Introduces the eigenwalk problem and proves a linear-diameter support-localization theorem for sparse eigenvectors, yielding poly(n)-time classical exact diagonalization for O(1)-sparse extremal eigenvectors of poly(n)-sparse 2^n-dimensional Hamiltonians.
A Multireference Quantum Krylov Algorithm for Strongly Correlated Elec- trons
4 Pith papers cite this work, alongside 9 external citations. Polarity classification is still indexing.
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representative citing papers
A quantum processor prepares a momentum-space matrix product state, and a classical computer later optimizes a real-space correlator from the same measurements, reaching a 3.5 percent calibrated energy error on a 4x4 Hubbard system.
A quantum-classical resolvent method with a new fermionic block-encoding input scheme computes the spectrum and J values of 20O in a truncated sd-shell space, matching classical diagonalization.
SQD needs an exponentially increasing number of computational-basis configurations to approximate ground-state energies of Heisenberg and Hubbard models within fixed accuracy, even when configurations are chosen optimally by probability.
citing papers explorer
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Polynomial-time exact diagonalization via sparse guided eigenwalks
Introduces the eigenwalk problem and proves a linear-diameter support-localization theorem for sparse eigenvectors, yielding poly(n)-time classical exact diagonalization for O(1)-sparse extremal eigenvectors of poly(n)-sparse 2^n-dimensional Hamiltonians.
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Explicitly correlated ground states with a feedback-free variational hybrid algorithm
A quantum processor prepares a momentum-space matrix product state, and a classical computer later optimizes a real-space correlator from the same measurements, reaching a 3.5 percent calibrated energy error on a 4x4 Hubbard system.
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Ab initio many-fermion structure calculations on a quantum computer
A quantum-classical resolvent method with a new fermionic block-encoding input scheme computes the spectrum and J values of 20O in a truncated sd-shell space, matching classical diagonalization.
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A Critical Assessment of the Sample-Based Quantum Diagonalization for Heisenberg and Hubbard Models
SQD needs an exponentially increasing number of computational-basis configurations to approximate ground-state energies of Heisenberg and Hubbard models within fixed accuracy, even when configurations are chosen optimally by probability.