Q.If and are symmetric matrices, prove that is a skew symmetric matrix.
For symmetric matrices and , the commutator is always skew-symmetric because its transpose equals its own negative: .
The key here is to understand what symmetric and skew-symmetric matrices mean in terms of transposes. A symmetric matrix equals its own transpose: . A skew-symmetric matrix equals the negative of its transpose: .
When you multiply symmetric matrices, the product is not necessarily symmetric — but its transpose has a neat property: (since and ). This is the engine that drives the proof.
Let’s walk through it step by step.
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Start with the transpose of the expression.
We want to check if is skew-symmetric. That means we need to compute and see if it equals .
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Use the transpose of a sum/difference.
The transpose of a sum is the sum of transposes:
- Apply the product rule for transposes. Remember: . So:
- Substitute the symmetry condition. Since and are symmetric, and . This gives:
- Put it together.
- Factor out a negative sign. Notice that . Therefore:
This is exactly the definition of a skew-symmetric matrix: a matrix such that .
A common mistake is to assume itself is symmetric just because and are. That’s false — is symmetric only if and commute (). The problem specifically uses the difference , which is zero when they commute, and skew-symmetric otherwise.
This result is actually a special case of a deeper fact: for any square matrices, is always traceless and, when and are symmetric, it’s skew-symmetric. This commutator structure appears everywhere in quantum mechanics and Lie algebra theory.
The matrix is skew-symmetric because .
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