ROQAM formulates Green's function estimation via orthogonal polynomials to preserve Hessenberg structure under finite precision, enabling lower precision with depth and outperforming QSVD by orders of magnitude in resource estimates for a quantum impurity model.
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Pith papers citing it
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quant-ph 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
n-regular block encodings let QSP apply degree-n polynomials directly to the eigenvalues of any square matrix, with an efficient conversion from standard block encodings.
A single-ancilla Power-Cosine QSP filter on time-evolution operators achieves deterministic many-body ground state preparation with exponential excited-state suppression and O(Δ^{-2} log(1/ε)) depth scaling.
citing papers explorer
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Estimating Green's functions with a robust quantum Arnoldi method
ROQAM formulates Green's function estimation via orthogonal polynomials to preserve Hessenberg structure under finite precision, enabling lower precision with depth and outperforming QSVD by orders of magnitude in resource estimates for a quantum impurity model.
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Quantum Eigenvalue Transformations for Arbitrary Matrices
n-regular block encodings let QSP apply degree-n polynomials directly to the eigenvalues of any square matrix, with an efficient conversion from standard block encodings.
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Deterministic Ground State Preparation via Power-Cosine Filtering of Time Evolution Operators
A single-ancilla Power-Cosine QSP filter on time-evolution operators achieves deterministic many-body ground state preparation with exponential excited-state suppression and O(Δ^{-2} log(1/ε)) depth scaling.