Efficient construction of canonical polyadic approximations of tensor networks
Karl Pierce, Edward F Valeev

TL;DR
This paper introduces an efficient method for constructing canonical polyadic (CP) tensor decompositions of tensor networks, significantly reducing computational complexity and improving accuracy for electronic structure calculations.
Contribution
It presents a novel approach leveraging tensor network structure to reduce CP decomposition complexity from O(n^4) to O(n^3) for Coulomb tensors, enhancing efficiency in many-body electronic structure.
Findings
Reduced CP construction complexity by up to 2 orders of magnitude.
Achieved more accurate CP approximations than existing methods.
Provided robust initial guesses for CP factors using SQ decomposed tensors.
Abstract
We consider the problem of constructing a canonical polyadic (CP) decomposition for a tensor network, rather than a single tensor. We illustrate how it is possible to reduce the complexity of constructing an approximate CP representation of the network by leveraging its structure in the course of the CP factor optimization. The utility of this technique is demonstrated for the order-4 Coulomb interaction tensor approximated by 2 order-3 tensors via an approximate generalized square-root (SQ) factorization, such as density fitting or (pivoted) Cholesky. The complexity of constructing a 4-way CP decomposition is reduced from (for the non-approximated Coulomb tensor) to for the SQ-factorized tensor, where and are the basis and CP ranks, respectively. This reduces the cost of constructing the CP approximation of…
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Taxonomy
TopicsTensor decomposition and applications · Advanced NMR Techniques and Applications · Quantum, superfluid, helium dynamics
