Transfer Matrix and Lattice Dilatation Operator for High-Quality Fixed Points in Tensor Network Renormalization Group
Nikolay Ebel, Tom Kennedy, Slava Rychkov

TL;DR
This paper compares transfer matrix and lattice dilatation operator methods for extracting scaling dimensions from fixed points in tensor network RG studies of 2D lattice models, showing excellent agreement with conformal field theory predictions.
Contribution
It introduces extensions to TM and LDO methods to determine CFT operator spins and compares their effectiveness at high precision in tensor network RG fixed points.
Findings
TM and LDO methods perform equally well with comparable resources.
Excellent agreement with CFT for scaling dimensions and spins up to 4.125.
Non-universal eigenvalues are linked to the Jacobian's equivalence to the LDO operator.
Abstract
Tensor network renormalization group maps study critical points of 2d lattice models like the Ising model by finding the fixed point of the RG map. In a prior work arXiv:2408.10312 we showed that by adding a rotation to the RG map, the Newton method could be implemented to find an extremely accurate fixed point. For a particular RG map (Gilt-TNR) we studied the spectrum of the Jacobian of the RG map at the fixed point and found good agreement between the eigenvalues corresponding to relevant and marginal operators and their known exact values. In this companion work we use two further methods to extract many more scaling dimensions from this Newton method fixed point, and compare the numerical results with the predictions of conformal field theory (CFT). The first method is the well-known transfer matrix (TM), while the second method we refer to as the lattice dilatation operator (LDO).…
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Taxonomy
TopicsBlack Holes and Theoretical Physics · Cosmology and Gravitation Theories · Quantum many-body systems
