A method which produces a sequence of numerical approximations which converges (provided technical conditions are satisfied) to the solution of a problem, generally through repeated applications of some procedure. Examples include Newton's method for root finding, and Jacobi iteration for ...

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41 views

what is procedure for crank Nicolson method in nonlinear partial differential equations? [closed]

can u tell me step by step of what is procedure for crank Nicolson method to apply in nonlinear partial differential equations? and how to plot it.
4
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0answers
88 views

Robust smoothers for geometric multigrid

I'm searching for robust smoothers for geometric multigrids. By robust I mean: Effective for high order approximations (say spectral element, spectral Discontinuous Galerkin), Parallel (suitable ...
0
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1answer
123 views

How to solve the problem without using symbolic computation

I have the following simple nonlinear equations with two unknowns only: $$\left\{ \begin{array}{c} \int_1^2{\dfrac{ e^{{a_1} x+{a_2} x^3}}{1+x^2}} \, dx=1 \\[13pt] \int_1^2{ x^2 e^{{a_1} x+{a_2} ...
0
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0answers
47 views

Gauss-Seidel iteration weighted by change

In general, I can use Gauss-Seidel iteration for finite difference solution of partial differential equations. In my case I am only solving an analog of steady-state heat transfer, so there is no ...
0
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0answers
23 views

what's the optimal parameters to reach the maximum speed of GAMG algorithm

everyone! As the GAMG algorithm has many parameters to set, how can I reach the maximum speed? Is there any optimal parameters range for any CFD models? or I have to try every parameters to reach the ...
3
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1answer
119 views

Is this finite difference approach correct?

I am solving incompressible 2D Navier-Stokes equations with zero y-component velocity. The geometry is a simple 2D pipe of a length $L$ and diameter $W$ and there is only two boundary conditions: ...
2
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0answers
23 views

SPECT reconstrction using MLEM

In Single-Photon Emission Computerized Tomography (SPECT) parallel beam reconstruction using Maximum-Likelihood Expectation–Maximization(MLEM), is it sufficient to scan the object around 180 degree? ...
0
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0answers
27 views

Learning Lanczos eigenvalue iteration - what is wrong?

I try to familiarize myself with iterative eigenvalue solvers such as Lanczos. So I tried rewrite it to python directly according to wiki. But it doesn't seem to work. The problem: it approximates ...
5
votes
1answer
77 views

Eigenvectors of slightly perturbed matrix

Assume I know eigen-pairs $(\epsilon_i,\vec\phi_i)$ for matrix operator $\hat H$ that $ \hat H \vec \phi_i = \epsilon_i \vec \phi_i $ Now I have slightly perturbed $\hat H' = \hat H + \hat R$ were ...
4
votes
1answer
100 views

Power Iteration over Rayleigh Quotient Iteration?

It is a commonly known fact that the Rayleigh Quotient converges cubically (1), while the Power Iteration may converge slowly if the difference between the dominant and second-dominant eigenvalue is ...
1
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0answers
27 views

Markov (Chain) image generators?

Markov Chains can be used to generate, or auto-complete, text. https://en.wikipedia.org/wiki/Markov_chain#Markov_text_generators Training text is read, and some information about the text is ...
10
votes
1answer
262 views

Smallest eigenvalue without inverse

Suppose $A\in\mathbb{R}^{n\times n}$ is a symmetric, positive definite matrix. $A$ is big enough that it's expensive to solve $Ax=b$ directly. Is there an iterative algorithm for finding the ...
1
vote
1answer
93 views

Iterative Closest Point Algorithm

I am currently working on an iterative closest point algorithm (in C++, see here). I understand the basic premise of an ICP algorithm. You have two point clouds (a target and a reference) and you ...
7
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0answers
62 views

DIIS method to accelerate SCF convergence for stretched geometries

I am implementing from scratch an Hartree-Fock calculation in the STO-3G basis set to perform Born-Oppenheimer molecular dynamics. I have a Restricted Hartree-Fock procedure that can reproduce very ...
0
votes
1answer
68 views

Variational Monte Carlo: Variational energy is lower than ground state energy

I'm writing a VMC simulation for hydrogen and helium atoms, but in both my codes my variational energy for certain wavefunctions is not only statistically different from my expectation value, but it ...
2
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0answers
55 views

Does Conjugate Residual really have convergence properties similar to that of Conjugate Gradient?

