State complexity of power

The number of states in a deterministic finite automaton (DFA) recognizing the language $L^k$, where $L$ is regular language recognized by an $n$-state DFA, and $k?2$ is a constant, is shown to be at most $n{2}^{(k?1)n}$ and at least $(n?k)2^{(k?1)(n?k)}$ in the worst case, for every $n>k$ and for every alphabet of at least six letters. Thus, the state complexity of $L^k$ is $\Theta \left(n{2}^{(k?1)n}\right)$. In the case $k=3$ the corresponding state complexity function for $L^3$ is determined as $\frac{6n?3}{8}{4}^n?(n?1)2^n?n$ with the lower bound witnessed by automata over a four-letter alphabet. The nondeterministic state complexity of $L^k$ is demonstrated to be $nk$. This bound is shown to be tight over a two-letter alphabet.     

Continuity and random dynamics of the non-autonomous stochastic FitzHugh–Nagumo system on RN

In this article, we use the so-called difference estimate method to investigate the continuity and random dynamics of the non-autonomous stochastic FitzHugh–Nagumo system with a general nonlinearity. Firstly, under weak assumptions on the noise coefficient, we prove the existence of a pullback attractor in $L^2\left({\mathbb{R}}^N\right)\times L^2\left({\mathbb{R}}^N\right)$ by using the tail estimate method and a certain compact embedding on bounded domains. Secondly, although the difference of the first component of solutions possesses at most $p$-times integrability where $p$ is the growth exponent of the nonlinearity, we overcome the absence of higher-order integrability and establish the continuity of solutions in $(L^p\left({\mathbb{R}}^N\right)\cap H^1\left({\mathbb{R}}^N\right))\times L^2\left({\mathbb{R}}^N\right)$ with respect to the initial values belonging to $L^2\left({\mathbb{R}}^N\right)\times L^2\left({\mathbb{R}}^N\right)$. As an application of the result on the continuity, the existence of a pullback attractor in $(L^p\left({\mathbb{R}}^N\right)\cap H^1\left({\mathbb{R}}^N\right))\times L^2\left({\mathbb{R}}^N\right)$ is proved for arbitrary $N\ge 1$ and $p>2$.     

Alternating direction implicit method for solving two-dimensional cubic nonlinear Schrödinger equation

In this paper, four alternating direction implicit (ADI) schemes are presented for solving two-dimensional cubic nonlinear Schrödinger equations. Firstly, we give a Crank–Nicolson ADI scheme and a linearized ADI scheme both with accuracy $O(\mathrm{\Delta }{t}^2+h^2)$, with the same method, use fourth-order Padé compact difference approximation for the spatial discretization; two HOC-ADI schemes with accuracy $O(\mathrm{\Delta }{t}^2+h^4)$ are given. The two linearized ADI schemes apply extrapolation technique to the real coefficient of the nonlinear term to avoid iterating to solve. Unconditionally stable character is verified by linear Fourier analysis. The solution procedure consists of a number of tridiagonal matrix equations which make the computation cost effective. Numerical experiments are conducted to demonstrate the efficiency and accuracy, and linearized ADI schemes show less computational cost. All schemes given in this paper also can be used for two-dimensional linear Schrödinger equations.     

Higher-order convergence with fractional-step method for singularly perturbed 2D parabolic convection–diffusion problems on Shishkin mesh

In this article, we propose a second-order uniformly convergent numerical method for a singularly perturbed 2D parabolic convection–diffusion initial–boundary-value problem. First, we use a fractional-step method to discretize the time derivative of the continuous problem on uniform mesh in the temporal direction, which gives a set of two 1D problems. Then, we use the classical finite difference scheme to discretize those 1D problems on a special mesh, which results almost first-order convergence, i.e., $O(N^{?1+\beta }lnN+\Delta t)$. To enhance the order of convergence to $O(N^{?2+\beta }{ln}^{2}N+\Delta t^2)$, we use the Richardson extrapolation technique. In support of the theoretical results, numerical experiments are performed by employing the proposed technique.     

