tightening shaft based on adaptive fuzzy backstepping control

This paper presents a modular designed autonomous bolt tightening shaft system with an adaptive fuzzy backstepping control approach developed for it. The bolt tightening shaft is designed for the autonomous bolt tightening operation, which has huge potential for industry application. Due to the inherent nonlinear and uncertain properties, the bolt tightening shaft and the bolt tightening process are mathematically modeled as an uncertain strict feedback system. With the adaptive backstepping and approximation property of fuzzy logic system, the controller is recursively designed. Based on the Lyapunov stability theorem, all signals in the closed-loop system are proved to be uniformly ultimately bounded and the torque tracking error exponentially converges to a small residue. And the effectiveness and performance of the proposed autonomous system are verified by the simulation and experiment results on the bolt tightening shaft system.     

Positive <Emphasis Type="Italic">L</Emphasis><Subscript>1</Subscript>-gain filter design for positive continuous-time Markovian jump systems with partly known transition rates

The paper is concerned with the problem of positive L ₁-gain filter design for positive continuous-time Markovian jump systems with partly known transition rates. Our aim is to design a positive full-order filter such that the corresponding filtering error system is positive and stochastically stable with L ₁-gain performance. By applying a linear co-positive Lyapunov function and free-connection weighting vectors, the desired positive L ₁-gain filter is provided. The obtained theoretical results are demonstrated by numerical examples.     

Practical chosen-ciphertext secure Hierarchical Identity-Based Broadcast Encryption

We focus on practical Hierarchical Identity-Based Broadcast Encryption (HIBBE) with semantic security against adaptively chosen-ciphertext attacks (CCA2) in the standard model. We achieve this goal in two steps. First, we propose a new HIBBE scheme that is secure against chosen-plaintext attacks (CPA). Compared with the existing HIBBE scheme that is built from composite-order bilinear groups, our construction is based on prime-order bilinear groups. The much better efficiency of group operations in prime-order bilinear groups makes our proposed HIBBE scheme more practical. Then, we convert it into a CCA2-secure scheme at the cost of a one-time signature. Instead of extending one user hierarchy in the Canetti–Halevi–Katz approach from CPA-secure (\(l+1\))-Hierarchical Identity-Based Encryption [(\(l+1\))-HIBE] to CCA2-secure \(l\)-HIBE, our construction merely adds one on-the-fly dummy user in the basic scheme. We formally prove the security of these two schemes in the standard model. Comprehensive theoretical analyses and experimental results demonstrate that the proposed HIBBE schemes achieve desirable performance.     

Virtual-Point-Based asymptotic tracking control of 4WS vehicles

This paper studies the lateral and longitudinal path tracking control of four-wheel steering vehicles. By the introduction of virtual points, a robust and adaptive path tracking control strategy is proposed to simultaneously counteract modeling uncertainties, unexpected disturbances, and coupling effects. An adaptive model-based feedforward adaptive term and the robust integral of the sign of the error (RISE) feedback term can be used to yield an asymptotic tracking result, which improve the tracking performance and reduce the control effort. The stability of closed-loop system is analyzed using a Lyapunov-based method. Simulation results are provided to demonstrate the performance of the proposed controller under different driving conditions.     

Data Fusion-based resilient control system under DoS attacks: A game theoretic approach

In this paper, the resilient control under the Denial-of-Service (DoS) attack is rebuilt within the framework of Joint Directors of Laboratories (JDL) data fusion model. The JDL data fusion process is characterized by the so-called Game-in-Game approach, where decisions are made at different layers. The interactions between different JDL levels are considered which take the form of Packet Delivery Rate of the communication channel. Some criterions to judge whether the cyber defense system is able to protect the underlying control system is provided. Finally, a numerical example is proposed to verify the validity of the proposed method.     

Interval or moments: which carry more information?

In many practical situations, we do not have enough observations to uniquely determine the corresponding probability distribution, we only have enough observations to estimate two parameters of this distribution. In such cases, the traditional statistical approach is to estimate the mean and the standard deviation. Alternatively, we can estimate the two bounds that form the range of the corresponding variable and thus, generate an interval. Which of these two approaches should we select? A natural idea is to select the most informative approach, i.e., an approach in which we need the smallest amount of additional information (in Shannon’s sense) to obtain the full information about the situation. In this paper, we follow this idea and come up with the following conclusion: in practical situations in which a 95 % confidence level is sufficient, interval bounds are more informative; however, in situations in which we need higher confidence, the moments approach is more informative.     

Radiometric normalization and image mosaic generation of ASTER thermal infrared data: An application to extensive sand sheets and dune fields

Data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) have a significant advantage over previous datasets because of the combination of high spatial resolution (15-90 m) and enhanced multispectral capabilities, particularly in the thermal infrared (TIR) atmospheric window (8-12 μm) of the Earth where common silicate minerals are more easily identified. However, the 60 km swath width of ASTER can limit the effectiveness of accurately tracing large-scale features, such as eolian sediment transport pathways, over long distances. The primary goal of this paper is to describe a method for generating a seamless and radiometrically accurate ASTER TIR mosaic of atmospherically corrected radiance and from that, extract surface emissivity for arid lands, specifically, sand seas. The Gran Desierto in northern Sonora, Mexico was used as a test location for the radiometric normalization technique because of past remote sensing studies of the region, its compositional diversity, and its size. A linear approach was taken to transform adjacent image swaths into a direct linear relationship between image acquisition dates. Pseudo-invariant features (PIFs) were selected using a threshold of correlation between radiance values, and change-pixels were excluded from the linear regression used to determine correction factors. The degree of spectral correlation between overlapping pixels is directly related to the amount of surface change over time; therefore, the gain and offsets between scenes were based only on regions of high spectral correlation. The result was a series of radiometrically normalized radiance-at-surface images that were combined with a minimum of image edge seams present. These edges were subsequently blended to create the final mosaic. The advantages of this approach for TIR radiance (as opposed to emissivity) data include the ability to: (1) analyze data acquired on different dates (with potentially very different surface temperatures) as one seamless compositional dataset; (2) perform decorrelation stretches (DCS) on the entire dataset in order to identify and discriminate compositional units; and (3) separate brightness temperature from surface emissivity for quantitative compositional analysis of the surface, reducing seam-line error in the emissivity mosaic. The approach presented here is valid for any ASTER-related study of large geographic regions where numerous images spanning different temporal and atmospheric conditions are encountered.