Zhurun Ji

All Publications

• Local probe of bulk and edge states in a fractional Chern insulator. Nature Ji, Z., Park, H., Barber, M. E., Hu, C., Watanabe, K., Taniguchi, T., Chu, J. H., Xu, X., Shen, Z. X. 2024; 635 (8039): 578-583

  Abstract

  The fractional quantum Hall effect is a key example of topological quantum many-body phenomena, arising from the interplay between strong electron correlation, topological order and time-reversal symmetry breaking. Recently, a lattice analogue of the fractional quantum Hall effect at zero magnetic field has been observed, confirming the existence of a zero-field fractional Chern insulator (FCI). Despite this, the bulk-edge correspondence-a hallmark of a FCI featuring an insulating bulk with conductive edges-has not been directly observed. In fact, this correspondence has not been visualized in any system for fractional states owing to experimental challenges. Here we report the imaging of FCI edge states in twisted MoTe2 (t-MoTe2) using microwave impedance microscopy1. By tuning the carrier density, we observe the system evolving between metallic and FCI states, the latter of which exhibits insulating bulk and conductive edges, as expected from the bulk-boundary correspondence. Further analysis suggests the composite nature of the FCI edge states. We also observe the evolution of edge states across the topological phase transition as a function of interlayer electric field and reveal exciting prospects of neighbouring domains with different fractional orders. These findings pave the way for research into topologically protected one-dimensional interfaces between various anyonic states at zero magnetic field, such as gapped one-dimensional symmetry-protected phases with non-zero topological entanglement entropy, Halperin-Laughlin interfaces and the creation of non-abelian anyons.

  View details for DOI 10.1038/s41586-024-08092-7

  View details for PubMedID 39567787

  View details for PubMedCentralID 11464376

• Opto-twistronic Hall effect in a three-dimensional spiral lattice. Nature Ji, Z., Zhao, Y., Chen, Y., Zhu, Z., Wang, Y., Liu, W., Modi, G., Mele, E. J., Jin, S., Agarwal, R. 2024

  Abstract

  Studies of moiré systems have explained the effect of superlattice modulations on their properties, demonstrating new correlated phases1. However, most experimental studies have focused on a few layers in two-dimensional systems. Extending twistronics to three dimensions, in which the twist extends into the third dimension, remains underexplored because of the challenges associated with the manual stacking of layers. Here we study three-dimensional twistronics using a self-assembled twisted spiral superlattice of multilayered WS2. Our findings show an opto-twistronic Hall effect driven by structural chirality and coherence length, modulated by the moiré potential of the spiral superlattice. This is an experimental manifestation of the noncommutative geometry of the system. We observe enhanced light-matter interactions and an altered dependence of the Hall coefficient on photon momentum. Our model suggests contributions from higher-order quantum geometric quantities to this observation, providing opportunities for designing quantum-materials-based optoelectronic lattices with large nonlinearities.

  View details for DOI 10.1038/s41586-024-07949-1

  View details for PubMedID 39294380

  View details for PubMedCentralID 10439888

• Characterization of Two Fast-Turnaround Dry Dilution Refrigerators for Scanning Probe Microscopy JOURNAL OF LOW TEMPERATURE PHYSICS Barber, M. E., Li, Y., Gibson, J., Yu, J., Jiang, Z., Hu, Y., Ji, Z., Nandi, N., Hoke, J. C., Bishop-Van Horn, L., Arias, G. R., Van Harlingen, D. J., Moler, K. A., Shen, Z., Kou, A., Feldman, B. E. 2024

  View details for DOI 10.1007/s10909-023-03035-4

  View details for Web of Science ID 001190209400002

• Capturing dynamical correlations using implicit neural representations. Nature communications Chitturi, S. R., Ji, Z., Petsch, A. N., Peng, C., Chen, Z., Plumley, R., Dunne, M., Mardanya, S., Chowdhury, S., Chen, H., Bansil, A., Feiguin, A., Kolesnikov, A. I., Prabhakaran, D., Hayden, S. M., Ratner, D., Jia, C., Nashed, Y., Turner, J. J. 2023; 14 (1): 5852

  Abstract

  Understanding the nature and origin of collective excitations in materials is of fundamental importance for unraveling the underlying physics of a many-body system. Excitation spectra are usually obtained by measuring the dynamical structure factor, S(Q, ω), using inelastic neutron or x-ray scattering techniques and are analyzed by comparing the experimental results against calculated predictions. We introduce a data-driven analysis tool which leverages 'neural implicit representations' that are specifically tailored for handling spectrographic measurements and are able to efficiently obtain unknown parameters from experimental data via automatic differentiation. In this work, we employ linear spin wave theory simulations to train a machine learning platform, enabling precise exchange parameter extraction from inelastic neutron scattering data on the square-lattice spin-1 antiferromagnet La2NiO4, showcasing a viable pathway towards automatic refinement of advanced models for ordered magnetic systems.

  View details for DOI 10.1038/s41467-023-41378-4

  View details for PubMedID 37730824

  View details for PubMedCentralID 8662964