Hello SymPy Community,
My name is Temiloluwa, and I would like to propose the addition of more matrix decomposition methods (*Schur, Polar, and Hermite Decomposition) *as my project idea <https://github.com/sympy/sympy/wiki/GSoC-Ideas#idea-prompts>for Google Summer of Code (GSoC) 2025. I have successfully gotten a PR <https://github.com/sympy/sympy/pull/27352> in for a *QR decomposition method* for DomainMatrix and I am currently finalizing a *PLDU decomposition* and a *fraction-free QR decomposition (QRD) *pull request <https://github.com/sympy/sympy/pull/27423> for DomainMatrix, aimed at improving the *GramSchmidt process* >From my exploration of the SymPy codebase, I have observed that the few matrix decomposition <https://github.com/sympy/sympy/blob/master/sympy/matrices/decompositions.py> methods that exist are *LU, QR, **Cholesky *variants and some others to name a few. However, important methods like: - *Schur Decomposition* (A=QTQH) - *Polar Decomposition* (A=UP) - *Hermite Decomposition* (A=LDLH) are yet to be implemented. Integrating these decompositions would enhance SymPy’s linear algebra capabilities, particularly in *eigenvalue computation and numerical stability*. I look forward to discussing this further and receiving feedback from the community. Best regards, *Temiloluwa* -- You received this message because you are subscribed to the Google Groups "sympy" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion visit https://groups.google.com/d/msgid/sympy/008ee22b-e3c3-40b0-8565-18e2f1aef17cn%40googlegroups.com.
