Feedback Protocol Research Articles

Prolonging a discrete time crystal by quantum-classical feedback

Nonequilibrium phases of quantum matter featuring time crystalline eigenstate order have been realized recently on noisy intermediate-scale quantum (NISQ) devices. While ideal quantum time crystals exhibit collective subharmonic oscillations and spatiotemporal long-range order persisting for infinite times, the decoherence time of current NISQ devices sets a natural limit to the survival of these phases, restricting their observation to a shallow quantum circuit. Here we propose a time-periodic scheme that leverages quantum-classical feedback protocols in subregions of the system to enhance a time crystal signal significantly exceeding the decoherence time of the device. As a case of study, we demonstrate the survival of the many-body localized discrete time crystal phase in the one-dimensional periodically kicked Ising model, accounting for decoherence of the system with an environment. Based on classical simulation of quantum circuit realizations we find that this approach is suitable for implementation on existing quantum hardware and presents a prospective path to simulate complex quantum many-body dynamics that transcend the low depth limit of current digital quantum computers. Published by the American Physical Society 2024

Distributed Minimum-Energy Containment Control of Continuous-Time Multi-Agent Systems by Inverse Optimal Control

Dear Editor, This letter focuses on the distributed optimal containment control of continuous-time multi-agent systems (CTMASs) with respect to the minimum-energy performance index over fixed topology. To achieve this, we firstly investigate the optimal containment control problem using the inverse optimal control method, where all states of followers asymptotically converge to the convex hull spanned by the leaders while some quadratic performance indexes get minimized. A sufficient condition for existence of the distributed optimal containment control protocol is derived. By introducing the parametric algebraic Riccati equation (PARE), it is strictly proved that the global performance index can be used to approximate the standard minimum-energy performance index as the parameters tends to infinity. In consequence, the standard minimum-energy cooperative containment control can be solved by local steady state feedback protocols. Finally, numerical examples are given to demonstrate the effectiveness of theoretical results.

Steady-state entanglement production in a quantum thermal machine with continuous feedback control

Quantum thermal machines can generate steady-state entanglement by harvesting spontaneous interactions with local environments. However, using minimal resources and control, the entanglement is typically weak. Here, we study entanglement generation in a two-qubit quantum thermal machine in the presence of a continuous feedback protocol. Each qubit is measured continuously and the outcomes are used for real-time feedback to control the local system-environment interactions. We show that there exists an ideal operation regime where the quality of entanglement is significantly improved, to the extent that it can violate standard Bell inequalities and uphold quantum teleportation. In agreement with (Khandelwal et al 2020 New J. Phys. 22 073039), we also find, for ideal operation, that the heat current across the system is proportional to the entanglement concurrence. Finally, we investigate the robustness of entanglement production when the machine operates away from the ideal conditions.

Observer-based positive edge consensus of multi-agent systems with directed graphs

This paper concentrates on the positive edge consensus in directed networks with spanning trees using output feedback protocols. First, a novel positive system observer is established, which introduces a parameter to enhance the design freedom of the observer. Furthermore, sufficient conditions are proposed, which are based solely on the network’s edge count. Specifically, improved consensus and non-negative conditions are obtained by optimizing the constraints on the eigenvalue information. Subsequently, based on positive edge-consensus design conditions, a programming algorithm is developed. Finally, the effectiveness of the proposed control protocol is verified utilizing numerical simulations.

Silicon spin qubit noise characterization using real-time feedback protocols and wavelet analysis

Recently, several groups have demonstrated two-qubit gate fidelities in semiconductor spin qubit systems above 99%. Achieving this regime of fault-tolerant compatible high fidelities is nontrivial and requires exquisite stability and precise control over the different qubit parameters over an extended period of time. This motivates the search for the efficient calibration of qubit control parameters against different sources of micro- and macroscopic noise and methods for noise analysis. Here, we present several single- and two-qubit parameter feedback protocols, optimized for and implemented in the state-of-the-art fast field-programmable gate array hardware. Furthermore, we present a wavelet-based analysis on feedback data collected over a ∼9 h time frame to gain insight into the different sources of noise in the system. Scalable feedback is an outstanding challenge and the presented implementation and analysis gives insight into the benefits and drawbacks of qubit parameter feedback, as feedback related overhead increases. This work demonstrates a pathway toward robust qubit parameter feedback and systematic noise analysis, crucial for mitigation strategies toward systematic high-fidelity qubit operation compatible with quantum error correction protocols.

