MHB Linear Algebra Rank of a Matrix Problem

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The discussion focuses on proving that the array a(k) = rank(A^(k + 1)) - rank(A^k) is monotonically increasing for an n x n matrix A with complex elements. It highlights that the relationship rank(AB) ≤ min(rank(A), rank(B)) supports the notion of a(k) being non-decreasing. The problem was ultimately solved using the Frobenius Inequality related to matrix rank. Participants express gratitude for the insights shared during the discussion. The conclusion emphasizes the importance of understanding matrix rank properties in linear algebra.
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Let A be a n x n matrix with complex elements. Prove that the a(k) array, with k ∈ ℕ, where a(k) = rank(A^(k + 1)) - rank(A^k), is monotonically increasing.

Thank you! :)
 
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This follows from $\operatorname {rank} (AB)\leq \min(\operatorname {rank} (A),\operatorname {rank} (B))$, if by "increasing" you mean "not decreasing".
 
Finally solved it using the Frobenius Inequality for the rank of a matrix. Thank you anyway!
 
I am studying the mathematical formalism behind non-commutative geometry approach to quantum gravity. I was reading about Hopf algebras and their Drinfeld twist with a specific example of the Moyal-Weyl twist defined as F=exp(-iλ/2θ^(μν)∂_μ⊗∂_ν) where λ is a constant parametar and θ antisymmetric constant tensor. {∂_μ} is the basis of the tangent vector space over the underlying spacetime Now, from my understanding the enveloping algebra which appears in the definition of the Hopf algebra...

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