Pauli propagation enables fast classical simulation of strongly correlated quantum systems

Quantum Physics [Submitted on 26 Nov 2025 (v1), last revised 31 May 2026 (this version, v2)] Title:Pauli propagation enables fast classical simulation of strongly correlated quantum systems View PDF HTML (experimental)Abstract:Ground state energy estimation for strongly correlated quantum systems remains a central challenge in computational physics and chemistry. While tensor network methods like 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 results with sub-1% relative accuracy compared to DMRG benchmarks for the Heisenberg and Hubbard models in one and two dimensions. For a 10x10 Heisenberg lattice (100 qubits), vDBF obtains accurate results in approximately 1 minute on a single CPU thread, compared to over 50 hours on 64 threads for DMRG. For the 8x8 half-filled Hubbard model, corresponding to 128 qubits, vDBF reaches the 1% error regime in less than one hour, while our DMRG calculations required more than 10 hours on 64 threads. We further test vDBF on the 84-qubit {\pi}-valence active space of hexabenzocoronene, where the tighter-threshold calculations achieve sub-1% agreement with DMRG. These results demonstrate that classical simulation techniques developed in the context of quantum advantage benchmarking can provide practical tools for many-body physics. Submission history From: Nicholas Mayhall [view email][v1] Wed, 26 Nov 2025 18:22:13 UTC (336 KB) [v2] Sun, 31 May 2026 03:08:19 UTC (453 KB) Current browse context: quant-ph Change to browse by: References & Citations Loading... Bibliographic and Citation Tools Bibliographic Explorer (What is the Explorer?) Connected Papers (What is Connected Papers?) Litmaps (What is Litmaps?) scite Smart Citations (What are Smart Citations?) Code, Data and Media Associated with this Article alphaXiv (What is alphaXiv?) CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub (What is DagsHub?) Gotit.pub (What is GotitPub?) Hugging Face (What is Huggingface?) ScienceCast (What is ScienceCast?) Demos Recommenders and Search Tools Influence Flower (What are Influence Flowers?) CORE Recommender (What is CORE?) arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.