Quantum oblique eigenprojection
This work shows how a quantum computer can perform an oblique eigenprojection for matrices with complex eigenvalues, overcoming limitations where standard polynomial methods fail due to analytic obstructions. By using a two-sided block preconditioning based on the discrete Fourier transform of the matrix resolvent, the method achieves a normalization factor close to its theoretical optimum while maintaining near-linear query complexity.