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In this paper, we investigate the energy minimization model arising in the ensemble Kohn--Sham density functional theory for metallic systems, in which a pseudo-eigenvalue matrix and a general smearing approach are involved. We study the invariance of the energy functional and the existence of the minimizer of the ensemble Kohn--Sham model. We propose an adaptive twoparameter step size strategy and the corresponding preconditioned conjugate gradient methods to solve the energy minimization model. Under some mild but reasonable assumptions, we prove the global convergence for the gradients of the energy functional produced by our algorithms. Numerical experiments show that our algorithms are efficient, especially for large scale metallic systems. In particular, our algorithms produce convergent numerical approximations for some metallic systems, for which the traditional self-consistent field iterations fail to converge. [ABSTRACT FROM AUTHOR]

The goal of this paper is to relate the capacitance matrix formalism to the tightbinding approximation. By doing so, we open the way to the use of mathematical techniques and tools from condensed matter theory in the mathematical and numerical analysis of metamaterials, in particular for the understanding of their topological properties. We first study how the capacitance matrix formalism, both when the material parameters are static and modulated, can be posed in a Hamiltonian form. Then, we use this result to compare this formalism to the tight-binding approximation. We prove that the correspondence between the capacitance formulation and the tight-binding approximation holds only in the case of dilute resonators. On the other hand, the tight-binding model is often coupled with a nearest-neighbor approximation, whereby long-range interactions are neglected. Even in the dilute case, we show that long-range interactions between subwavelength resonators are relatively strong and nearest-neighbor approximations are not generally appropriate. [ABSTRACT FROM AUTHOR]

This paper is mainly concerned with a two-species competition model in open advective environments, where individuals cannot pass through the upstream boundary and do not return to the habitat after leaving the downstream boundary. By the theory of principal eigenvalue, we first obtain two critical curves (Γ1 and Γ2) in the plane of bifurcation parameters that sharply determine the local stability of the two semitrivial steady states. Then under various conditions on given parameters, we discuss the global dynamics via different techniques, including the comparison principle for eigenvalues and perturbation and compactness arguments, and show that both competitive exclusion and coexistence are possible. For general values of parameters, we take both analytic and numerical approaches to further understand the potential behaviors of Γ1 and Γ2, and we numerically observe that in addition to the competitive exclusion and coexistence, the bistable phenomenon is also possible, which is different from the known results of competitive ODE and reaction-diffusion systems (where bistability is impossible). The implication of our numerical results on future work is also discussed. [ABSTRACT FROM AUTHOR]

The finite-time stabilization problem is considered for a class of multi-input multioutput nonlinear systems composed of several different subsystems that are coupled with unknown nonlinearities, possibly superlinear and nonvanishing at the origin. A novel decentralized, continuous finite-time output-feedback control algorithm is presented by dynamically compensating the unknown nonlinear couplings and applying a saturation technique. A crucial strategy is to estimate the uncertain nonlinearities and the unmeasured state by means of a finite-time extended state observer. The effectiveness of the proposed decentralized finite-time output-feedback design is validated by rigorous mathematical analysis and numerical simulations. [ABSTRACT FROM AUTHOR]

Threshold-linear networks (TLNs) are recurrent networks where the dynamics are threshold-linear (linearly rectified at zero). Mathematically, they consist of coupled nonsmooth ordinary differential equations. When the nodes in the network are assumed to be neurons or neuronal populations, TLNs represent firing rate models. We investigate the dynamics of a subclass of TLNs referred to as competitive TLNs where all the connections between different nodes are inhibitory. We prove the existence of periodic solutions in competitive TLNs with three nodes using a combination of mathematical analysis and numerical simulations. We calculate the analytical expressions of the periodic solutions, then we consider a reduced system of transcendental equations and apply a Kantorovich's convergence result to demonstrate the existence of these solutions. We then analyze the attributes (frequency and amplitude) of these periodic solutions as the model parameters vary. Finally, we study the entrainment properties of competitive TLNs in the oscillatory regime, by examining their response to external periodic inputs to one of the nodes in the network. We numerically determine the ranges of input amplitudes and frequencies for which competitive TLNs are able to follow the periodic input for three-node networks and larger networks with cyclic symmetry. [ABSTRACT FROM AUTHOR]