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Check whether a symmetric matrix is negative semi-definite, a relaxed version of negative definite that allows zero.

How It Works

How Negative Semi-Definite Matrix Checker Works

Semi-definiteness is a looser condition than definiteness — it allows borderline zero cases, not just strictly negative ones. Correctly testing it requires checking every principal minor (not just the leading ones), confirming that all odd-order principal minors are zero or negative and all even-order ones are zero or positive.

FAQ

Frequently Asked Questions

Why does semi-definite need more checks than definite?
For strict definiteness, checking the leading principal minors alone is sufficient. For the semi-definite (borderline-allowed) case, that shortcut no longer holds — every principal minor, not just the leading ones, has to be checked to get a correct answer.
Where does negative semi-definiteness come up?
It's the standard second-order condition for a local maximum in optimization problems where the maximum might sit along a flat ridge rather than a sharp peak.