Existence of ground states for a Kirchhoff type problem without 4-superlinear condition

We consider the existence of ground state solutions for the Kirchhoff type problem

where $a,b>0$, $N=1,2,3$ and $2<p<2^1$. Here we are interested in the case that $2<p\le 4$ since the existence of ground state for $4<p\le 2^1$ is easily obtained by a standard variational argument. Our method is based on a Poho$\stackrel{?}{z}$aev type identity.     

On the applicability of Postʼs lattice

For decision problems $\Pi (B)$ defined over Boolean circuits using gates from a restricted set B only, we have $\Pi (B){?}_m^{{\mathrm{AC}}^0}\Pi (B^{\prime })$ for all finite sets B and $B^{\prime }$ of gates such that all gates from B can be computed by circuits over gates from $B^{\prime }$. In this note, we show that a weaker version of this statement holds for decision problems defined over Boolean formulae, namely that $\Pi (B){?}_m^{{\mathrm{NC}}^2}\Pi (B^{\prime }\cup \{\wedge ,\vee \})$ and $\Pi (B){?}_m^{{\mathrm{NC}}^2}\Pi (B^{\prime }\cup \{0,1\})$ for all finite sets B and $B^{\prime }$ of Boolean functions such that all $f\in B$ can be defined in $B^{\prime }$.     

Eigenvalues of a real supersymmetric tensor

In this paper, we define the symmetric hyperdeterminant, eigenvalues and E-eigenvalues of a real supersymmetric tensor. We show that eigenvalues are roots of a one-dimensional polynomial, and when the order of the tensor is even, E-eigenvalues are roots of another one-dimensional polynomial. These two one-dimensional polynomials are associated with the symmetric hyperdeterminant. We call them the characteristic polynomial and the E-characteristic polynomial of that supersymmetric tensor. Real eigenvalues (E-eigenvalues) with real eigenvectors (E-eigenvectors) are called H-eigenvalues (Z-eigenvalues). When the order of the supersymmetric tensor is even, H-eigenvalues (Z-eigenvalues) exist and the supersymmetric tensor is positive definite if and only if all of its H-eigenvalues (Z-eigenvalues) are positive. An $m\mathrm{th}$-order $n$-dimensional supersymmetric tensor where $m$ is even has exactly $n{(m-1)}^{n-1}$ eigenvalues, and the number of its E-eigenvalues is strictly less than $n{(m-1)}^{n-1}$ when $m\ge 4$. We show that the product of all the eigenvalues is equal to the value of the symmetric hyperdeterminant, while the sum of all the eigenvalues is equal to the sum of the diagonal elements of that supersymmetric tensor, multiplied by ${(m-1)}^{n-1}$. The $n{(m-1)}^{n-1}$ eigenvalues are distributed in $n$ disks in $C$. The centers and radii of these $n$ disks are the diagonal elements, and the sums of the absolute values of the corresponding off-diagonal elements, of that supersymmetric tensor. On the other hand, E-eigenvalues are invariant under orthogonal transformations.     

A meshless method for solving the time fractional advection–diffusion equation with variable coefficients

In this paper, an efficient and accurate meshless method is proposed for solving the time fractional advection–diffusion equation with variable coefficients which is based on the moving least square (MLS) approximation. In the proposed method, firstly the time fractional derivative is approximated by a finite difference scheme of order $O\left({\left(\delta t\right)}^{2?\alpha }\right),0<\alpha \le 1$ and then the MLS approach is employed to approximate the spatial derivative where time fractional derivative is expressed in the Caputo sense. Also, the validity of the proposed method is investigated in error analysis discussion. The main aim is to show that the meshless method based on the MLS shape functions is highly appropriate for solving fractional partial differential equations (FPDEs) with variable coefficients. The efficiency and accuracy of the proposed method are verified by solving several examples.