ArticlePhysical review letters2020
Breaking the Entanglement Barrier: Tensor Network Simulation of Quantum Transport.
Article in Physical review letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Sub-Sharvin Conductance and Incoherent Shot-Noise in Graphene Disks at Magnetic Field.Materials (Basel, Switzerland) · 2024Article
- Flexible DMRG-Based Framework for Anharmonic Vibrational Calculations.Journal of chemical theory and computation · 2023Article
- Matrix Product State Simulations of Non-Equilibrium Steady States and Transient Heat Flows in the Two-Bath Spin-Boson Model at Finite Temperatures.Entropy (Basel, Switzerland) · 2021Article
- Analytic expressions for the steady-state current with finite extended reservoirs.The Journal of chemical physics · 2020Article
- Open System Tensor Networks and Kramers' Crossover for Quantum Transport.Physical review. A · 2020Article
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Authors and funding
2 authors.
Funding
Abstract
The recognition that large classes of quantum many-body systems have limited entanglement in the ground and low-lying excited states led to dramatic advances in their numerical simulation via so-called tensor networks. However, global dynamics elevates many particles into excited states, and can lead to macroscopic entanglement and the failure of tensor networks. Here, we show that for quantum transport-one of the most important cases of this failure-the fundamental issue is the canonical basis in which the scenario is cast: When particles flow through an interface, they scatter, generating a "bit" of entanglement between spatial regions with each event. The frequency basis naturally captures that-in the long-time limit and in the absence of inelastic scattering-particles tend to flow from a state with one frequency to a state of identical frequency. Recognizing this natural structure yields a striking-potentially exponential in some cases-increase in simulation efficiency, greatly extending the attainable spatial and time scales, and broadening the scope of tensor network simulation to hitherto inaccessible classes of nonequilibrium many-body problems.
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Registered trials
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