numerical-linear-algebra-toolkit

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High-performance numerical linear algebra operations

General

What this skill does


# Numerical Linear Algebra Toolkit

## Purpose

Provides high-performance numerical linear algebra operations for scientific computing and mathematical analysis.

## Capabilities

- Matrix decompositions (LU, QR, SVD, Cholesky, Schur)
- Eigenvalue/eigenvector computation
- Sparse matrix operations
- Iterative solvers (CG, GMRES, BiCGSTAB)
- Condition number estimation
- Error analysis and bounds

## Usage Guidelines

1. **Decomposition Selection**: Choose appropriate factorization for the problem
2. **Sparsity Exploitation**: Use sparse formats for large sparse matrices
3. **Iterative Methods**: Apply iterative solvers for very large systems
4. **Conditioning**: Assess and monitor condition numbers

## Tools/Libraries

- LAPACK
- BLAS
- SuiteSparse
- Eigen

Files: 1

Size: 1.0 KB

Complexity: 8/100

Category: General

Source: https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/science/mathematics/skills/numerical-linear-algebra-toolkit

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