method-ed

Perform exact diagonalization of a many-body quantum Hamiltonian by constructing a symmetry-adapted basis and applying sparse matrix solvers to extract exact eigenvalues and eigenvectors. This handles Hilbert space dimensions up to your memory limit.

The best way to benchmark approximate methods like DMRG is using exact diagonalization as a rigorous oracle. It eliminates approximation errors for small-scale clusters and provides a definitive ground state and low-lying spectrum to verify accuracy.

Compute exact real-time quench evolution and finite-temperature estimators for quantum systems using Krylov time evolution and FTLM/TPQ estimators. This enables precise dynamics and thermodynamics calculations for small-scale quantum systems.

Yes, you can analyze level statistics and ETH diagnostics using exact diagonalization. It computes the full spectrum of many-body quantum Hamiltonians, allowing for detailed analysis of scar towers and thermalization properties.

Yes, exact diagonalization supports symmetry-resolved sectors for quantum many-body systems. It requires symmetry-adapted basis construction to efficiently manage Hilbert space dimensions within the available memory limit.

The primary limitation of exact diagonalization is the Hilbert space dimension, which is constrained by your system's memory limit. It is restricted to small-scale quantum systems and requires sparse matrix solvers to manage computational overhead.