Out-of-time-order correlations in many-body localized and thermal phases

We use the out-of-time-order (OTO) correlators to study the slow dynamics in the many-body localized (MBL) phase. We investigate OTO correlators in the effective ("l-bit") model of the MBL phase, and show that their amplitudes after disorder averaging approach their long-time limits as power-laws of time. This power-law dynamics is due to dephasing caused by interactions between the localized operators that fall off exponentially with distance. The long-time limits of the OTO correlators are determined by the overlaps of the local operators with the conserved l-bits. We demonstrate numerically our results in the effective model and three other more "realistic" spin chain models. Furthermore, we extend our calculations to the thermal phase and find that for a time-independent Hamiltonian, the OTO correlators also appear to vanish as a power law at long time, perhaps due to coupling to conserved densities. In contrast, we find that in the thermal phase of a Floquet spin model with no conserved densities the OTO correlator decays exponentially at long times.Comment: 24 pages, 12 figure

Age of Information in a Multisource Ber/Geo/1/1 Preemptive Queueing System

This work studies the information freshness of the vehicle-to-infrastructure status updating in Internet of vehicles, which is modeled as a multi-source Ber/Geo/1/1 preemptive queueing system with heterogeneous service time. We pay attention to both the distribution and average of AoI. To fully track the per-source AoI evolution, a Markov two-dimensional (2D) age process is introduced. The first element of the 2D age process stands for the instantaneous per-source AoI, while the second represents whether an update of the concerned source is being served and its current age. A complete framework and detailed analyses on the per-source AoI are presented based on the Markovity of the 2D age process. By studying the state transition probabilities, stationary equations, and stationary distribution of the 2D age process, analytical expressions of the probability mass function and average of per-source AoI are derived. Numerical results validate the accuracy of the theoretical analyses

The feasibility of Follow-the-Greens for 4-dimensional trajectory based airport ground movements

Safer and more efficient airport ground movements can be planned by routing and scheduling systems based on the 4-dimensional trajectory (4DT). In order to achieve the benefits envisioned in the planning stage, an effective taxiing guidance system is indispensable. The Follow-the-Greens (FtG) guidance concept provides an augmented means for 4DT based taxiing with pilot in the loop, which is expected to guide the piloted aircraft by dynamically adjusting the lit position of green ground navigation lamps according to the assigned 4DTs. This paper presents a simulation study to investigate the feasibility of FtG based on a control theoretic modeling of the taxiing system. The 4DT conformance errors with different navigation lamp control strategies are investigated. The key performance indices, including temporal constraint violation and fuel consumption, are analysed. The results demonstrate that it is feasible to follow conflict-free 4DTs through FtG if an appropriate lamp controller is available. The results also highlight the need to proactively handle the potential conformance errors in the routing and scheduling stage

A Robust CACC Scheme Against Cyberattacks Via Multiple Vehicle-to-Vehicle Networks

Cooperative Adaptive Cruise Control (CACC) is a vehicular technology that allows groups of vehicles on the highway to form in closely-coupled automated platoons to increase highway capacity and safety, and decrease fuel consumption and CO2 emissions. The underlying mechanism behind CACC is the use of Vehicle-to-Vehicle (V2V) wireless communication networks to transmit acceleration commands to adjacent vehicles in the platoon. However, the use of V2V networks leads to increased vulnerabilities against faults and cyberattacks at the communication channels. Communication networks serve as new access points for malicious agents trying to deteriorate the platooning performance or even cause crashes. Here, we address the problem of increasing robustness of CACC schemes against cyberattacks by the use of multiple V2V networks and a data fusion algorithm. The idea is to transmit acceleration commands multiple times through different communication networks (channels) to create redundancy at the receiver side. We exploit this redundancy to obtain attack-free estimates of acceleration commands. To accomplish this, we propose a data-fusion algorithm that takes data from all channels, returns an estimate of the true acceleration command, and isolates compromised channels. Note, however, that using estimated data for control introduces uncertainty into the loop and thus decreases performance. To minimize performance degradation, we propose a robust $H_{\infty}$ controller that reduces the joint effect of estimation errors and sensor/channel noise in the platooning performance (tracking performance and string stability). We present simulation results to illustrate the performance of our approach