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I'm interested in finding the expected rank of asome random matrix $A$, where $A$ is roughly a sum of matrices of the form $UBU^{\dagger}$, with $U$ being random taken from some(I don't want to specify its distribution right now, since my question makes sense in general).

Computing $\mathbb{E} \ \mathrm{rk}(A)$ is usually infeasible, as rank is a rather awful function to consider or optimize etc. Are there quantities which could serve as proxies for the rank, but whose averages would be easier to compute in this setting? In other words, I'm looking for functions $f(A)$ such that $\mathbb{E}f(A)$ can be computed and $f(A)$ is a reasonable approximation to $\mathrm{rk}(A)$. An example would be $\mathrm{tr}(A)$, which would be close to the rank if the eigenvalues of $A$ are close to $1$.

Since replacing rank with some nicer (e.g. convex) function seems to be a common approach e.g. in optimization, I'd be also interested in references.

I'm interested in finding the expected rank of a random matrix $A$, where $A$ is roughly a sum of matrices of the form $UBU^{\dagger}$, with $U$ being random taken from some distribution.

Computing $\mathbb{E} \ \mathrm{rk}(A)$ is infeasible, as rank is a rather awful function to consider or optimize etc. Are there quantities which could serve as proxies for the rank, but whose averages would be easier to compute in this setting? In other words, I'm looking for functions $f(A)$ such that $\mathbb{E}f(A)$ can be computed and $f(A)$ is a reasonable approximation to $\mathrm{rk}(A)$. An example would be $\mathrm{tr}(A)$, which would be close to the rank if the eigenvalues of $A$ are close to $1$.

Since replacing rank with some nicer (e.g. convex) function seems to be a common approach e.g. in optimization, I'd be also interested in references.

I'm interested in finding the expected rank of some random matrix $A$ (I don't want to specify its distribution right now, since my question makes sense in general).

Computing $\mathbb{E} \ \mathrm{rk}(A)$ is usually infeasible, as rank is a rather awful function to consider or optimize etc. Are there quantities which could serve as proxies for the rank, but whose averages would be easier to compute in this setting? In other words, I'm looking for functions $f(A)$ such that $\mathbb{E}f(A)$ can be computed and $f(A)$ is a reasonable approximation to $\mathrm{rk}(A)$. An example would be $\mathrm{tr}(A)$, which would be close to the rank if the eigenvalues of $A$ are close to $1$.

Since replacing rank with some nicer (e.g. convex) function seems to be a common approach e.g. in optimization, I'd be also interested in references.

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Expected rank - computable approximations

I'm interested in finding the expected rank of a random matrix $A$, where $A$ is roughly a sum of matrices of the form $UBU^{\dagger}$, with $U$ being random taken from some distribution.

Computing $\mathbb{E} \ \mathrm{rk}(A)$ is infeasible, as rank is a rather awful function to consider or optimize etc. Are there quantities which could serve as proxies for the rank, but whose averages would be easier to compute in this setting? In other words, I'm looking for functions $f(A)$ such that $\mathbb{E}f(A)$ can be computed and $f(A)$ is a reasonable approximation to $\mathrm{rk}(A)$. An example would be $\mathrm{tr}(A)$, which would be close to the rank if the eigenvalues of $A$ are close to $1$.

Since replacing rank with some nicer (e.g. convex) function seems to be a common approach e.g. in optimization, I'd be also interested in references.