Simulation-Based Training in Obstetric Anesthesia: An Update

(Int J Obstet Anesth. 2023:54:103643) Anesthesiologists play a very important role in the care of pregnant patients. Simulation training is a tool that has been integrated into anesthesiology training to teach hands-on skills and teamwork to both incoming and experienced clinicians. The criteria for properly equipped simulations include clearly stated procedures and expectations, a curriculum whose goal is to meet said expectations, clearly stated simulation modalities, proper instructors, and proper feedback protocols. This study aimed to analyze the use of simulations for obstetric anesthesia.

Output consensus robustness and performance of first‐order agents

AbstractIn this article, we study consensus robustness and performance problems for continuous‐time multi‐agent systems. We consider first‐order unstable agents coordinated by an output feedback protocol over a network subject to an unknown, uncertain constant delay. Our objectives are twofold. First, we seek to determine the largest range of delay permissible so that the agents may achieve robustly consensus despite variation of the delay length, herein referred to as the delay consensus margin. Second, we attempt to determine consensus error performance quantified under an norm criterion, which measures the disruptive effect of random nodal noises on consensus. We consider both undirected and directed graphs. For undirected graphs, we obtain analytical results for the delay consensus margin and the consensus error performance, while for directed graphs, we develop computational results and analytical bounds. The results provide conceptual insights and exhibit how the agents' unstable pole, nonminimum phase zero, as well as the network topology and network delay may limit fundamentally the consensus robustness and performance of first‐order agents.

Stabilization and Synchronization of Neural Networks via Impulsive Adaptive Control.

This article addresses the stabilization and synchronization problems of coupled neural networks (NNs) via an impulsive adaptive control (IAC) strategy. Unlike the traditional fixed-gain-based impulsive methods, a novel discrete-time-based adaptive updating law for the impulsive gain is designed to maintain the stabilization and synchronization performance of the coupled NNs, where the adaptive generator only intermittently updates its data at the impulsive instants. Several stabilization and synchronization criteria for the coupled NNs are established based on the impulsive adaptive feedback protocols. Additionally, the corresponding convergence analysis are also provided. Finally, the effectiveness of the obtained theoretical results is illustrated using two comparison simulation examples.

LATENT VARIABLE MODELING FOR BIOLOGICALLY INFORMED PROGNOSIS IN STUDIES OF PHYSICAL RESILIENCE

Abstract Physical resilience – rebound in relevant functioning and biomarkers following a health stressor – is hypothesized to be rooted in the level of fitness of stress-response physiology defining one’s “physiological resilience capacity” (PRC). This physiology forms a dynamical system comprising specific modules (the individual stress response systems and their underlying components) and their dynamic interactions with each other via feedback and other protocols. Such a system can be modeled using differential equations whose parameters may then define the PRC. We do not yet know how to measure these parameters directly, however. Rather, they are conceptually defined “constructs” which must be inferred using indirect measures—ideally, stimulus response data probing multiple aspects of the relevant physiology. Latent variable models are ideally suited to this setting. Two challenges for their application in studies of resilience are presented: (1) Integrating specific scientific knowledge on the dynamical systems in modeling the co-distribution of the indirect measures. (2) Synergizing such models’ advantages for construct measurement with advantages of machine learning approaches to optimize accuracy for predicting resilient outcomes by inferred PRC. Challenges and their proposed solutions are illustrated using multifaceted stimulus response data being collected in an ongoing investigation on the physiological basis of resilience to clinical stressors in older adults, the Study of Physical Resilience in agING. The work aims to produce physiologically rooted measures providing effective risk predictors for older adults facing impending stressors as well as intervention candidates by which to promote PRC in the longer term.

Nash Equilibrium Seeking for Multicluster Games of Multiple Nonidentical Euler–Lagrange Systems

The problem of seeking Nash equilibrium in multicluster games is studied. Different from the existing multi-cluster game studies, the participants considered in this paper have Euler-Lagrange (EL) dynamics and cannot directly obtain the information of non-neighbor participants. Agents can only communicate through directed communication graphs. In addition, there are coupling constraints between agent decisions in the same cluster. Under the widely used assumptions, two distributed algorithms are proposed to solve the Nash equilibrium (NE) of the multi-cluster game based on gradient descent, state feedback, and consensus protocol. The convergence of the two algorithms is analyzed by singular perturbation analysis and variational analysis. The theoretical results show that the first algorithm achieves exponential convergence when the parameters are certain, while the other algorithm also achieves global asymptotic convergence when the parameters are uncertain. Finally, the effectiveness of the search strategy is verified by numerical examples.

Consensus of MASs With Input and Communication Delays by Predictor-Based Protocol.

