Moving-Water Equilibria Preserving HLL-Type Schemes for the Shallow Water Equations

We construct new HLL-type moving-water equilibria preserving upwind schemes for the one-dimensional Saint-Venant system of shallow water equations with nonflat bottom topography.The designed first-and secondorder schemes are tested on a number of numerical examples,in which we verify the well-balanced property as well as the ability of the proposed schemes to accurately capture small perturbations of moving-water steady states.

Adaptive Moving Mesh Central-Upwind Schemes for Hyperbolic System of PDEs:Applications to Compressible Euler Equations and Granular Hydrodynamics

We introduce adaptive moving mesh central-upwind schemes for one-and two-dimensional hyperbolic systems of conservation and balance laws.The proposed methods consist of three steps.First,the solution is evolved by solving the studied system by the second-order semi-discrete central-upwind scheme on either the one-dimensional nonuniform grid or the two-dimensional structured quadrilateral mesh.When the evolution step is complete,the grid points are redistributed according to the moving mesh differential equation.Finally,the evolved solution is projected onto the new mesh in a conservative manner.The resulting adaptive moving mesh methods are applied to the one-and two-dimensional Euler equations of gas dynamics and granular hydrodynamics systems.Our numerical results demonstrate that in both cases,the adaptive moving mesh central-upwind schemes outperform their uniform mesh counterparts.

Finding the Maximal Eigenpair for a Large, Dense, Symmetric Matrix based on Mufa Chen's Algorithm

A hybrid method is presented for determining maximal eigenvalue and its eigenvector(called eigenpair)of a large,dense,symmetric matrix.Many problems require finding only a small part of the eigenpairs,and some require only the maximal one.In a series of papers,efficient algorithms have been developed by Mufa Chen for computing the maximal eigenpairs of tridiagonal matrices with positive off-diagonal elements.The key idea is to explicitly construet effective initial guess of the maximal eigenpair and then to employ a self-closed iterative algorithm.In this paper we will extend Mufa Chen's algorithm to find maximal eigenpair for a large scale,dense,symmetric matrix.Our strategy is to first convert the underlying matrix into the tridiagonal form by using similarity transformations.We then handle the cases that prevent us from applying Chen's algorithm directly,e.g.,the cases with zero or negative super-or sub-diagonal elements.Serval numerical experiments are carried out to demonstrate the efficiency of the proposed hybrid method.

ON THE EMPTY BALLS OF A CRITICAL OR SUBCRITICAL BRANCHING RANDOM WALK

Let{Z_(n)}_(n)≥0 be a critical or subcritical d-dimensional branching random walk started from a Poisson random measure whose intensity measure is the Lebesugue measure on R^(d).Denote by R_(n):=sup{u>0:Z_(n)({x∈R^(d):∣x∣<u})=0}the radius of the largest empty ball centered at the origin of Z_(n).In this work,we prove that after suitable renormalization,Rn converges in law to some non-degenerate distribution as n→∞.Furthermore,our work shows that the renormalization scales depend on the offspring law and the dimension of the branching random walk.This completes the results of Révész[13]for the critical binary branching Wiener process.

Fifth-Order A-WENO Schemes Based on the Adaptive Diffusion Central-Upwind Rankine-Hugoniot Fluxes

We construct new fifth-order alternative WENO(A-WENO)schemes for the Euler equations of gas dynamics.The new scheme is based on a new adaptive diffusion centralupwind Rankine-Hugoniot(CURH)numerical flux.The CURH numerical fluxes have been recently proposed in[Garg et al.J Comput Phys 428,2021]in the context of secondorder semi-discrete finite-volume methods.The proposed adaptive diffusion CURH flux contains a smaller amount of numerical dissipation compared with the adaptive diffusion central numerical flux,which was also developed with the help of the discrete RankineHugoniot conditions and used in the fifth-order A-WENO scheme recently introduced in[Wang et al.SIAM J Sci Comput 42,2020].As in that work,we here use the fifth-order characteristic-wise WENO-Z interpolations to evaluate the fifth-order point values required by the numerical fluxes.The resulting one-and two-dimensional schemes are tested on a number of numerical examples,which clearly demonstrate that the new schemes outperform the existing fifth-order A-WENO schemes without compromising the robustness.

