You want to solve Ax = b where A is sparse and symmetric positive definite. Which SciPy solver is best suited for this?

hard📝 Application Q9 of 15

SciPy - Sparse Matrices (scipy.sparse)

You want to solve Ax = b where A is sparse and symmetric positive definite. Which SciPy solver is best suited for this?

Ainv

Bspsolve

Clu_solve

Dcg (Conjugate Gradient)

Step-by-Step Solution

Solution:

Step 1: Identify matrix properties
A is sparse and symmetric positive definite, ideal for iterative solvers.
Step 2: Choose solver optimized for this case
The conjugate gradient method (cg) is efficient for such matrices and available in SciPy.
Final Answer:
cg (Conjugate Gradient) -> Option D
Quick Check:
Symmetric positive definite sparse matrix = use cg solver [OK]

Quick Trick: Use cg for symmetric positive definite sparse matrices [OK]

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