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Fermi-Hubbard model is a fundamental lattice model describing correlated electron systems in condensed matter physics and is closely related to high-temperature superconductivity. In recent years, cold-atom quantum simulations have become an important paradigm for studying the Fermi-Hubbard model, and advances in quantum many-body computations have contributed to our understanding of its fundamental properties. Notably, a recent ultracold-atom experiment achieving the well-known antiferromagnetic (AFM) phase transition in the three-dimensional (3D) Hubbard model represents a key step in quantum simulation, laying a foundation for exploring the link between the quantum magnetism and high-temperature superconductivity. In this paper, the experimental and theoretical research progress of Fermi-Hubbard model in 3D systems is reviewed, the development history and present status in this field are discussed, and the future development direction is also prospected. The paper is organized as follows. To begin with, recent progress of observing AFM phase transitions in the 3D Hubbard model is reviewed, focusing on an ultracold-atom experiment conducted by the research group at the University of Science and Technology of China (USTC). Next, a theoretical introduction to the fundamental properties of the 3D Hubbard model is provided, in which prior theoretical studies is summarized, the current research status is outlined, and some unresolved or under-explored problems are discussed. In Section 3, the quantum simulation of the Hubbard model using ultracold atoms in optical lattices is discussed, and the basic principle, historical developments and key challenges are outlined. The USTC team overcame these challenges through innovative techniques such as atom cooling, large-scale uniform box traps, and precise measurements of the AFM structure factor. Their work successfully confirms the AFM phase transition via the critical scaling analysis. Finally, the significance of this achievement is emphasized, and the future research prospects of the 3D Hubbard model are discussed, including experimental studies on the doped regions and related theoretical benchmarks. -
Keywords:
- Fermi-Hubbard model /
- quantum simulation based on ultracold atoms /
- quantum many-body computation /
- antiferromagnetic phase transition
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[3] Qin M, Schäfer T, Andergassen S, Corboz P, Gull E 2022 Annu. Rev. Conden. Ma. P 13 275Google Scholar
[4] Hubbard J, Flowers B H 1963 Proc. R. Soc. Lond. Ser. A 276 238Google Scholar
[5] Kanamori J 1963 Prog. Theor. Phys. 30 275Google Scholar
[6] Gutzwiller M C 1963 Phys. Rev. Lett. 10 159Google Scholar
[7] Chen Q J, Wang Z Q, Rufus Boyack, Yang S L, Levin K 2024 Rev. Mod. Phys. 96 025002Google Scholar
[8] Campostrini M, Hasenbusch M, Pelissetto A, Rossi P, Vicari E 2002 Phys. Rev. B 65 144520Google Scholar
[9] Mermin N D, Wagner H 1966 Phys. Rev. Lett. 17 1133Google Scholar
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[11] Ibarra-García-Padilla E, Mukherjee R, Hulet R G, Hazzard K R A, Paiva T, Scalettar R T 2020 Phys. Rev. A 102 033340Google Scholar
[12] Sun F, Xu X Y 2024 arXiv: 2404.09989 [cond-mat. str-el]
[13] Song Y F, Deng Y, He Y Y 2024 arXiv: 2407.08603 [cond-mat. str-el]
[14] Werner F, Parcollet O, Georges A, Hassan S R 2005 Phys. Rev. Lett. 95 056401Google Scholar
[15] Fuchs S, Gull E, Troyer M, Jarrell M, Pruschke T 2011 Phys. Rev. B 83 235113Google Scholar
[16] Schäfer T, Katanin A A, Held K, Toschi A 2017 Phys. Rev. Lett. 119 046402Google Scholar
[17] Rampon L, Simkovic F, Ferrero M 2024 arXiv: 2409.08848 [cond-mat. str-el]
