Engineering Photon Delocalization in a Rabi Dimer with a Dissipative Bath

A Rabi dimer is used to model a recently reported circuit quantum electrodynamics system composed of two coupled transmission-line resonators with each coupled to one qubit. In this study, a phonon bath is adopted to mimic the multimode micromechanical resonators and is coupled to the qubits in the Rabi dimer. The dynamical behavior of the composite system is studied by the Dirac-Frenkel time-dependent variational principle combined with the multiple Davydov D$_{2}$ ans\"{a}tze. Initially all the photons are pumped into the left resonator, and the two qubits are in the down state coupled with the phonon vacuum. In the strong qubit-photon coupling regime, the photon dynamics can be engineered by tuning the qubit-bath coupling strength $\alpha$ and photon delocalization is achieved by increasing $\alpha$. In the absence of dissipation, photons are localized in the initial resonator. Nevertheless, with moderate qubit-bath coupling, photons are delocalized with quasiequilibration of the photon population in two resonators at long times. In this case, high frequency bath modes are activated by interacting with depolarized qubits. For strong dissipation, photon delocalization is achieved via frequent photon-hopping within two resonators and the qubits are suppressed in their initial down state.Comment: 11 pages, 11 figure

Dissipative dynamics in a tunable Rabi dimer with periodic harmonic driving

Recent progress on qubit manipulation allows application of periodic driving signals on qubits. In this study, a harmonic driving field is added to a Rabi dimer to engineer photon and qubit dynamics in a circuit quantum electrodynamics device. To model environmental effects, qubits in the Rabi dimer are coupled to a phonon bath with a sub-Ohmic spectral density. A non-perturbative treatment, the Dirac-Frenkel time-dependent variational principle together with the multiple Davydov D$_2$ {\it Ansatz} is employed to explore the dynamical behavior of the tunable Rabi dimer. In the absence of the phonon bath, the amplitude damping of the photon number oscillation is greatly suppressed by the driving field, and photons can be created thanks to resonances between the periodic driving field and the photon frequency. In the presence of the phonon bath, one still can change the photon numbers in two resonators, and indirectly alter the photon imbalance in the Rabi dimer by directly varying the driving signal in one qubit. It is shown that qubit states can be manipulated directly by the harmonic driving. The environment is found to strengthen the interqubit asymmetry induced by the external driving, opening up a new venue to engineer the qubit states

A Cost-effective Shuffling Method against DDoS Attacks using Moving Target Defense

Moving Target Defense (MTD) has emerged as a newcomer into the asymmetric field of attack and defense, and shuffling-based MTD has been regarded as one of the most effective ways to mitigate DDoS attacks. However, previous work does not acknowledge that frequent shuffles would significantly intensify the overhead. MTD requires a quantitative measure to compare the cost and effectiveness of available adaptations and explore the best trade-off between them. In this paper, therefore, we propose a new cost-effective shuffling method against DDoS attacks using MTD. By exploiting Multi-Objective Markov Decision Processes to model the interaction between the attacker and the defender, and designing a cost-effective shuffling algorithm, we study the best trade-off between the effectiveness and cost of shuffling in a given shuffling scenario. Finally, simulation and experimentation on an experimental software defined network (SDN) indicate that our approach imposes an acceptable shuffling overload and is effective in mitigating DDoS attacks

Contextual Attention Recurrent Architecture for Context-aware Venue Recommendation

Venue recommendation systems aim to effectively rank a list of interesting venues users should visit based on their historical feedback (e.g. checkins). Such systems are increasingly deployed by Location-based Social Networks (LBSNs) such as Foursquare and Yelp to enhance their usefulness to users. Recently, various RNN architectures have been proposed to incorporate contextual information associated with the users' sequence of checkins (e.g. time of the day, location of venues) to effectively capture the users' dynamic preferences. However, these architectures assume that different types of contexts have an identical impact on the users' preferences, which may not hold in practice. For example, an ordinary context such as the time of the day reflects the user's current contextual preferences, whereas a transition context - such as a time interval from their last visited venue - indicates a transition effect from past behaviour to future behaviour. To address these challenges, we propose a novel Contextual Attention Recurrent Architecture (CARA) that leverages both sequences of feedback and contextual information associated with the sequences to capture the users' dynamic preferences. Our proposed recurrent architecture consists of two types of gating mechanisms, namely 1) a contextual attention gate that controls the influence of the ordinary context on the users' contextual preferences and 2) a time- and geo-based gate that controls the influence of the hidden state from the previous checkin based on the transition context. Thorough experiments on three large checkin and rating datasets from commercial LBSNs demonstrate the effectiveness of our proposed CARA architecture by significantly outperforming many state-of-the-art RNN architectures and factorisation approaches

