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About this paper
Pilsung Kang
The authors test whether reorganizing Hamiltonian-term gradient contributions improves minimization in variational quantum algorithms. They compare projection-based directions with raw-gradient updates using exact statevector simulations of transverse-field Ising models. Under matched five-probe, norm-matched searches, raw-gradient line search achieved lower energy in HEA by 0.267 units and favored HVA by 0.034, practically unresolved. The conclusion is limited to these tested controls.
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