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Superdiffusion resilience in Heisenberg chains with two-dimensional interactions on a quantum processor

  • Keerthi Kumaran
  • , Manas Sajjan
  • , Bibek Pokharel
  • , Kevin Wang
  • , Joe Gibbs
  • , Jeffrey Cohn
  • , Barbara Jones
  • , Sarah Mostame
  • , Sabre Kais
  • , Arnab Banerjee

Research output: Contribution to journal › Article › peer-review

Abstract

Superdiffusive spin transport in the one-dimensional (1D) Heisenberg model is a key theoretical discovery in nonequilibrium quantum many-body physics. Although extensively studied in 1D systems, the breakdown and sustenance of superdiffusion in two-dimensional (2D) lattices with integrability-breaking terms, as found in real materials, remains an open question. To address this, we develop a toy model that extends the 1D Heisenberg model with a representative set of 2D interaction types and tunable strengths. Our model exhibits varying degrees of superdiffusion breakdown depending on the interaction type, spanning ballistic to diffusive regimes. We establish and justify a hierarchy of 2D interactions based on their resilience against superdiffusion breakdown: Heisenberg >XX> Ising. This precise control over the superdiffusive behavior also enables rigorous benchmarking of quantum hardware, and our simulations on IBM's Heron devices confirm the hardware's ability to accurately capture these many-body nonequilibrium phenomena. Overall, our results are relevant not only to simulating superdiffusion in real materials, such as the 1D Heisenberg compound KCuF3, which contains modest nonintegrable 2D terms, but also to extending superdiffusive behavior to larger 2D qubit lattices and other 2D materials.

Original languageEnglish
Article number174408
JournalPhysical Review B
Volume113
Issue number17
DOIs
StatePublished - 2026

Funding

We acknowledge funding from the Office of Science through the Quantum Science Center (QSC), a National Quantum Information Science Research Center. We acknowledge the use of IBM Quantum services for this work. We also acknowledge Joel Moore, Norhan Eassa, Varadharajan Mu-ruganadham, and Zoe Holmes for insightful discussions. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.

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