Positive definiteness of real quadratic forms resulting from the variable-step L1-type approximations of convolution operators

The positive definiteness of real quadratic forms with convolution structures plays an important rolein stability analysis for time-stepping schemes for nonlocal operators. In this work, we present a novel analysistool to handle discrete convolution kernels resulting from variable-step approximations for convolution operators.More precisely, for a class of discrete convolution kernels relevant to variable-step L1-type time discretizations, weshow that the associated quadratic form is positive definite under some easy-to-check algebraic conditions. Ourproof is based on an elementary constructing strategy by using the properties of discrete orthogonal convolutionkernels and discrete complementary convolution kernels. To our knowledge, this is the first general result onsimple algebraic conditions for the positive definiteness of variable-step discrete convolution kernels. Using theunified theory, we obtain the stability for some simple nonuniform time-stepping schemes straightforwardly.

The top-order energy of quasilinear wave equations in two space dimensions is uniformly bounded

Alinhac solved a long-standing open problem in 2001 and established that quasilinear wave equations in two space dimensions with quadratic null nonlinearities admit global-in-time solutions,provided that the initial data are compactly supported and sufficiently small in Sobolev norm.In this work,Alinhac obtained an upper bound with polynomial growth in time for the top-order energy of the solutions.A natural question then arises whether the time-growth is a true phenomenon,despite the possible conservation of basic energy.In the present paper,we establish that the top-order energy of the solutions in Alinhac theorem remains globally bounded in time.

Localized Exponential Time Differencing Method for Shallow Water Equations: Algorithms and Numerical Study

In this paper,we investigate the performance of the exponential time differencing(ETD)method applied to the rotating shallow water equations.Comparing with explicit time stepping of the same order accuracy in time,the ETD algorithms could reduce the computational time in many cases by allowing the use of large time step sizes while still maintaining numerical stability.To accelerate the ETD simulations,we propose a localized approach that synthesizes the ETD method and overlapping domain decomposition.By dividing the original problem into many subdomain problems of smaller sizes and solving them locally,the proposed approach could speed up the calculation of matrix exponential vector products.Several standard test cases for shallow water equations of one or multiple layers are considered.The results show great potential of the localized ETD method for high-performance computing because each subdomain problem can be naturally solved in parallel at every time step.

Linear-quadratic generalized Stackelberg games with jump-diffusion processes and related forward-backward stochastic differential equations

A kind of linear-quadratic Stackelberg games with the multilevel hierarchy driven by both Brownian motion and Poisson processes is considered.The Stackelberg equilibrium is presented by linear forward-backward stochastic differential equations(FBSDEs)with Poisson processes(FBSDEPs)in a closed form.By the continuity method,the unique solvability of FBSDEPs with a multilevel self-similar domination-monotonicity structure is obtained.

Revisit of Semi-Implicit Schemes for Phase-Field Equations

It is a very common practice to use semi-implicit schemes in various computations,which treat selected linear terms implicitly and the nonlinear terms explicitly.For phase-field equations,the principal elliptic operator is treated implicitly to reduce the associated stability constraints while the nonlinear terms are still treated explicitly to avoid the expensive process of solving nonlinear equations at each time step.However,very few recent numerical analysis is relevant to semi-implicit schemes,while”stabilized”schemes have become very popular.In this work,we will consider semiimplicit schemes for the Allen-Cahn equation with general potential function.It will be demonstrated that the maximum principle is valid and the energy stability also holds for the numerical solutions.This paper extends the result of Tang&Yang(J.Comput.Math.,34(5)(2016),pp.471–481),which studies the semi-implicit scheme for the Allen-Cahn equation with polynomial potentials.