I have coded up a toy implementation of Conjugate Residual and have been testing it. Both wikipedia and the Saad claim that Conjugate Residual and Conjugate Gradient have similar convergence ...
9
votes
1answer
193 views

Iterative “solver” for $x^t \Sigma^{-1} x$

I can't imagine I'm the first to think about the following problem, so I'll be satisfied with a reference (but a complete, detailed answer is always appreciated): Say you have a symmetric positive ...
4
votes
0answers
64 views

What causes periodic humps in residual plots?

When using many iterative methods, whether for solving linear systems, looking for steady-state convergence in CFD, etc., the semilog plot of the residual often shows "humps" as the residual decays. ...
1
vote
1answer
71 views

Convergence problem in iterative method

I am trying to solve two non-linear equations self-consistently in a Gummel loop. Sometimes (every once in a while), I get to a situation when the loop repeats itself with wrong solutions and a ...
2
votes
1answer
59 views

Minimizing Cost Functions using Iterative Least Squares

I am currently trying to use iterative least squares to solve a system, $y = Hx + v$ where $y$ is a vector of observations, $H$ is the design matrix, and $v$ is the observation error. From my ...
9
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1answer
128 views

What iterative method can effectively solve a linear system with this kind of spectrum

I have a linear system with matrix which eigenvalues are uniformly distributed on the unit circle like this: Is it possible to solve this kind of system effectively by iterative method, maybe with ...
1
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1answer
67 views

Incomplete Cholesky

Is there an efficient way to perform an incomplete Cholesky factorization on a symmetric positive definite sparse matrix (CSR format), in order to use it as a preconditioner for a CG solver? Is there ...
5
votes
1answer
362 views

Can Gauss-Seidel/SOR (preconditioned?) be applied to a non-diagonally dominant matrix?

After applying finite difference method to a Laplace/Poisson problem always arises a diagonal dominant system of equations that can be solved with Gauss-Seidel or SOR methods. If the original PDE does ...
2
votes
1answer
128 views

Best preconditioner for mixed-poisson problem (RT0 elements)

For a very large mixed-poisson problem with lowest order Raviart-Thomas elements (RT0), I plan on using an iterative solver. However, this kind of problem is not positive-definite (saddle point ...
2
votes
2answers
143 views

FLOPs of iterative vs direct solvers

In general, do iterative solvers require more floating point operations than the direct solver counterparts? I have some scientific code (written in both PETSc and FEniCS) for solving a mixed FE ...
0
votes
1answer
117 views

Strict Feasibility in Interior Point Methods

As we know, in the interior point methods, all the iterates have to be strictly feasible. I implemented an affine scaling interior point for nonlinear objective functions. For small examples (2D), it ...
0
votes
2answers
274 views

How to obtain a convergent solution iteratively for a linear system of equations? [closed]

I am working on a problem that requires an iterative procedure to solve a linear system of equations, the system of equations in matrix form is: $$\underbrace{\begin{bmatrix} r_{11} & r_{12} ...
4
votes
1answer
92 views

How to evaluate a series of derivatives?

Consider the function $$f(\mathbf{x}) = \sum_{n=0}^{N} a_n \left( (\mathbf{b}-\mathbf{x})\cdot \nabla \right)^n \frac{1}{r}$$ where $r = |\mathbf{x}| = \sqrt{(x-x_0)^2 + (y-y_0)^2}$ and $a_n$ and ...
1
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1answer
142 views

Direct or iterative solver for ill-conditioned problems

I have to solve an ill-conditioned sparse matrix. Once I read that iterative solver are the better tool for such problems. Is that true? If yes, why?
1
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0answers
102 views

Search Direction in Conjugate Gradient

Could you help me with a Conjugate Gradient question? In using CG to solve Ax=b, why is the search direction $p_{k+1}$ in CG chosen as a linear combination of the residual $r_k$ and previous direction ...
4
votes
1answer
122 views

Methods for Constrained Optimization Problems with Box Constraints

Consider this problem: \begin{equation} \begin{array}{ll} \text{minimize } & f(x) \\ \text{subject to } & a \leq x \leq b \end{array} \end{equation} where $a,b,x \in ...
0
votes
1answer
71 views

Iterative algorithms for sparsity using a function for operator A in Ax=b

I am going to solve an linear iterative inverse problem. I have two functions in matlab which one of them play the forward and ...
1
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0answers
128 views

Speeding up the classical Jacobi method using Scheduled Relaxation method? [closed]

There has been quite a flutter recently in the iterative world about an algorithm that speeds up the classical Jacobi method by as much as 200 times using a scheduled relaxation method where a ...
3
votes
1answer
208 views

Designing a preconditioner for a very Ill-conditionned matrix

I am a physicist with limited numerical methods knowledge and I am trying to speed up the inversion of a very ill-conditioned problem ($rcond>10^{30}$). The same sparse square matrix is used ...
3
votes
2answers
251 views

How many generations does it typically take for a differential evolution method to reach a global optimum?

