A diagonalization-free Krylov (bi-Lanczos/Arnoldi) construction yields exact or truncated adiabatic gauge potentials for non-Hermitian STA, reducing them to sparse matrix equations that suppress nonadiabatic excitations and detect PT/EP transitions.
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Analytical Pauli-string coefficients plus multistage state refinement let tensor networks find low eigenstates of million-dimensional Laplacians with high fidelity on 20 qubits.
HAVQDS achieves higher approximation ratios on 6-14 qubit SK instances than adiabatic or CD methods while cutting CNOT counts by 1-2 orders of magnitude.
A penalty-free, fully quantum algorithm is proposed for finding ground and excited states of many-body Hamiltonians.
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Shortcuts to Adiabaticity for non-Hermitian systems in Krylov Space
A diagonalization-free Krylov (bi-Lanczos/Arnoldi) construction yields exact or truncated adiabatic gauge potentials for non-Hermitian STA, reducing them to sparse matrix equations that suppress nonadiabatic excitations and detect PT/EP transitions.
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Efficient Pauli-decomposition and multistage state-refinement for tensor network based differential equation solver
Analytical Pauli-string coefficients plus multistage state refinement let tensor networks find low eigenstates of million-dimensional Laplacians with high fidelity on 20 qubits.
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Hybrid Real-Imaginary Time Evolution for Low-Depth Hamiltonian Simulation in Quantum Optimization
HAVQDS achieves higher approximation ratios on 6-14 qubit SK instances than adiabatic or CD methods while cutting CNOT counts by 1-2 orders of magnitude.
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A penalty-free quantum algorithm to find energy eigenstates
A penalty-free, fully quantum algorithm is proposed for finding ground and excited states of many-body Hamiltonians.