In this article, the consensus problem of multiagent systems (MASs) affected by input and communication delays is investigated. A predictor-based state feedback protocol is used to reach the consensus of linear MASs by delay compensation. In order to analyze the maximum delay under the predictor-based protocol, the overall MASs are equivalent to the feedback interconnection system, including a linear time-invariant system and a time-delay operator, in view of the characteristic of the Laplacian matrix. Then, the maximum delay corresponding to the predictor-based protocol is evaluated by using the small gain theorem (SGT). Finally, two numerical examples are given to verify the effectiveness of the obtained consensus condition.

Attack-free protocols design for leader-following consensus of discrete-time multi-agent systems with multiple input delays

The consensus problem for leader-following multi-agent systems (MASs) characterised by discrete-time multiple input delays linear systems with directed communication topologies is investigated. Under reasonable assumptions, full-order observer-based output feedback protocols are first established by using the relative outputs and inputs of neighbouring agents. In order to overcome the impact of potential network attacks, we truncate the relative inputs of the proposed protocols, namely the exchange of communication information between neighbouring agents is forbidden, so that the closed-loop leader-following MAS is inherently immune to being attacked and achieves consensus. Additionally, the improved attack-free protocols not only allow arbitrarily large yet bounded delays, but also only relative output measurement can be available, which reduces the communication burden and thus are easy to implement in practice. A numerical example is worked out to illustrate the effectiveness of the proposed approach.

Engagement with written corrective feedback: Examination of feedback types and think-aloud protocol as pedagogical interventions

This study examined the combined effects of written corrective feedback (WCF) and think-aloud protocols (TAPs) as two types of pedagogical intervention for improving the revision quality of second language (L2) writing. With a quasi-experimental design, it explored whether TAPs trigger deeper processing of WCF under two WCF-type conditions: direct or indirect WCF. Participants were 80 high-intermediate learners of English as a second language (ESL) at a US university who were divided into (1) direct WCF+TAPs; (2) direct WCF-only; (3) indirect WCF+TAPs; and (4) indirect WCF-only. The impacts of the interventions were gauged by changes in seven subsystems of complexity–accuracy–lexis (CAL) between the first and final drafts of narrative essays. Results showed differential impacts of the four conditions depending on the linguistic dimensions, including some negative impacts of TAPs. Participants’ comments during TAP sessions were used to triangulate the interventions’ effects. We conclude that WCF and TAPs promoted different types of processing; while WCF contributed to the potential restructuring of learners’ interlanguage systems, TAPs triggered learners’ higher-order thinking and served as a self-reflection tool to make strategic decisions in revising the text.

Dynamics of a colloidal particle driven by continuous time-delayed feedback.

We perform feedback experiments and simulations in which a colloidal dumbbell particle, acting as a particle on a ring, is followed by a repulsive optical trap controlled by a continuous-time-delayed feedback protocol. The dynamics are described by a persistent random walk similarly to that of an active Brownian particle, with a transition from predominantly diffusive to driven behavior at a critical delay time. We model the dynamics in the short and long delay regimes using stochastic delay differential equationsand derive a condition for stable driven motion. We study the stochastic thermodynamic properties of the system, finding that the maximum work done by the trap coincides with a local minimum in the mutual information between the trap and the particle position at the onset of stable driven dynamics.

Fully distributed leader–follower consensus for multi-agent systems based on reduced-order adaptive feedback protocol

This paper addresses the leader–follower consensus problem of linear multi-agent systems by designing reduced-order adaptive output feedback protocol. Using relative output information among neighboring agents, node-based adaptive output feedback control protocol and edge-based adaptive output feedback control protocol are presented, respectively. For both cases, based on Lyapunov analysis and algebraic Riccati equation design, some sufficient conditions are given to achieve leader–follower consensus by applying the proposed adaptive output feedback protocols. Finally, some simulation examples are given to illustrate the validity of the theoretical results.

The impact of augmented feedback (and technology) on learning and teaching cricket skill: A systematic review with meta-analysis.

Augmented feedback, including that provided using technology, can elicit multifaceted benefits on perceptual-motor learning and performance of sporting skills. However, current considerations of the applied value in supporting learning and teaching cricket skill is limited. This systematic review with meta-analysis aimed to understand the role and effectiveness of feedback-involved interventions on skill-based performance outcomes in cricket-related research. Six electronic databases were searched (SPORTDiscus, CINAHL, MEDLINE, Scopus, Web of Science and PsycINFO). Of 8,262 records identified, 11 studies met inclusion criteria; five of which were included in meta-analyses. Given no studies with an isolated feedback intervention-arm were identified, the two meta-analyses explored anticipation-based studies consisting of an intervention that included augmented feedback; positioned with respect to the key motor skill concepts of perception (anticipation accuracy) and action (performance success). Despite results highlighting improved performance outcomes for the feedback-involved intervention groups, with a large effect size for improved anticipation accuracy (Hedge's g = 1.21, 95% CIs [-0.37, 2.78]) and a medium effect size for overall performance success (Hedge's g = 0.55, 95% CIs [-0.39, 1.50]), results were not statistically significant and should be interpreted with caution given the wide confidence intervals. Considering the small number of studies available, in addition to the lack of isolated feedback protocols, further research is warranted to thoroughly explore the impact of augmented feedback on skill-based performance in cricket. Beyond the meta-analyses, the review also explored all included studies from an ecological dynamics perspective; presenting future avenues of research framed around evaluating the applied value of using augmented feedback (mediated with or without technology) for learning and teaching skill in cricket. Trial registration The protocol was preregistered with Open Science Framework (osf.io/384pd).

