Put . We use the following closed-range lemma:Indeed,Away from this kernel, zero is separated from the spectrum of the positive self-adjoint operator exactly whenfor some . This is equivalent to closed range. Zero is then absent from the essential spectrum exactly when . Similarly,because measures the cokernel.
Applying the lecture definitions of the three essential spectra of a closed operator now givesand
If is normal, so is . The spectral theorem givesand maps the spectral mass of at exactly to the spectral mass of at . Thus zero is isolated with finite multiplicity for exactly when is an isolated eigenvalue of finite multiplicity for . Consequently
Normality is essential. Let be the unilateral shift and take . Its spectrum is the closed unit disk, so is not in the discrete spectrum. Butwhose zero eigenvalue is isolated and simple. Hence while .
Set . The squares of the singular values of are the eigenvalues of the finite-dimensional positive operatorThe Rayleigh-Ritz variational principle and its min-max characterization show that, as the trial space grows, its -st eigenvalue counted upward cannot increase. Therefore, for each fixed ,once . Being nonnegative, it has a limitThe core assumption ensures that these Ritz limits are the min-max values of , rather than values for a smaller closed restriction.
- If , then for some , so every .
- If is a discrete eigenvalue of multiplicity , exactly
- If lies in the essential spectrum, the min-max principle or an orthonormal Weyl sequence gives for every fixed .
For , defineIn the first case for all sufficiently large . In the second case its first summands tend to one and all remaining summands eventually vanish, so . In the third case . These are exactly the three values in the definition of , and hence
Letand, for , form the finite rectangular matrixEvery entry is available from . Let its singular values, padded and ordered as in the question, beFor fixed , Parseval's identity gives convergence of the finite Gram matrices:as . Consequently, ifthenSingular values are Lipschitz under scalar shifts, so the subsequent limit and part ii give
Define the finite-information arithmetic functionsFinite-matrix singular values can be obtained by arithmetic eigenvalue approximation, so these functions form the required arithmetic tower using only . The two inner limits recover the limiting singular values, while the outer limit is exactly the multiplicity formula from part ii:
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