An analytical Hessian-vector product kernel for arbitrary linear map compositions in tensor networks is derived via recursive tangent-state propagation, enabling scalable Riemannian trust-region optimization with major fidelity gains on spin-chain circuits.
Lanczos, An iteration method for the solution of the eigenvalue problem of linear differential and integral op- erators, J
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A Krylov staggering parameter derived from Lanczos coefficients analytically distinguishes topological phases in the short-range Kitaev model and tracks boundary versus bulk control of the gap in long-range cases.
A dipole-conserving spin chain with Ising interactions stabilizes antiferromagnetic dipole order at the level of spin pairs and undergoes transitions to conventional antiferromagnetic or ferromagnetic order depending on interaction sign and strength.
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Hessian-vector products for tensor networks via recursive tangent-state propagation
An analytical Hessian-vector product kernel for arbitrary linear map compositions in tensor networks is derived via recursive tangent-state propagation, enabling scalable Riemannian trust-region optimization with major fidelity gains on spin-chain circuits.
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Long-Range Pairing in the Kitaev Model: Krylov Subspace Signatures
A Krylov staggering parameter derived from Lanczos coefficients analytically distinguishes topological phases in the short-range Kitaev model and tracks boundary versus bulk control of the gap in long-range cases.
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Fractonic Constraints and Magnetic Order in a Dipole-Conserving Spin Chain
A dipole-conserving spin chain with Ising interactions stabilizes antiferromagnetic dipole order at the level of spin pairs and undergoes transitions to conventional antiferromagnetic or ferromagnetic order depending on interaction sign and strength.
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