[18] Kozik E, Burovski E, Scarola V W, Troyer M 2013 Phys. Rev. B 87 205102Google Scholar
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[20] Garioud R, Šimkovic F, Rossi R, Spada G, Schäfer T, Werner F, Ferrero M 2024 Phys. Rev. Lett. 132 246505Google Scholar
[21] He Y Y, Qin M P, Shi H, Lu Z Y, Zhang S W 2019 Phys. Rev. B 99 045108Google Scholar
[22] Zheng B X, Chung C M, Corboz P, Ehlers G, Qin M P, Noack R M, Shi H, White S R, Zhang S W, Chan G K L 2017 Science 358 1155Google Scholar
[23] Xu H, Chung C M, Qin M P, Schollwöck U, White S R, Zhang S W 2024 Science 384 7691Google Scholar
[24] Feynman R P 1982 Int. J. Theor. Phys. 21 467Google Scholar
[25] Anderson M H, Ensher J R, Matthews M R, Wieman C E, Cornell E A 1995 Science 269 198Google Scholar
[26] Jaksch D, Bruder C, Cirac J I, Gardiner C W, Zoller P 1998 Phys. Rev. Lett. 81 3108Google Scholar
[27] DeMarco B, Jin D S 1999 Science 285 1703Google Scholar
[28] Greiner M, Mandel O, Esslinger T, Hansch T W, Bloch I 2002 Nature 415 39Google Scholar
[29] Jordens R, Strohmaier N, Gunter K, Moritz H, Esslinger T 2008 Nature 455 204Google Scholar
[30] Schneider U, Hackermuller L, Will S, Best Th, Bloch I, Costi T A, Helmes R W, Rasch D, Rosch A 2008 Science 322 1520Google Scholar
[31] Ho T L, Zhou Q 2009 arXiv: 0911.5506 [cond-mat. quant-gas]
[32] Lee P A, Nagaosa N, Wen X G 2006 Rev. Mod. Phys. 78 17Google Scholar
[33] Duan L M, Demler E, Lukin M D 2003 Phys. Rev. Lett. 91 090402Google Scholar
[34] Trotzky S, Cheinet P, Fölling S, et al. 2008 Science 319 295Google Scholar
[35] Bakr W S, Gillen J I, Peng A, Folling S, Greiner M 2009 Nature 462 74Google Scholar
[36] Haller E, Hudson J, Kelly A, Cotta D A, Peaudecerf B, Bruce G D, Kuhr S 2015 Nat. Phys. 11 738Google Scholar
[37] Greif D, Parsons M F, Mazurenko A, Chiu C S, Blatt S, Huber F, Ji G, Greiner M 2016 Science 351 953Google Scholar
[38] Hart R A, Duarte P M, Yang T L, Liu X X, Paiva T, Khatami E, Scalettar R T, Trivedi N, Huse D A, Hulet R G 2015 Nature 519 211Google Scholar
[39] Mazurenko A, Chiu C S, Ji G, et al. 2017 Nature 545 462Google Scholar
[40] Yang B, Sun H, Huang C J, Wang H Y, Deng Y J, Dai H N, Yuan Z S, Pan J W 2020 Science 369 550Google Scholar
[41] Sun H, Yang B, Wang H Y, et al. 2021 Nat. Phys. 17 990Google Scholar
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图 1 超冷原子模拟费米-哈伯德模型的示意图, 采用超冷原子等效于凝聚态体系中的电子, 而利用光学驻波构建出晶格结构, 可构筑哈伯德模型中的量子反铁磁物态, 进而通过调控体系的相互作用、温度和掺杂浓度等来研究反铁磁相变, 以及探究高温超导态的微观机理
Fig. 1. Illustration of the ultracold atom simulation for the Fermi-Hubbard model, ultracold atoms serve as analogues of electrons in condensed matter systems, with optical standing waves forming lattice structures, this setup allows for the creation of the Hubbard antiferromagnetic (AFM) state, by controlling parameters such as interaction strength, temperature and doping, the system can be utilized to study AFM phase transitions and explore the microscopic mechanism of high-temperature superconductivity.
图 2 (a)半满填充下的费米-哈伯德模型大致相图[1]; (b)随着$ U $增大实验测量的反铁磁结构因子结果[1]; (c)关于$ U $的临界标度行为[1]
Fig. 2. (a) Schematic phase diagram of the 3D half-filled Fermi-Hubbard model[1]; (b) experimental results of antiferromagnetic structure factor as a function of interaction strength $ U $[1]; (c) the critical scaling behavior of antiferromagnetic structure factor[1].
图 3 使用DMFT和$ {\mathrm{D}}{{\Gamma }}{\mathrm{A}} $算法得到的掺杂三维哈伯德模型在$ U=9.8 t $的磁性相图[16], 其中AF是奈儿反铁磁序, SDW是非公度的自旋密度波序, QCP是量子临界点
Fig. 3. Magnetic phase diagram for the 3D doped Hubbard model with $ U=9.8 t $, based on DMFT and $ {\mathrm{D}}{{\Gamma }}{\mathrm{A}} $ simulations[16], AF denotes the antiferromagnetic order, and SDW represents incommensurate spin density wave order, and QCP marks the quantum critical point.