Stability of the Semi-Implicit Method for the Cahn-Hilliard Equation with Logarithmic Potentials

We consider the two-dimensional Cahn-Hilliard equation with logarithmic potentials and periodic boundary conditions.We employ the standard semi-implicit numerical scheme,which treats the linear fourth-order dissipation term implicitly and the nonlinear term explicitly.Under natural constraints on the time step we prove strict phase separation and energy stability of the semiimplicit scheme.This appears to be the first rigorous result for the semi-implicit discretization of the Cahn-Hilliard equation with singular potentials.

Effective Maximum Principles for Spectral Methods

Many physical problems such as Allen-Cahn flows have natural maximum principles which yield strong point-wise control of the physical solutions in terms of the boundary data,the initial conditions and the operator coefficients.Sharp/strict maximum principles insomuch of fundamental importance for the continuous problem often do not persist under numerical discretization.A lot of past research concentrates on designing fine numerical schemes which preserves the sharp maximum principles especially for nonlinear problems.However these sharp principles not only sometimes introduce unwanted stringent conditions on the numerical schemes but also completely leaves many powerful frequency-based methods unattended and rarely analyzed directly in the sharp ma-ximum norm topology.A prominent example is the spectral methods in the family of weighted residual methods.In this work we introduce and develop a new framework of almost sharp maximum principles which allow the numerical solutions to deviate from the sharp bound by a controllable discretization error:we call them effective maximum principles.We showcase the analysis for the classical Fourier spectral methods including Fourier Galerkin and Fourier collocation in space with forward Euler in time or second order Strang splitting.The model equations include the Allen-Cahn equations with double well potential,the Burgers equation and the Navier-Stokes equations.We give a comprehensive proof of the effective maximum principles under very general parametric conditions.

A Well-Balanced Partial Relaxation Scheme for the Two-Dimensional Saint-Venant System

We develop a new moving-water equilibria preserving partial relaxation(PR)scheme for the two-dimensional(2-D)Saint-Venant systemof shallowwater equations.The new scheme is a 2-D generalization of the one-dimensional(1-D)PR scheme recently proposed in[X.Liu,X.Chen,S.Jin,A.Kurganov,andH.Yu,SIAMJ.Sci.Comput.,42(2020),pp.A2206–A2229].Our scheme is based on the PR approximation,which is designed in two steps.First,the geometric source terms are incorporated into the discharge fluxes,which results in a hyperbolic system with global fluxes.Second,the discharge equations are relaxed so that the nonlinearity is moved into the stiff right-hand side of the four added auxiliary equation.The obtained PR system is then numerically integrated using a semi-discrete hybrid upwind/central-upwind finitevolume method combined with an efficient semi-implicit ODE solver.The new 2-D PR scheme inherits the main advantages of the 1-D PR scheme:(i)no special treatment of the geometric source terms is required,(ii)no nonlinear(cubic)equations should be solved to obtain the point values of the water depth out of the reconstructed equilibriumvariables.The performance of the proposed PR scheme is illustrated on a number of numerical examples,in which we demonstrate that the PR scheme not only capable of exactly preserving quasi 1-D moving-water steady states and accurately capturing their small perturbations,but can also handle genuinely 2-D steady states and their small perturbations in a non-oscillatory manner.

Initial and Boundary Value Problem for a System of Balance Laws from Chemotaxis:Global Dynamics and Diffusivity Limit

In this paper,we study long-time dynamics and diffusion limit of large-data solutions to a system of balance laws arising from a chemotaxis model with logarithmic sensitivity and nonlinear production/degradation rate.Utilizing energy methods,we show that under time-dependent Dirichlet boundary conditions,long-time dynamics of solutions are driven by their boundary data,and there is no restriction on the magnitude of initial energy.Moreover,the zero chemical diffusivity limit is established under zero Dirichlet boundary conditions,which has not been observed in previous studies on related models.

