No. 01
泡利传播实现强关联量子系统的快速经典模拟Pauli Propagation Enables Fast Classical Simulation of Strongly Correlated Quantum Systems
强关联量子系统的基态能量估计仍然是计算物理和化学中的一个核心挑战。虽然像密度矩阵重正化群（DMRG）这样的张量网络方法为一维系统提供了高效解，但更高维问题仍然困难。在这里，我们提出一种变分双括号流（vDBF）算法，它利用泡利传播——一种最初为量子电路经典模拟而开发的技术——来高效近似基态能量。通过将贪心算符选择与基于系数的涨落截断以及能量方差外推相结合，我们对多达 128 个量子比特的海森堡和 Hubbard 晶格获得了低于 1% 的相对误差。对于 10 × 10 海森堡晶格（100 个量子比特），vDBF 在单个 CPU 线程上约 2 分钟内获得准确结果，而 DMRG 在 64 个线程上需要超过 50 小时。对于量子蒙特卡洛难以处理的系统，也获得了准确结果：在最大阻挫的 8 × 8 J1–J2 晶格和空穴掺杂的 8 × 8 Hubbard 模型上，最严格的阈值外推到已发表最佳变分估计的千分之几以内。我们进一步在六苯并蔻的 84 量子比特 π 价活性空间上测试 vDBF，其中最可靠的外推关联能与 DMRG 吻合在 1% 以内。这些结果表明，在量子优势基准测试背景下发展的经典模拟技术，可以为多体物理提供实用工具。另见 8 幅图。
Abstract (English)
Ground-state energy estimation for strongly correlated quantum systems remains a central challenge in computational physics and chemistry. While tensor network methods like Density Matrix Renormalization Group (DMRG) provide efficient solutions for one-dimensional systems, higher-dimensional problems remain difficult. Here we present a variational double bracket flow (vDBF) algorithm that leverages Pauli Propagation, a technique originally developed for classical simulation of quantum circuits, to efficiently approximate ground-state energies. By combining greedy operator selection with coefficient-based fluctuation truncation and energy-variance extrapolation, we obtain sub-1% relative errors for Heisenberg and Hubbard lattices of up to 128 qubits. For a 10 × 10 Heisenberg lattice (100 qubits), vDBF obtains accurate results in approximately 2 min on a single CPU thread, compared to over 50 h on 64 threads for DMRG. Accurate results are also obtained for systems that are difficult for quantum Monte Carlo: on the maximally frustrated 8 × 8 J 1 – J 2 lattice and the hole-doped 8 × 8 Hubbard model, the tightest thresholds extrapolate to within a few tenths of a percent of the best published variational estimates. We further test vDBF on the 84-qubit π -valence active space of hexabenzocoronene, where the most reliable extrapolated correlation energies agree with DMRG to within 1%. These results demonstrate that classical simulation techniques developed in the context of quantum advantage benchmarking can provide practical tools for many-body physics. See 8 more figures
Chinmay Shrikhande, Arnab Bachhar, José Aarón Rodríguez-Jiménez, Edward F. Valeev, and Nicholas J. Mayhall
PRX Quantum 7, 043022 (2026)
10.1103/kq3v-whcq