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(simulation) Is there any advantage of similarity transformation over unitary transformation in terms of reducing negative elements in matrix?
(simulation) develop algorithm for minimizing ground state energies for absolute matrix
Implement reweighting method for reduce negative sign (turns out that it is meeningless)
advantage of unitary matrix over orthogonal matrix
Implement riemannian optimization
Frustration-free model
(Theoretically) All frustration-free models can transform into the non-negative-sign models at zero temperature?
(Theoretically) If absolute map of local hamiltonian has the same ground-state energies spectrum, then the model after absolute map is also a frustration-free model?
Algorithm
(simulation) Is there any advantage of similarity transformation over unitary transformation in terms of reducing negative elements in matrix?
(simulation) develop algorithm for minimizing ground state energies for absolute matrix
Implement reweighting method for reduce negative sign (turns out that it is meeningless)
advantage of unitary matrix over orthogonal matrix
Implement riemannian optimization
Frustration-free model
(Theoretically) All frustration-free models can transform into the non-negative-sign models at zero temperature?
(Theoretically) If absolute map of local hamiltonian has the same ground-state energies spectrum, then the model after absolute map is also a frustration-free model?
(simulation) Apply algorithm