CDFCI: High-Performance Parallel Software for Quantum Many-Body Eigenvalue Problems
Abstract
CDFCI is a shared-memory parallel numerical program for computing low-lying eigenpairs of large-scale, non-relativistic fermionic Hamiltonians. The software is designed to handle a broad class of many-body quantum models, including both ab initio electronic structure Hamiltonians and lattice-based Hamiltonians arising in condensed matter physics. CDFCI combines an efficient coordinate-descent-based selected configuration interaction algorithm with dedicated parallelization strategies, achieving high performance on modern multi-core architectures. Benchmark results on representative quantum chemistry and condensed matter test cases demonstrate that CDFCI attains state-of-the-art accuracy with competitive performance compared to established selected configuration interaction (such as CIPSI or SHCI) and DMRG implementations. The software is open-source, extensively documented, and provides a Python interface for seamless integration with PySCF and other many-body simulation workflows.
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BibTeX
@misc{zhang2026cdfci,
title = {{CDFCI: High-Performance Parallel Software for Quantum Many-Body Eigenvalue Problems}},
author = {Yuejia Zhang and Zhe Wang and Jianfeng Lu and Yingzhou Li},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2605.04483},
eprint = {2605.04483},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2605.04483},
}
RIS
TY - UNPB
TI - CDFCI: High-Performance Parallel Software for Quantum Many-Body Eigenvalue Problems
AU - Yuejia Zhang
AU - Zhe Wang
AU - Jianfeng Lu
AU - Yingzhou Li
PY - 2026
DA - 2026/09/17
PB - arXiv
DO - 10.48550/arxiv.2605.04483
UR - https://arxiv.org/abs/2605.04483
AB - CDFCI is a shared-memory parallel numerical program for computing low-lying eigenpairs of large-scale, non-relativistic fermionic Hamiltonians. The software is designed to handle a broad class of many-body quantum models, including both ab initio electronic structure Hamiltonians and lattice-based Hamiltonians arising in condensed matter physics. CDFCI combines an efficient coordinate-descent-based selected configuration interaction algorithm with dedicated parallelization strategies, achieving high performance on modern multi-core architectures. Benchmark results on representative quantum chemistry and condensed matter test cases demonstrate that CDFCI attains state-of-the-art accuracy with competitive performance compared to established selected configuration interaction (such as CIPSI or SHCI) and DMRG implementations. The software is open-source, extensively documented, and provides a Python interface for seamless integration with PySCF and other many-body simulation workflows.
ER -