Quantum state transmission in a cavity array via two-photon exchange

The dynamical behavior of a coupled cavity array is investigated when each cavity contains a three-level atom. For the uniform and staggered intercavity hopping, the whole system Hamiltonian can be analytically diagonalized in the subspace of single-atom excitation. The quantum state transfer along the cavities is analyzed in detail for distinct regimes of parameters, and some interesting phenomena including binary transmission, selective localization of the excitation population are revealed. We demonstrate that the uniform coupling is more suitable for the quantum state transfer. It is shown that the initial state of polariton located in the first cavity is crucial to the transmission fidelity, and the local entanglement depresses the state transfer probability. Exploiting the metastable state, the distance of the quantum state transfer can be much longer than that of Jaynes-Cummings-Hubbard model. A higher transmission probability and longer distance can be achieved by employing a class of initial encodings and final decodings.Comment: 8 pages, 7 figures. to appear in Phys. Rev.

The research infrastructure of Chinese foundations, a database for Chinese civil society studies

This paper provides technical details and user guidance on the Research Infrastructure of Chinese Foundations (RICF), a database of Chinese foundations, civil society, and social development in general. The structure of the RICF is deliberately designed and normalized according to the Three Normal Forms. The database schema consists of three major themes: foundations’ basic organizational profile (i.e., basic profile, board member, supervisor, staff, and related party tables), program information (i.e., program information, major program, program relationship, and major recipient tables), and financial information (i.e., financial position, financial activities, cash flow, activity overview, and large donation tables). The RICF’s data quality can be measured by four criteria: data source reputation and credibility, completeness, accuracy, and timeliness. Data records are properly versioned, allowing verification and replication for research purposes

Physics-Augmented Data-EnablEd Predictive Control for Eco-driving of Mixed Traffic Considering Diverse Human Behaviors

Data-driven cooperative control of connected and automated vehicles (CAVs) has gained extensive research interest as it can utilize collected data to generate control actions without relying on parametric system models that are generally challenging to obtain. Existing methods mainly focused on improving traffic safety and stability, while less emphasis has been placed on energy efficiency in the presence of uncertainties and diversities of human-driven vehicles (HDVs). In this paper, we employ a data-enabled predictive control (DeePC) scheme to address the eco-driving of mixed traffic flows with diverse behaviors of human drivers. Specifically, by incorporating the physical relationship of the studied system and the Hankel matrix update from the generalized behavior representation to a particular one, we develop a new Physics-Augmented Data-EnablEd Predictive Control (PA-DeePC) approach to handle human driver diversities. In particular, a power consumption term is added to the DeePC cost function to reduce the holistic energy consumption of both CAVs and HDVs. Simulation results demonstrate the effectiveness of our approach in accurately capturing random human driver behaviors and addressing the complex dynamics of mixed traffic flows, while ensuring driving safety and traffic efficiency. Furthermore, the proposed optimization framework achieves substantial reductions in energy consumption, i.e., average reductions of 4.83% and 9.16% when compared to the benchmark algorithms

RAR-PINN algorithm for the data-driven vector-soliton solutions and parameter discovery of coupled nonlinear equations

This work aims to provide an effective deep learning framework to predict the vector-soliton solutions of the coupled nonlinear equations and their interactions. The method we propose here is a physics-informed neural network (PINN) combining with the residual-based adaptive refinement (RAR-PINN) algorithm. Different from the traditional PINN algorithm which takes points randomly, the RAR-PINN algorithm uses an adaptive point-fetching approach to improve the training efficiency for the solutions with steep gradients. A series of experiment comparisons between the RAR-PINN and traditional PINN algorithms are implemented to a coupled generalized nonlinear Schr\"{o}dinger (CGNLS) equation as an example. The results indicate that the RAR-PINN algorithm has faster convergence rate and better approximation ability, especially in modeling the shape-changing vector-soliton interactions in the coupled systems. Finally, the RAR-PINN method is applied to perform the data-driven discovery of the CGNLS equation, which shows the dispersion and nonlinear coefficients can be well approximated

Transformable Super-Isostatic Crystals Self-Assembled from Segment Colloidal Rods

Colloidal particles can spontaneously self-assemble into ordered structures, which not only can manipulate the propagation of light, but also vibration or phonons. Using Monte Carlo simulation, we study the self-assembly of perfectly aligned segment rod particles with lateral flat cutting. Under the help of surface attractions, we find that particles with different cutting degree can self-assemble into different crystal phases characterized by bond coordination $z$ that varies from 3 to 6. Importantly, we identify a transformable super-isostatic structures with \emph{pgg} symmetry and redundant bonds ($z=5$). We find that this structure can support either the soft bulk model or soft edge model depending on its Poisson's ratio which can be tuned from positive to negative by a uniform soft deformation. Importantly, the bulk soft modes are associated with states of self-stress along the direction of zero strain during the uniform soft deformation. This self-assembled transformable super-isostatic structure may act as mechanical metamaterials with potential application in micro-mechanical engineering.Comment: 11pages,5 figure

Steady-State Response of Axially Moving Viscoelastic Beams With Pulsating Speed:

Abstract Principal parametric resonance in transverse vibration is investigated for viscoelastic beams moving with axial pulsating speed. A nonlinear partial-differential equation governing the transverse vibration is derived from the dynamical, constitutive, and geometrical relations. Under certain assumption, the partial-differential reduces to an integro-partialdifferential equation for transverse vibration of axially accelerating viscoelastic nonlinear beams. The method of multiple scales is applied to two equations to calculate the steady-state response. Closed form solutions for the amplitude of the vibration are derived from the solvability condition of eliminating secular terms. The stability of straight equilibrium and nontrivial steady-state response are analyzed by use of the Lyapunov linearized stability theory. Numerical examples are presented to highlight the effects of speed pulsation, viscoelascity, and nonlinearity and to compare results obtained from two equations

Minkowski's lost legacy and hadron electromagnetism

We revisit Minkowski's lost legacy on relativistic electromagnetism in order to resolve long-standing puzzles over the charge distribution of relativistic systems like hadrons. Hadrons are unique relativistic electromagnetic systems characterized by their comparable size and Compton wavelength $r_h \sim \lambda_C$. As such, it was recently realized that the traditional Sachs definition of the charge distribution based on a non-relativistic formula is invalid. We explain that this is the same problem pursued by Lorentz, Einstein and others, on the electromagnetism of a moving body. We show how various charge distributions proposed in hadronic physics naturally emerge as the multipole moment densities in the macroscopic theory of relativistic electromagnetism.Comment: 7 pages, 2 figures; published on Physics Letters