Use the Eigenvalue Solver () to find the solution to linear or linearized eigenvalue problems (also called eigenfrequency problems). This solver is automatically used when a Eigenvalue or Eigenfrequency study is added to the model.

Also see The Eigenvalue Solver Algorithms.

Use the Defined by study step list to specify if the settings are synchronized with the corresponding study step. Select User defined to specify the properties below (in addition to the relative tolerance, which is always available).

The settings here are similar to those for the Eigenvalue study step, with the following exceptions:

From the Eigenvalue transformation list, select a transformation method for transforming the eigenvalues into another related quantity. The default is None, which keeps the original eigenvalues. Depending on the physics in the model, other transformations might also be available.

The number in the Relative tolerance field (default 1.0·10−6) controls the relative error in the computed eigenvalues.

Select the Enter transformed value check box to enter the value to search around as the transformed value (an eigenfrequency, for example) instead of the corresponding eigenvalue.

The Integration type for eigenvalue solver list and the Number of integration points for eigenvalue solver list are the same as the Integration type for estimation list and the Number of integration points for estimation list described for the Eigenvalue study step. When you choose Automatic in the Integration type for eigenvalue solver list, it uses the Gauss type for real symmetric or Hermitian eigenvalue solvers and the trapezoidal method for other types of solver. When you choose Automatic in Number of integration points for eigenvalue solver, it is 8 for real symmetric or Hermitian eigenvalue solvers and 16 for other types of solvers.

Select the Distribute linear system solution check box to run the FEAST eigenvalue solver in parallel. See Running FEAST in a Parallel MPI Mode for more information.

From the Compute and store left eigenvectors list, choose Automatic (the default), On, or Off. The Automatic option typically is the same as Off, but, depending on the other settings, if needed, the left eigenvector will be computed (and eventually stored). The eigenvectors referred to as just “eigenvectors” are right eigenvectors. A left eigenvector is defined as a row vector XL that satisfy XL A = λLXL . For example, for sensitivity and optimization, when the matrices are nonsymmetric, left eigenvectors will be computed. Also, left eigenvectors can be used for projecting equations in the modal solver.

If the eigenvalue itself appears nonlinearly, the solver reduces the problem to a quadratic approximation around an eigenvalue linearization point. Select the Transform eigenvalue linearization point check box to transform the linearization point value using the selected eigenvalue transformation. Specify the value of the linearization point in the Value of eigenvalue linearization point field (default value: 0).

For other settings, see the Eigenvalue or Eigenfrequency study settings. When the eigenvalue search settings are defined by the study step, these settings, including the ones above except the Relative tolerance, are not available.

From the Linearity list, choose Linear (the default) or Linear perturbation.

Both for linear and nonlinear PDE problems, the eigenvalue problem is that of the linearization about a solution. Such a solution is specified with the Prescribed by list. Select:

Use the Solution list to specify which solution to use if Prescribed by is set to Solution:

Select the Store linearization point and deviation in output check box to store the linearization point and the deviation from that linearization instead of the total solution.

Select an option from the Scaling of eigenvectors list to specify the scaling method used to normalize the eigenvectors. Select:

The eigenvalue solver is an iterative algorithm. Use the Maximum number of eigenvalue iterations field to limit the number of iterations (default: 300).

When you use the ARPACK solver, you can use the Dimension of Krylov space field to control the algorithm’s memory use. The default value of 0 means that the solver sets the dimension automatically to approximately twice the number specified in the Desired number of eigenvalues field in the General section.

In this section you can define constants that can be used as temporary constants in the solver. You can use the constants in the model or to define values for internal solver parameters. These constants overrule any previous definition (for example, from Global Definitions). The constant values are expressions and can, for example, include the range() operator, units, and global expressions. The constant name can be a new or an existing global parameter. The constant is temporary in the sense that it is only defined during the solver run. You cannot override parameters used in the following parts of the model:

Click the Add button () to add a constant and then define its name in the Constant name column and its value (a numerical value or parameter expression) in the Constant value column. By default, any defined parameters are first added as the constant names, but you can change the names to define other constants. Click Delete () to remove the selected constant from the list.

The Log section contains logs of the eigenvalue solver results and properties of the assembled system, including the solver iterations and the total solution time. This log is stored in the Model MPH-file.