Parameter Name 
Valid Entries 
Description 


n1.0, n2.0 
The basis set dictates the accuracy of the field representation within each mesh element. The higher the basis set order, the more functions are used, generally resulting in a more accurate result. For more information, see “Basis Set”. 

Local Error Estimate 
Determines what quantity is used to determine where to refine the mesh during AMR. 

Direct, Iterative, Automatic 
This parameter controls the type of solver that is used to solve the matrix equation(s). The options are Direct and Iterative. The Direct solver performs an LU factorization of the matrix, and the iterative method uses a variant of the preconditioned conjugate gradient (PCG) method. The “Iterative” setting will force the use of an iterative technique that does not rely on factorization of the system matrix. One of several iterative methods can be selected, each with distinctive characteristics that make them applicable in different situations. Generally, the direct methods require more memory than the iterative methods but are more reliable and are better for use with multiple right handsides. The iterative techniques can require much less memory than direct methods, but may or may not converge, so some experimentation may be required on any given problem. The Automatic selection is equivalent to Iterative, as this is typically faster than the Direct option. 

Automatic, HMLU, MFLU 
Choosing “Direct” for the linear solver method parameter forces the solver to use one of two methods that rely on an LU factorization of the system matrix – “MFLU” and “HMLU”. 

Automatic, Low, Medium, High, Perfect 
The HMLU linear solver produces an inexact LU factorization of the system matrix that is subsequently used in an iterative loop to determine the solution vectors for port/mode excitations. The accuracy of the factor can be controlled via the “Factor Accuracy Level” solver parameter. Options are “Low”, “Medium”, “High”, “Perfect”, and “Automatic”. The “Perfect” setting yields a factor with an accuracy equivalent to that obtained using the MFLU solver, and will result in the iterative loop converging in a single step. A lower factor accuracy is faster to compute and takes less system memory, as compared to higher accuracy settings, but it can also lead to more iterations being required in the iterative loop. If the “Automatic” setting is chosen, the solver will adjust the accuracy setting as necessary to minimize runtime and memory, starting with the “Low” setting. The “Automatic” setting also allows for failover to a different solver if the default solver cannot solve the problem. 

CG, BiStabCG, CGS, GMR 
Visible if Linear Solver/Method is " 

Jacobi, GaussSeidel 
Visible if Linear Solver/Method is " 

Visible if Linear Solver/Method is " 


Visible if Linear Solver/Method is " 
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