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1. Mott-moiré excitons

   https://doi.org/10.1103/PhysRevB.107.195151  

   Huang, Tsung-Sheng; Chou, Yang-Zhi; Baldwin, Christopher L.; Wu, Fengcheng; Hafezi, Mohammad (May 2023, Physical Review B)

   We develop a systematic theory for excitons subject to Fermi-Hubbard physics in moiré twisted transition metal dichalcogenides (TMDs). Specifically, we consider excitons from two moiré bands with a Mott-insulating valence band sustaining 120 spin order. These “Mott-moiré excitons,” which are achievable in twisted TMD heterobilayers, are bound states of a magnetic polaron in the valence band and a free electron in the conduction band. We find significantly narrower exciton bandwidths in the presence of Hubbard physics, serving as a potential experimental signature of strong correlations. We also demonstrate the high tunability of Mott-moiré excitons through the dependence of their binding energies, diameters, and bandwidths on the moiré period. In addition, we study bound states between charges outside of the strongly correlated moiré band and find that these as well exhibit signatures of spin correlation. Our work provides guidelines for future exploration of strongly correlated excitons in triangular Hubbard systems such as twisted TMD heterobilayers. 

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2. Spin-mediated Mott excitons

   https://doi.org/10.1103/PhysRevB.107.075111  

   Huang, T.-S.; Baldwin, C. L.; Hafezi, M.; Galitski, V. (February 2023, Physical Review B)
3. Emergence of quasiparticles in a doped Mott insulator

   https://doi.org/10.1038/s42005-020-00480-5  

   Wang, Yao; He, Yu; Wohlfeld, Krzysztof; Hashimoto, Makoto; Huang, Edwin W; Lu, Donghui; Mo, Sung-Kwan; Komiya, Seiki; Jia, Chunjing; Moritz, Brian; et al (December 2020, Communications Physics)

   Abstract How a Mott insulator develops into a weakly coupled metal upon doping is a central question to understanding various emergent correlated phenomena. To analyze this evolution and its connection to the high-T_ccuprates, we study the single-particle spectrum for the doped Hubbard model using cluster perturbation theory on superclusters. Starting from extremely low doping, we identify a heavily renormalized quasiparticle dispersion that immediately develops across the Fermi level, and a weakening polaronic side band at higher binding energy. The quasiparticle spectral weight roughly grows at twice the rate of doping in the low doping regime, but this rate is halved at optimal doping. In the heavily doped regime, we find both strong electron-hole asymmetry and a persistent presence of Mott spectral features. Finally, we discuss the applicability of the single-band Hubbard model to describe the evolution of nodal spectra measured by angle-resolved photoemission spectroscopy (ARPES) on the single-layer cuprate La_2−xSr_xCuO₄(0 ≤x≤ 0.15). This work benchmarks the predictive power of the Hubbard model for electronic properties of high-T_ccuprates. 

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4. Interaction spectroscopy of a two-component Mott insulator

   https://doi.org/10.1103/PhysRevA.99.033612  

   Amato-Grill, Jesse; Jepsen, Niklas; Dimitrova, Ivana; Lunden, William; Ketterle, Wolfgang (March 2019, Physical Review A)
5. Neuromorphic learning with Mott insulator NiO

   https://doi.org/10.1073/pnas.2017239118  

   Zhang, Zhen; Mondal, Sandip; Mandal, Subhasish; Allred, Jason M.; Aghamiri, Neda Alsadat; Fali, Alireza; Zhang, Zhan; Zhou, Hua; Cao, Hui; Rodolakis, Fanny; et al (September 2021, Proceedings of the National Academy of Sciences)

   Habituation and sensitization (nonassociative learning) are among the most fundamental forms of learning and memory behavior present in organisms that enable adaptation and learning in dynamic environments. Emulating such features of intelligence found in nature in the solid state can serve as inspiration for algorithmic simulations in artificial neural networks and potential use in neuromorphic computing. Here, we demonstrate nonassociative learning with a prototypical Mott insulator, nickel oxide (NiO), under a variety of external stimuli at and above room temperature. Similar to biological species such as Aplysia , habituation and sensitization of NiO possess time-dependent plasticity relying on both strength and time interval between stimuli. A combination of experimental approaches and first-principles calculations reveals that such learning behavior of NiO results from dynamic modulation of its defect and electronic structure. An artificial neural network model inspired by such nonassociative learning is simulated to show advantages for an unsupervised clustering task in accuracy and reducing catastrophic interference, which could help mitigate the stability–plasticity dilemma. Mott insulators can therefore serve as building blocks to examine learning behavior noted in biology and inspire new learning algorithms for artificial intelligence. 

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