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arXiv:2501.00552 · Physical Review Letters

Quantum Many-Body Dynamics for Fermionic t − J Model Simulated with Atom Arrays

Y. H. Zhang, Xin-Chi Zhou, Bao‐Zong Wang, Xiong-Jun Liu

Published Jan 2, 2026• 4 citations
arXivHTMLPDF

Abstract

The fermionic t-J model has been widely recognized as a canonical model for broad range of strongly correlated phases, particularly the high-T_{c} superconductor. Simulating this model with controllable quantum platforms offers new possibilities to probe high-T_{c} physics, yet suffers challenges. Here we propose a novel scheme to realize a highly tunable extended t-J model in a programmable Rydberg-dressed tweezer array. Through engineering the Rydberg-dressed dipole-dipole interaction and intertweezer couplings, the fermionic t-J model with independently tunable exchange and hopping couplings is achieved. With the high tunability, we explore quantum many-body dynamics in the large J/t limit, a regime well beyond the conventional optical lattices and cuprates, and predict an unprecedented many-body self-pinning effect related to the local quantum entanglement with emergent conserved quantities. The self-pinning effect leads to novel nonthermal quantum many-body dynamics, which violates eigenstate thermalization hypothesis in Krylov subspace. Our prediction opens a new horizon in exploring exotic quantum many-body physics with t-J model, and shall also make a step toward simulating the high-T_{c} physics in neutral atom systems.

DOI
10.1103/px63-dtc9

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The fermionic t-J model has been widely recognized as a canonical model for broad range of strongly correlated phases, particularly the high-T_{c} superconductor. Simulating this model with controllable quantum platforms offers new possibilities to probe high-T_{c} physics, yet suffers challenges. Here we propose a novel scheme to realize a highly tunable extended t-J model in a programmable Rydberg-dressed tweezer array. Through engineering the Rydberg-dressed dipole-dipole interaction and intertweezer couplings, the fermionic t-J model with independently tunable exchange and hopping couplings is achieved. With the high tunability, we explore quantum many-body dynamics in the large J/t limit, a regime well beyond the conventional optical lattices and cuprates, and predict an unprecedented many-body self-pinning effect related to the local quantum entanglement with emergent conserved quantities. The self-pinning effect leads to novel nonthermal quantum many-body dynamics, which violates eigenstate thermalization hypothesis in Krylov subspace. Our prediction opens a new horizon in exploring exotic quantum many-body physics with t-J model, and shall also make a step toward simulating the high-T_{c} physics in neutral atom systems.
Analog quantum simulations with Rydberg atoms in optical tweezers have emerged as a powerful tool for exploring strongly correlated many-body physics. However, the range of accessible phenomena remains limited by constraints in controlling many-body interactions in these systems. Here, we propose an alternative approach to realizing tunable interactions using Rydberg dressing on Aquila, a 256-atom quantum simulator based on optical tweezer arrays. By weakly admixing a Rydberg state via off-resonant laser coupling, we generate long-range interactions with temporal control. In combination with programmable atom geometries and site-selective control, this dressing protocol enables simulation of quantum spin models with state preparation and measurement in arbitrary basis. These capabilities enable access to exciting regimes of quantum simulation, including Quantum spin liquids, XYZ lattice models and broader application of quantum reservoir computing. Our approach establish Rydberg dressing as a practical and scalable tool for expanding the class of many-body systems accessible to analog quantum simulation and provides a critical stepping stone toward quantum machine learning and hybrid analog-digital quantum simulation with neutral atoms.
Programmable arrays of neutral Rydberg atoms are one of the leading platforms today for scalable quantum simulation and computation. In these systems, the dipole-dipole interactions between the individual atoms, or qubits, typically result in binary -- i.e., two-body -- couplings. In this work, we develop an experimentally accessible scheme for engineering three-body interactions in Rydberg lattices. Such strong three-body couplings can fundamentally modify the underlying physics compared to systems with only two-body interactions: we demonstrate this, in particular, by systematically investigating the effective many-body Hamiltonian and its emergent quantum phases. This capability paves the way for the quantum simulation of a broader class of correlated models of condensed matter and high-energy physics.
Strongly correlated materials exhibit complex emergent phenomena -- such as unconventional high-temperature superconductivity -- that cannot be explained within a single or weakly-interacting particle description, making understanding their physics a central challenge in condensed matter physics. This thesis develops and applies novel approaches to strongly correlated electron systems, focusing on neural quantum states (NQS) and quantum simulation with cold atoms in optical lattices or Rydberg tweezer arrays. A key contribution of this work is the advancement of neural-network-based representations of quantum many-body states. By employing state-of-the-art network architectures like Transformers and combining them with physical constructions such as determinants, Pfaffians and Gutzwiller-projection, NQS are extended to simulate large two-dimensional fermionic single- and multi-band systems with high accuracy and beyond the capabilities of conventional methods. In addition, the thesis explores how quantum simulators based on ultracold atoms in optical lattices can be leveraged to study models directly relevant to strongly correlated materials -- e.g. the multi-band model of cuprate superconductors -- as well as proposes strategies to probe superconductivity in this setting. Furthermore, hybrid approaches that combine NQS with data from quantum simulators are developed. This synergy allows for improved optimization and direct comparison between theory and experiment. These methodological developments are applied to investigate two fundamental questions in high-temperature superconductivity: On the one hand, the work proposes a microscopic mechanism based on Feshbach resonances and tests this hypothesis extensively in a model system relevant to cuprates, nickelates and heavy fermion materials. On the other hand, it develops systematic approaches to derive effective low-energy models from more complex systems like multi-band models or electron-phonon coupled systems, shining light on the timely question which single-band models capture the physics of high-temperature superconductors like cuprate or nickelate materials. Overall, the thesis demonstrates how combining machine learning and quantum simulation provides powerful tools for understanding strongly correlated quantum matter.
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Rydberg atoms, characterized by their strong and long-range dipole-dipole interactions, provide a versatile platform for exploring intriguing collective and many-body effects. Recently, the experimental realization of these effects in dense ensembles and reconfigurable atomic arrays has attracted significant interest, particularly for applications in quantum simulations and non-equilibrium physics. This review focuses on such recent development, discussing the theoretical foundations of the interactions between Rydberg atoms and the ensuing many-body physics, while providing a critical survey of experimental techniques for their precise manipulation and observation. We further discuss recent breakthroughs in leveraging Rydberg collective effects to probe novel many-body phases and non-equilibrium dynamics of these systems. By synthesizing theoretical insights with experimental milestones, we provide a comprehensive perspective on this rapidly evolving field and its transformative potential for future quantum technologies.