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20202026
most citedRobust approximation of tensor networks: application to grid-free tensor factorization of the Coulomb interaction

27 citations · 38 across the 6 of their papers we have counts for

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physics.chem-ph2026

A CPD-enabled low-scaling environment solver in a coupled cluster based static quantum embedding theory

Karl Pierce, Muhammad Talha Aziz, Avijit Shee +1

We incorporate a canonical polyadic decomposition (CPD) based low-level solver as a means to accelerate the environment-level solver for the recently developed MPCC embedding frame…

physics.chem-ph2025

Towards Using Matrix-Free Tensor Decompositions to Systematically Improve Approximate Tensor-Networks

Karl Pierce

We investigate a novel approach to approximate tensor-network contraction via the exact, matrix-free decomposition of full tensor-networks. We study this method as a means to elimi…

physics.chem-ph2025

Using Matrix-Free Tensor-Network Optimizations to Construct a Reduced-Scaling and Robust Second-Order Møller-Plesset Theory

Karl Pierce, Miguel Morales

We investigate the efficient combination of the canonical polyadic decomposition (CPD) and tensor hyper-contraction (THC) approaches. We first present a novel low-cost CPD solver w…

physics.chem-ph2022★ 11 cited

Efficient construction of canonical polyadic approximations of tensor networks

Karl Pierce, Edward F Valeev

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 co…

physics.chem-ph2020★ 27 cited

Robust approximation of tensor networks: application to grid-free tensor factorization of the Coulomb interaction

Karl Pierce, Varun Rishi, Edward F. Valeev

Approximation of a tensor network by approximating (e.g., factorizing) one or more of its constituent tensors can be improved by canceling the leading-order error due to the consti…