Man pages for eigencore
Certified Partial Eigenvalue and Singular Value Computation
| adjoint | Return the adjoint operator. |
| alpha_beta | Extract homogeneous generalized coordinates. |
| as_operator | Convert an object to an eigencore operator. |
| auto | Automatic solver choice. |
| backward_error | Extract backward-error diagnostics. |
| benchmark_eigen_methods | Benchmark eigen methods against base and optional references. |
| benchmark_svd_methods | Benchmark SVD methods against base and optional references. |
| b_orthogonalize | Orthogonalize columns in the B-inner product. |
| both_ends | Target both algebraic ends. |
| center | Center an operator by rows or columns. |
| certificate | Extract a result certificate. |
| check_adjoint | Check an operator adjoint identity. |
| cholqr2 | Cholesky QR with a corrective second pass. |
| compose | Compose two operators. |
| crossprod_operator | Create A^* A as an operator. |
| diagnostics | Extract diagnostics. |
| eigencore-package | eigencore |
| eigen_problem | Define an eigenproblem. |
| eig_full | Compute a full dense eigendecomposition |
| eig_partial | Compute a partial eigendecomposition. |
| eigs | RSpectra-compatible eigen shim. |
| eigs_sym | RSpectra-compatible symmetric eigen shim. |
| euclidean | Euclidean vector space descriptor. |
| general | General operator structure descriptor. |
| generalized_schur | Compute a dense generalized Schur decomposition |
| generalized_svd | Compute a dense generalized singular value decomposition |
| golub_kahan | Golub-Kahan bidiagonalization method descriptor. |
| hermitian | Hermitian/symmetric operator structure descriptor. |
| lanczos | Hermitian Lanczos method descriptor. |
| largest | Target the largest algebraic values. |
| largest_imaginary | Target the largest imaginary part. |
| largest_magnitude | Target the largest values by magnitude. |
| largest_real | Target the largest real part. |
| left_vectors | Extract left singular vectors or left eigenvectors. |
| linear_operator | Create a block-native linear operator. |
| lobpcg | LOBPCG method descriptor. |
| mgs2 | Modified Gram-Schmidt with two passes. |
| nearest | Target values nearest a shift. |
| operator_scale | Multiply an operator by a scalar. |
| operator_sum | Sum compatible operators. |
| orthogonality_loss | Measure orthogonality loss. |
| plan_solver | Plan a solver for a problem. |
| randomized | Randomized SVD method descriptor. |
| rayleigh_ritz | Rayleigh-Ritz projection in a trial basis. |
| residuals | Extract residual diagnostics. |
| right_vectors | Extract right singular vectors. |
| scale_cols | Scale operator columns. |
| scale_rows | Scale operator rows. |
| shifted_cholesky_preconditioner | Shifted Cholesky preconditioner. |
| shifted_diagonal_preconditioner | Shifted diagonal preconditioner. |
| shifted_tridiagonal_preconditioner | Shifted tridiagonal preconditioner. |
| shift_invert | Shift-invert method descriptor. |
| smallest | Target the smallest algebraic values. |
| smallest_imaginary | Target the smallest imaginary part. |
| smallest_magnitude | Target the smallest values by magnitude. |
| smallest_real | Target the smallest real part. |
| solve.eigencore_eigen_problem | Solve a planned eigenproblem. |
| solve.eigencore_svd_problem | Solve a planned SVD problem. |
| svd_partial | Compute a partial singular-value decomposition. |
| svd_problem | Define an SVD problem. |
| svds | RSpectra-compatible SVD shim. |
| symmetric_operator | Mark an operator as symmetric/Hermitian. |
| validate_eigen_accuracy | Validate eigencore eigen results against a dense oracle. |
| validate_svd_accuracy | Validate eigencore SVD results against base::svd(). |
| values | Extract computed values. |
| vectors | Extract eigenvectors. |
