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QENEX LAB: A Self-Contained Quantum Chemistry Platform with Sub-Nanohartree Precision and Automated Discovery Capabilities

Qenex Ai

Published Mar 26, 2026• 0 citations
Publisher

Abstract

We present QENEX LAB, an open-architecture quantum chemistry platform implementing Hartree-Fock (RHF/UHF), Møller-Plesset perturbation theory (MP2), coupled cluster singles and doubles (CCSD), the perturbative triples correction CCSD(T), unrestricted CCSD (UCCSD), equation-of-motion CCSD (EOM-CCSD), complete active space self-consistent field (CASSCF), and Kohn-Sham density functional theory (B3LYP, LDA) with linear-response time-dependent DFT (LR-TDDFT). Molecular integrals are evaluated via Obara-Saika recurrence relations with optional libcint acceleration. Benchmark calculations on He, H2, H2O, and other small molecules demonstrate sub-nanohartree agreement with PySCF reference values when using the libcint integral path, and sub-millihartree agreement with the native pure-Python integral engine. We present accuracy benchmarks across STO-3G, cc-pVDZ, and cc-pVTZ basis sets for nine molecules, validate mathematical invariants including Brillouin's theorem, density matrix idempotency, and size consistency, and describe supplementary capabilities including molecular property prediction (ADMET, toxicity, pharmacokinetics), inverse molecular design via genetic algorithms, and a SHA-256 Merkle-tree provenance chain for computational reproducibility. The platform comprises 81 Python source files (90,103 lines) operating without external quantum chemistry dependencies in the computation path.

DOI
10.26434/chemrxiv.15001263/v1

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