Variation and trends of landscape dynamics, land surface phenology and net primary production of the Appalachian Mountains

The gradients of elevations and latitudes in the Appalachian Mountains provide a unique regional perspective on landscape variations in the eastern United States and southeastern Canada. We reveal patterns and trends of landscape dynamics, land surface phenology, and ecosystem production along the Appalachian Mountains using time series data from Global Inventory Modeling and Mapping Studies and Advanced Very High Resolution Radiometer Global Production Efficiency Model datasets. We analyze the spatial and temporal patterns of the normalized difference vegetation index (NDVI), length of growing season (LOS), and net primary production (NPP) of selected ecoregions along the Appalachian Mountains regions. We compare the results in different spatial contexts, including North America and the Appalachian Trail corridor area. To reveal latitudinal variations, we analyze data and compare the results between the 30°-to-40°N and the 40°-to-50°N latitudes. The result reveal significant decreases in annual peak NDVI in the Appalachian Mountains regions. The trend for the Appalachian Mountains regions was a −0.0018 (R2=0.55, P\u3c0.0001) NDVI unit decrease per year during 25 years from 1982 to 2006. The LOS was prolonged by 0.3  days per year−1 during the 25-year percent. The NPP increased by 2.68  g Cm−2 yr−2 from 1981 to 2000

Error Analysis and Error Allocation for Turntable Systems Used in GyroWheel Calibration Tests

Calibration tests are of great importance to ensure rate-sensing accuracy of GyroWheel, an innovative attitude determination and control device. In the process of calibration tests, turntable errors are inevitable, which hinder the calibration accuracy and rate-sensing capability. Hence, error analysis for GyroWheel calibration tests is conducted, and the relationship between the calibration accuracy and the orientation error is established based on analytical derivation and numerical simulations. Subsequently, an error model of the turntable system is derived using rigid body kinematics, by which the relationship between the orientation error and turntable errors is described. According to sensitivity analysis and manufacturing capability, an error allocation method is proposed to determine the accuracy requirement of the test turntable, and the effectiveness of the proposed method is verified by repeated simulation tests. Based on the presented analysis and proposed method in this paper, the effects of various turntable errors on the calibration accuracy can be obtained quantitatively, and a theoretical basis for the determination of the turntable accuracy is provided, which are of great significance to guide the calibration tests and improve the calibration accuracy of GyroWheel

Sub-structure characteristic mode analysis of microstrip antennas using a global multi-trace formulation

A characteristic mode (CM) method that relies on a global multi-trace formulation (MTF) of surface integral equations is proposed to compute the modes and the resonance frequencies of microstrip patch antennas with finite dielectric substrates and ground planes. Compared to the coupled formulation of electric field and Poggio-Miller-Chang-Harrington-Wu-Tsai integral equations, global MTF allows for more direct implementation of a sub-structure CM method. This is achieved by representing the coupling of the electromagnetic fields on the substrate and ground plane in the form of a numerical Green function matrix, which yields a more compact generalized eigenvalue equation. The resulting sub-structure CM method avoids the cumbersome computation of the multilayered medium Green function (unlike the CM methods that rely on mixed-potential integral equations) and the volumetric discretization of the substrate (unlike the CM methods that rely on volume-surface integral equations), and numerical results show that it is a reliable and accurate approach to predicting the modal behavior of electromagnetic fields on practical microstrip antennas

X-ray emission for 424 MeV/u C ions impacting on selected targets

In inertial Confinement Fusion (ICF), X-ray radiation drives the implosion requiring not only sufficient conversion efficiency of the drive energy to the X-ray but also the highly spatial symmetry..