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[1] Shao H J, Wang Y X, Zhu D Z, Zhu Y S, Sun H N, Chen S Y, Zhang C, Fan Z J, Deng Y, Yao X C, Chen Y A, Pan J W 2024 Nature 632 267Google Scholar
[2] Arovas D P, Berg E, Kivelson S A, Raghu S 2022 Annu. Rev. Conden. Ma. P. 13 239Google Scholar
[3] Qin M, Schäfer T, Andergassen S, Corboz P, Gull E 2022 Annu. Rev. Conden. Ma. P 13 275Google Scholar
[4] Hubbard J, Flowers B H 1963 Proc. R. Soc. Lond. Ser. A 276 238Google Scholar
[5] Kanamori J 1963 Prog. Theor. Phys. 30 275Google Scholar
[6] Gutzwiller M C 1963 Phys. Rev. Lett. 10 159Google Scholar
[7] Chen Q J, Wang Z Q, Rufus Boyack, Yang S L, Levin K 2024 Rev. Mod. Phys. 96 025002Google Scholar
[8] Campostrini M, Hasenbusch M, Pelissetto A, Rossi P, Vicari E 2002 Phys. Rev. B 65 144520Google Scholar
[9] Mermin N D, Wagner H 1966 Phys. Rev. Lett. 17 1133Google Scholar
[10] Staudt R, Dzierzawa M, Muramatsu A 2000 Eur. Phys. J. B 17 411Google Scholar
[11] Ibarra-García-Padilla E, Mukherjee R, Hulet R G, Hazzard K R A, Paiva T, Scalettar R T 2020 Phys. Rev. A 102 033340Google Scholar
[12] Sun F, Xu X Y 2024 arXiv: 2404.09989 [cond-mat. str-el]
[13] Song Y F, Deng Y, He Y Y 2024 arXiv: 2407.08603 [cond-mat. str-el]
[14] Werner F, Parcollet O, Georges A, Hassan S R 2005 Phys. Rev. Lett. 95 056401Google Scholar
[15] Fuchs S, Gull E, Troyer M, Jarrell M, Pruschke T 2011 Phys. Rev. B 83 235113Google Scholar
[16] Schäfer T, Katanin A A, Held K, Toschi A 2017 Phys. Rev. Lett. 119 046402Google Scholar
[17] Rampon L, Simkovic F, Ferrero M 2024 arXiv: 2409.08848 [cond-mat. str-el]
[18] Kozik E, Burovski E, Scarola V W, Troyer M 2013 Phys. Rev. B 87 205102Google Scholar
[19] Lenihan C, Kim A J, Simkovic F, Kozik E 2022 Phys. Rev. Lett. 129 107202Google Scholar
[20] Garioud R, Šimkovic F, Rossi R, Spada G, Schäfer T, Werner F, Ferrero M 2024 Phys. Rev. Lett. 132 246505Google Scholar
[21] He Y Y, Qin M P, Shi H, Lu Z Y, Zhang S W 2019 Phys. Rev. B 99 045108Google Scholar
[22] Zheng B X, Chung C M, Corboz P, Ehlers G, Qin M P, Noack R M, Shi H, White S R, Zhang S W, Chan G K L 2017 Science 358 1155Google Scholar
[23] Xu H, Chung C M, Qin M P, Schollwöck U, White S R, Zhang S W 2024 Science 384 7691Google Scholar
[24] Feynman R P 1982 Int. J. Theor. Phys. 21 467Google Scholar
[25] Anderson M H, Ensher J R, Matthews M R, Wieman C E, Cornell E A 1995 Science 269 198Google Scholar
[26] Jaksch D, Bruder C, Cirac J I, Gardiner C W, Zoller P 1998 Phys. Rev. Lett. 81 3108Google Scholar
[27] DeMarco B, Jin D S 1999 Science 285 1703Google Scholar
[28] Greiner M, Mandel O, Esslinger T, Hansch T W, Bloch I 2002 Nature 415 39Google Scholar
[29] Jordens R, Strohmaier N, Gunter K, Moritz H, Esslinger T 2008 Nature 455 204Google Scholar
[30] Schneider U, Hackermuller L, Will S, Best Th, Bloch I, Costi T A, Helmes R W, Rasch D, Rosch A 2008 Science 322 1520Google Scholar
[31] Ho T L, Zhou Q 2009 arXiv: 0911.5506 [cond-mat. quant-gas]
[32] Lee P A, Nagaosa N, Wen X G 2006 Rev. Mod. Phys. 78 17Google Scholar
[33] Duan L M, Demler E, Lukin M D 2003 Phys. Rev. Lett. 91 090402Google Scholar
[34] Trotzky S, Cheinet P, Fölling S, et al. 2008 Science 319 295Google Scholar
[35] Bakr W S, Gillen J I, Peng A, Folling S, Greiner M 2009 Nature 462 74Google Scholar
[36] Haller E, Hudson J, Kelly A, Cotta D A, Peaudecerf B, Bruce G D, Kuhr S 2015 Nat. Phys. 11 738Google Scholar
[37] Greif D, Parsons M F, Mazurenko A, Chiu C S, Blatt S, Huber F, Ji G, Greiner M 2016 Science 351 953Google Scholar
[38] Hart R A, Duarte P M, Yang T L, Liu X X, Paiva T, Khatami E, Scalettar R T, Trivedi N, Huse D A, Hulet R G 2015 Nature 519 211Google Scholar
[39] Mazurenko A, Chiu C S, Ji G, et al. 2017 Nature 545 462Google Scholar
[40] Yang B, Sun H, Huang C J, Wang H Y, Deng Y J, Dai H N, Yuan Z S, Pan J W 2020 Science 369 550Google Scholar
[41] Sun H, Yang B, Wang H Y, et al. 2021 Nat. Phys. 17 990Google Scholar
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