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.
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Develops a translationally invariant tensor network algorithm to calculate disorder-averaged quantities in infinite random spin chains without sampling, benchmarked on the random transverse-field Ising model at its infinite-randomness critical point.
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Fast elementwise operations on tensor trains with alternating cross interpolation
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.
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Extracting average properties of disordered spin chains with translationally invariant tensor networks
Develops a translationally invariant tensor network algorithm to calculate disorder-averaged quantities in infinite random spin chains without sampling, benchmarked on the random transverse-field Ising model at its infinite-randomness critical point.