Tikhonov regularization of the moving Gram matrix stabilizes discretization of projected gradient flows for equality-constrained bilinear quantum control, preserving monotonic ascent with O(ε²) constraint drift and a CFL-type discrete stability criterion.
Wright.Numerical Optimization
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YAND defines optimization search directions via the equi-affine normal of level sets, proving invariance under volume-preserving affine maps and global convergence for smooth objectives.
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Tikhonov-regularised projected gradient flow for equality-constrained bilinear quantum control
Tikhonov regularization of the moving Gram matrix stabilizes discretization of projected gradient flows for equality-constrained bilinear quantum control, preserving monotonic ascent with O(ε²) constraint drift and a CFL-type discrete stability criterion.
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Yau's Affine Normal Descent: Algorithmic Framework and Convergence Analysis
YAND defines optimization search directions via the equi-affine normal of level sets, proving invariance under volume-preserving affine maps and global convergence for smooth objectives.