Use the uncentered sample covariance matrix
Then and, simultaneously for every unit vector ,
Here and the effective rank of a covariance matrix satisfies
The Gaussian sample-covariance operator-norm bound therefore gives, with probability at least ,
Under the assumed upper bound on , the second term is at most the first. Thus the stronger simultaneous estimate
holds for every . Squaring and using that the displayed ratio is at most one gives the inequality requested in the question after enlarging the universal constant .

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