Loss-aware natural gradient variants are introduced by embedding the loss hypersurface in a statistical manifold or using quantum state overlaps, yielding conformal updates that adjust effective step size.
Carrasco-Codina, E
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A Slater-determinant-to-qubit mapping enables low-depth VQE circuits for nuclear shell model calculations on NISQ hardware, achieving less than 4% deviation from classical predictions after zero-noise extrapolation for nuclei including lithium isotopes and 210Pb.
A hybrid quantum-classical method computes accurate Green's functions for the pairing model across the normal-to-superfluid transition by combining variational ground-state preparation with quantum subspace expansion for neighboring particle numbers.
citing papers explorer
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Loss-aware state space geometry for quantum variational algorithms
Loss-aware natural gradient variants are introduced by embedding the loss hypersurface in a statistical manifold or using quantum state overlaps, yielding conformal updates that adjust effective step size.
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A low-circuit-depth quantum computing approach to the nuclear shell model
A Slater-determinant-to-qubit mapping enables low-depth VQE circuits for nuclear shell model calculations on NISQ hardware, achieving less than 4% deviation from classical predictions after zero-noise extrapolation for nuclei including lithium isotopes and 210Pb.
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Quantum simulations of Green's functions for small superfluid systems
A hybrid quantum-classical method computes accurate Green's functions for the pairing model across the normal-to-superfluid transition by combining variational ground-state preparation with quantum subspace expansion for neighboring particle numbers.