A discretization-plus-coarse-graining scheme turns continuous-space interacting particles into a tensor-network-representable lattice model, enabling partition-function calculations for the 2D hard-disk problem.
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A transposition trick is introduced to impose lattice-reflection symmetry in TNRG projective truncations and entanglement filtering, enabling extraction of scaling dimensions separately in each symmetry sector for 2D and 3D systems.
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Statistical mechanics in continuous space with tensor network methods
A discretization-plus-coarse-graining scheme turns continuous-space interacting particles into a tensor-network-representable lattice model, enabling partition-function calculations for the 2D hard-disk problem.
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Lattice-reflection symmetry in tensor-network renormalization group with entanglement filtering in two and three dimensions
A transposition trick is introduced to impose lattice-reflection symmetry in TNRG projective truncations and entanglement filtering, enabling extraction of scaling dimensions separately in each symmetry sector for 2D and 3D systems.