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This research introduces the Stochastic Phase Algorithm (SPA), a method that compresses quantum bath representations to enable scalable simulations of non-Markovian transport on large lattices like 100x100. By replacing independent local baths with shared environments, SPA significantly reduces computational bottlenecks while maintaining accuracy for complex materials such as bacteriochlorophyll aggregates and rubrene. The technique offers a crucial pathway for advancing quantum dynamics modeling beyond current size limitations without sacrificing fidelity to exact benchmarks.
Scalable simulation of non-Markovian quantum transport by stochastic-phase bath reduction
arXiv:2609.28318v1 Announce Type: new Abstract: Accurate simulations of non-Markovian quantum transport remain limited to small systems, and a key bottleneck is that each system site requires an independent set of quantum bath orbitals. We introduce the Stochastic Phase Algorithm (SPA), which replaces the independent local Gaussian baths in single-quasiparticle Holstein models by $R$ shared quantum baths with stochastic site-dependent phases. We prove that phase averaging reproduces the target two-point bath correlation matrix for every $R$, while increasing $R$ systematically suppresses errors from higher-order cross-site correlations. We obtain a fixed-time $O(R^{-1})$ trace-norm error bound with a prefactor independent of system size and connectivity. This spatial compression applies directly to unitary baths and can be combined with coupled-Lindblad spectral compression [Phys. Rev. Lett. 136, 090403 (2026)], which represents each shared environment by a very small number of coupled, damped quantum modes fitted to its thermal bath correlation over the simulation window. Numerically, SPA converges against direct unitary benchmarks on a $3\times3$ lattice, enables full-state-vector quantum-bath dynamics on a $100\times100$ lattice, and, with $R=1$, closely reproduces near exact benchmarks for exciton populations in bacteriochlorophyll aggregates and carrier mobility in rubrene.
Abstract:Accurate simulations of non-Markovian quantum transport remain limited to small systems, and a key bottleneck is that each system site requires an independent set of quantum bath orbitals. We introduce the Stochastic Phase Algorithm (SPA), which replaces the independent local Gaussian baths in single-quasiparticle Holstein models by $R$ shared quantum baths with stochastic site-dependent phases. We prove that phase averaging reproduces the target two-point bath correlation matrix for every $R$, while increasing $R$ systematically suppresses errors from higher-order cross-site correlations. We obtain a fixed-time $O(R^{-1})$ trace-norm error bound with a prefactor independent of system size and connectivity. This spatial compression applies directly to unitary baths and can be combined with coupled-Lindblad spectral compression [Phys. Rev. Lett. 136, 090403 (2026)], which represents each shared environment by a very small number of coupled, damped quantum modes fitted to its thermal bath correlation over the simulation window. Numerically, SPA converges against direct unitary benchmarks on a $3\times3$ lattice, enables full-state-vector quantum-bath dynamics on a $100\times100$ lattice, and, with $R=1$, closely reproduces near exact benchmarks for exciton populations in bacteriochlorophyll aggregates and carrier mobility in rubrene.
Quantum Physics (quant-ph); Mesoscale and Nanoscale Physics (cond-mat.mes-hall); Materials Science (cond-mat.mtrl-sci)
arXiv:2609.28318 [quant-ph]
(or arXiv:2609.28318v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2609.28318 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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