State initialization of a hot spin qubit in a double quantum dot by measurement-based quantum feedback control

A measurement-based quantum feedback protocol is developed for spin-state initialization in a gate-defined double quantum dot spin qubit coupled to a superconducting cavity. The protocol improves qubit state initialization as it is able to robustly prepare the spin in shorter time and reach a higher fidelity, which can be preset. Being able to preset the fidelity aimed at is a highly desired feature enabling qubit initialization to be more deterministic. The protocol developed herein is also effective at high temperatures, which is critical for the current efforts toward scaling up the number of qubits in quantum computers.

Post-operative delirium in the patient with hip fracture: The journey from hospital arrival to discharge.

Delirium- an acute disorder of attention and cognition- is the commonest complication following hip fracture. Patients with hip fracture are particularly vulnerable to delirium, and many of the lessons from the care of the patient with hip fracture will extend to other surgical cohorts. Prevention and management of delirium for patients presenting with hip fracture, extending along a continuum from arrival through to the post-operative setting. Best practice guidelines emphasize multidisciplinary care including management by an orthogeriatric service, regular delirium screening, and multimodal interventions. The evidence base for prevention is strongest in terms of multifaceted interventions, while once delirium has set in, early recognition and identification of the cause are key. Integration of effective strategies is often suboptimal, and may be supported by approaches such as interactive teaching methodologies, routine feedback, and clear protocol dissemination. Partnering with patients and carers will support person centered care, improve patient experiences, and may improve outcomes. Ongoing work needs to focus on implementing recognized best practice, in order to minimize the health, social and economic costs of delirium.

Driven particle in a one-dimensional periodic potential with feedback control: Efficiency and power optimization.

A Brownian particle moving in a staircaselike potential with feedback control offers a way to implement Maxwell's demon. An experimental demonstration of such a system using sinusoidal periodic potential carried out by Toyabe etal. [Nat. Phys. 6, 988 (2010)1745-247310.1038/nphys1821] has shown that information about the particle's position can be converted to useful work. In this paper, we carry out a numerical study of a similar system using Brownian dynamics simulation. A Brownian particle moving in a periodic potential under the action of a constant driving force is made to move against the drive by measuring the position of the particle and effecting feedback control by altering potential. The work is extracted during the potential change and from the movement of the particle against the external drive. These work extractions come at the cost of information gathered during the measurement. Efficiency and work extracted per cycle of this information engine are optimized by varying control parameters as well as feedback protocols. Both these quantities are found to crucially depend on the amplitude of the periodic potential as well as the width of the region over which the particle is searched for during the measurement phase. For the case when potential flip (i.e., changing the phase of the potential by 180^{∘}) is used as the feedback mechanism, we argue that the square potential offers a more efficient information-to-work conversion. The control over the numerical parameters and averaging over large number of trial runs allow one to study the nonequilibrium work relations with feedback for this process with precision. It is seen that the generalized integral fluctuation theorem for error-free measurements holds to within the accuracy of the simulation.

Fully distributed event-triggered output feedback control for linear multi-agent systems with a derivable leader under directed graphs

This article studies the design method of fully distributed event-triggered output feedback protocol for linear multi-agent systems with a derivable leader under directed graphs. The research on such problems in the existing reference needs complete state feedback and the state variable of the adaptive law used in the literature controller is monotonic and non decreasing, which may make the control input exceed the actual saturation value, thus affecting the practical application. How to design a completely distributed event-triggered adaptive output feedback protocols for multi-agent systems with a derivable leader on directed graphs is an open issue. In order to overcome the difficulty of designing the controller without complete state information, we design the event-triggered output feedback protocol, and with the help of σ-modification techniques, ensure the boundedness of the adaptive law in proposed protocol. The conditions to ensure the realization of the leader–follower consensus and exclude Zeno behavior are given. Furthermore, the control protocol is fully distributed and uses neighbor information only when the event trigger conditions are satisfied. Finally, the availability of the proposed protocol is illustrated by simulation examples.