Mean-Field Backward Stochastic Differential Equations Driven by Fractional Brownian Motion

In this paper,we study a new class of equations called mean-field backward stochastic differential equations(BSDEs,for short)driven by fractional Brownian motion with Hurst parameter H>1/2.First,the existence and uniqueness of this class of BSDEs are obtained.Second,a comparison theorem of the solutions is established.Third,as an application,we connect this class of BSDEs with a nonlocal partial differential equation(PDE,for short),and derive a relationship between the fractional mean-field BSDEs and PDEs.

The Global Landscape of Phase Retrieval Ⅱ:Quotient Intensity Models

A fundamental problem in phase retrieval is to reconstruct an unknown signal from a set of magnitude-only measurements.In this work we introduce three novel quotient intensity models(QIMs) based on a deep modification of the traditional intensity-based models.A remarkable feature of the new loss functions is that the corresponding geometric landscape is benign under the optimal sampling complexity.When the measurements ai∈Rn are Gaussian random vectors and the number of measurements m≥Cn,the QIMs admit no spurious local minimizers with high probability,i.e.,the target solution x is the unique local minimizer(up to a global phase) and the loss function has a negative directional curvature around each saddle point.Such benign geometric landscape allows the gradient descent methods to find the global solution x(up to a global phase) without spectral initialization.

The Global Landscape of Phase Retrieval I:Perturbed Amplitude Models

A fundamental task in phase retrieval is to recover an unknown signal x∈R^(n) from a set of magnitude-only measurements y_(i)=|〈a_(i),x〉|,i=1,…,m.In this paper,we propose two novel perturbed amplitude models(PAMs)which have a non-convex and quadratic-type loss function.When the measurements a_(i)∈R^(n) are Gaussian random vectors and the number of measurements m≥Cn,we rigorously prove that the PAMs admit no spurious local minimizers with high probability,i.e.,the target solution x is the unique local minimizer(up to a global phase)and the loss function has a negative directional curvature around each saddle point.Thanks to the well-tamed benign geometric landscape,one can employ the vanilla gradient descent method to locate the global minimizer x(up to a global phase)without spectral initialization.We carry out extensive numerical experiments to show that the gradient descent algorithm with random initialization outperforms state-of-the-art algorithms with spectral initialization in empirical success rate and convergence speed.

Revisit of the Faddeev Model in Dimension Two

The Faddeev model is a fundamental model in relativistic quantum field theory used to model elementary particles. The Faddeev model can be regarded as a system of non-linear wave equations with both quasi-linear and semi-linear non-linearities, which is particularly challenging in two space dimensions. A key feature of the system is that there exist undifferentiated wave components in the non-linearities, which somehow causes extra difficulties. Nevertheless, the Cauchy problem in two space dimenions was tackled by Lei-Lin-Zhou(2011) with small, regular, and compactly supported initial data, using Klainerman’s vector field method enhanced by a novel angular-radial anisotropic technique.In the present paper, the authors revisit the Faddeev model and remove the compactness assumptions on the initial data by Lei-Lin-Zhou(2011). The proof relies on an improved L2norm estimate of the wave components in Theorem 3.1 and a decomposition technique for non-linearities of divergence form.

Boundary Homogenization of a Class of Obstacle Problems

We study the homogenization of a boundary obstacle problem on a C^(1,α)-domain D for some elliptic equations with uniformly elliptic coefficient matricesγ.For anyε∈R+,■D=Γ∪E,Γ∩∑=Фand Sε■∑with suitable assumptions,we prove that asεtends to zero,the energy minimizer u^(ε) of∫_(D)|γ▽u|^(2) dx,subject to u≥φcp on S_(ε),up to a subsequence,converges weakly in H^(1)(D)to u,which minimizes the energy functional∫D|r▽u|^(2)+∫∑(u-φ)^(2)-μ(x)dS_(x),whereμ(x)depends on the structure of Sεandφis any given function in C∞(D).