For differential evolution methods in optimization, how many generations does it typically take to reach a global optimum? How do we know if the values are never going to converge?
1
vote
3answers
135 views

Test set for linear solvers

Lets assume I have a iterative linear system solver, e. g. this one. Whats the typical approach on verifying and testing this kind of solvers? Is there a standard test set of linear systems one ...
3
votes
2answers
451 views

What are some reasons that Conjugate Gradient iteration does not converge?

I would greatly appreciate it if you could share some reasons the Conjugate Gradient iteration for Ax = b does not converge? My matrix A is symmetric positive definite. Thank you so much! Edit with ...
2
votes
1answer
718 views

How to test convergence of an algorithm for constrained optimization

I am applying an iterative method (projected newton) to an optimization problem. Theoretically, the method should converge linearly. I would greatly appreciate it if you could share how should I test ...
4
votes
1answer
58 views

Iteratively refine bounds on exp for Metropolis criterion

In Monte Carlo simulations, using the Metropolis criterion, one often has to compare a random number $a$, $0 \leq a < 1$, to the Boltzmann distribution $exp(-\beta\Delta E)$, where $\Delta E$ is ...
1
vote
2answers
74 views

Performance metrics to compare initial-boundary value problem solutions

I am comparing the performance several finite difference methods of solving an initial-boundary value problem. There are several dimensions to this comparison: Number of cells Number of timesteps ...
2
votes
3answers
401 views

Eigenvalues of a sparse banded nonsymmetric matrix from an elliptic operator

I have a sparse matrix coming from the discretization of a 3D elliptic PDE. The matrix is banded with seven non-zeros diagonals. The sparsity pattern of the matrix looks like this (the actual matrix ...
4
votes
1answer
224 views

Linear equation system: Direct solver works, iterative solver does not

I have to solve for x in b = A*x, where a is sparse. This works fine with Matlab's mldivide: x = A \ b. Since I will have to use an iterative algorithm for very large A, I'm currently testing Matlab's ...
1
vote
1answer
119 views

Finding null vectors of a parameter-dependent matrix

I have dense complex matrices $M(z)$ in which each element $M_{ij} = M_{ij}(z)$ depends on a complex parameter $z$. I need to find $z$ such that the matrix $M$ gets singular, i.e. I am looking for ...
2
votes
1answer
103 views

Finding Interior eigenvalues using Davidson algorithm

Is it possible to find interior eigenvalues closer to some lambda using Davidson method. I was searching online but found that most people use Jacobi-Davidson method for that. Thanks
1
vote
2answers
365 views

What sparse linear programming solver it is better to use?

I have the following LP problem: $$ \min \limits_{\varepsilon, x_{1}, \ldots, x_{n}}f(\varepsilon, x_{1}, \ldots, x_{n}) = \varepsilon \;\;\;\;\; s.t. \;\;C x \geq 0, \;\; x_{i}^{0} - \varepsilon ...
2
votes
0answers
80 views

Modal analysis of structure with aerodynamic damping

I'm using modal decomposition to predict the steady state response of a beam structure to harmonic loading. The structure itself is very lightly damped, but we know from experiments that the ...
7
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3answers
1k views

Sort of problems where SOR is faster than Gauss-Seidel?

Is there any simple rule of thumb to say if it is worth to do SOR instead of Gauss-Seidel? ( and possible way how to estimate realxation parameter $\omega$) I mean just by looking on the matrix, or ...
2
votes
2answers
691 views

What is the difference between “Newton-type” and “Newton-like” iteration?

Is there any clear classification between different iterative methods? What is the difference between Newton-type and ...
1
vote
0answers
122 views

full rank update to cholesky decomposition for multivariate normal distribution

This question is a specialization of full rank update to cholesky decomposition, to which I hope to get a more positive answer. When calculating the minus log of the multivariate normal distribution, ...
2
votes
1answer
273 views

full rank update to cholesky decomposition

Let $A$ be a real, symmetric, positive definite matrix. It has at least 500 rows, possibly much more. I compute its Cholesky decomposition, which allows me to calculate $det(A)$ $A^{-1}X$ for some ...