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

Fuente: arXiv
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Auteurs principaux: Pierce, Karl, Aziz, Muhammad Talha, Shee, Avijit, Faulstich, Fabian M.
Format: Preprint
Publié: 2026
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author Pierce, Karl
Aziz, Muhammad Talha
Shee, Avijit
Faulstich, Fabian M.
author_facet Pierce, Karl
Aziz, Muhammad Talha
Shee, Avijit
Faulstich, Fabian M.
contents 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 framework. Using CPD, we both factorize the three dominant order-three density-fitting two-electron integral (DF TEI) tensors and develop a novel formulation that reduces the storage complexity of the low-level solver from ${O}(N^3)$ to $O(NR)$, where $R$ is the CPD rank, and the computational scaling of the most time-consuming contractions from ${O}(N^4)$ to ${O}(NR^2)$. We provide benchmarks on representative chemical environments, namely water clusters $\mathrm{(H_2O)_n}$ with $n = 1$ to $6$ and linear alkane chains $\mathrm{C_nH_{2n+2}}$ with $n = 1$ to $6$. For both test sets, using the CPD-compressed DF TEI tensors reproduces the DF reference convergence behavior of the low-level solver, the subsequent high-level step, and the fully self-consistent MPCC iterations, while introducing only small, rank-controlled shifts in absolute energies. At a fixed tolerance in the absolute MPCC energy, the CP ranks required for these tensor approximations increase linearly with system size. Chemically relevant energy differences are likewise preserved, as demonstrated for water-cluster dissociation energies and in a proof-of-concept embedding calculation of methane in a four-water cluster.
format Preprint
id arxiv_https___arxiv_org_abs_2602_15129
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A CPD-enabled low-scaling environment solver in a coupled cluster based static quantum embedding theory
Pierce, Karl
Aziz, Muhammad Talha
Shee, Avijit
Faulstich, Fabian M.
Chemical Physics
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 framework. Using CPD, we both factorize the three dominant order-three density-fitting two-electron integral (DF TEI) tensors and develop a novel formulation that reduces the storage complexity of the low-level solver from ${O}(N^3)$ to $O(NR)$, where $R$ is the CPD rank, and the computational scaling of the most time-consuming contractions from ${O}(N^4)$ to ${O}(NR^2)$. We provide benchmarks on representative chemical environments, namely water clusters $\mathrm{(H_2O)_n}$ with $n = 1$ to $6$ and linear alkane chains $\mathrm{C_nH_{2n+2}}$ with $n = 1$ to $6$. For both test sets, using the CPD-compressed DF TEI tensors reproduces the DF reference convergence behavior of the low-level solver, the subsequent high-level step, and the fully self-consistent MPCC iterations, while introducing only small, rank-controlled shifts in absolute energies. At a fixed tolerance in the absolute MPCC energy, the CP ranks required for these tensor approximations increase linearly with system size. Chemically relevant energy differences are likewise preserved, as demonstrated for water-cluster dissociation energies and in a proof-of-concept embedding calculation of methane in a four-water cluster.
title A CPD-enabled low-scaling environment solver in a coupled cluster based static quantum embedding theory
topic Chemical Physics
url https://arxiv.org/abs/2602.15129