Alternating cross interpolation performs elementwise operations on tensor trains in O(χ³) time with error control, improving on the standard O(χ⁴) scaling when output ranks are controlled.
Solving the gross-pitaevskii equation with quantic tensor trains: Ground states and nonlinear dynamics
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An adaptive patching method exploits block-sparse QTT structures to reduce computational costs for tensor contractions and enables efficient evaluation of bubble diagrams and Bethe-Salpeter equations.
A tensor network algorithm computes momentum-resolved spectral functions for large non-periodic super-moiré systems by mapping tight-binding problems to solvable quantum many-body simulations using kernel polynomial methods and quantum Fourier transforms.
Tailoring tensor network algorithms to the scale hierarchy in quantics representation produces faster, more robust solvers for high-dimensional linear and eigenvalue PDE problems.
Tensor-network representation of the density matrix via Chebyshev algorithm computes real-space topological markers in C8 and C10 quasicrystals and Chern mosaics at scales of hundreds of millions of sites.
citing papers explorer
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Tensor network approach to momentum-resolved spectroscopy in non-periodic super-moir\'e systems
A tensor network algorithm computes momentum-resolved spectral functions for large non-periodic super-moiré systems by mapping tight-binding problems to solvable quantum many-body simulations using kernel polynomial methods and quantum Fourier transforms.
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Tensor network method for real-space topology in quasicrystal Chern mosaics
Tensor-network representation of the density matrix via Chebyshev algorithm computes real-space topological markers in C8 and C10 quasicrystals and Chern mosaics at scales of hundreds of millions of sites.