CDFCI：高性能并行软件用于多体大尺度本征值问题
CDFCI: High-Performance Parallel Software for Quantum Many-Body Eigenvalue Problems
AI总结：
CDFCI通过高效的坐标下降法和并行策略，解决大规模非相对论费米哈密顿量的低能本征对问题，实现高精度与高性能，支持从量子化学到凝聚态物理的多种模型。
摘要：
CDFCI是一种共享内存并行数值程序，用于计算大规模非相对论费米哈密顿量的低能本征对。该软件设计用于处理广泛类别的多体量子模型，包括从头计算电子结构哈密顿量和凝聚态物理中的晶格哈密顿量。CDFCI结合了高效的坐标下降法选择配置相互作用算法与专门的并行化策略，在现代多核架构上实现高性能。基准测试结果表明，CDFCI在量子化学和凝聚态物理测试案例中达到最先进的精度，性能与CIPSI、SHCI和DMRG实现相媲美。该软件开源，文档详尽，并提供Python接口，无缝集成至PySCF和其他多体模拟工作流中。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
