Programmable quantum simulators may one day outperform classical computers at certain tasks. But at present, the range of viable applications with noisy intermediate-scale quantum (NISQ) devices remains limited by gate errors and the number of high-quality qubits. Here, we develop an approach that places digital NISQ hardware as a versatile platform for simulating multi-dimensional condensed matter systems. Our method encodes a high-dimensional lattice in terms of many-body interactions on a reduced-dimension model, thereby taking full advantage of the exponentially large Hilbert space of the host quantum system. With circuit optimization and error mitigation techniques, we measured on IBM superconducting quantum processors the topological state dynamics and protected mid-gap spectra of higher-order topological lattices, in up to four dimensions, with high accuracy. Our projected resource requirements scale favorably with system size and lattice dimensionality compared to classical computation, suggesting a possible route to useful quantum advantage in the longer term.
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http://dx.doi.org/10.1038/s41467-024-49648-5 | DOI Listing |
Entropy (Basel)
December 2024
Faculty of Science, Kunming University of Science and Technology, Kunming 650500, China.
Currently, the rapid development of social media enables people to communicate more and more frequently in the network. Classifying user activities in social networks helps to better understand user behavior in social networks. This paper first creates an ego network for each user, encodes the higher-order topological features of the ego network as persistence diagrams using persistence homology, and computes the persistence entropy.
View Article and Find Full Text PDFSci Rep
January 2025
University of São Paulo, ICMC, São Carlos, 13566-590, Brazil.
Identifying driver genes is crucial for understanding oncogenesis and developing targeted cancer therapies. Driver discovery methods using protein or pathway networks rely on traditional network science measures, focusing on nodes, edges, or community metrics. These methods can overlook the high-dimensional interactions that cancer genes have within cancer networks.
View Article and Find Full Text PDFAdv Sci (Weinh)
January 2025
Université de Lorraine, CNRS, Institut Jean Lamour, Nancy, 54000, France.
ℤ-classified higher-order topological insulators (HOTIs) with chiral-symmetric higher-order topological phases protected by multipole chiral numbers (MCNs) have attracted extensive interest recently. However, how to design artificial ℤ-classified HOTIs with multiple topological phases remains an unresolved issue. Here, multiorbital degrees of freedom are introduced to acoustic crystals and the various methods of topological phase transitions are achieved for the orbital ℤ-classified HOTIs.
View Article and Find Full Text PDFSci Bull (Beijing)
January 2025
Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing 100871, China. Electronic address:
Z-classified topological phases lead to a larger-than-unity number of topological states. However, these multiple topological states are only localized at the corners in nonlocal systems. Here, first, we rigorously prove that the multiple topological states of nonlocal Su-Schrieffer-Heeger (SSH) chains can be inherited and realized by local aperiodic chains with only the nearest couplings.
View Article and Find Full Text PDFNeuroimage
January 2025
College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China; Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China. Electronic address:
Dynamic brain networks (DBNs) can capture the intricate connections and temporal evolution among brain regions, becoming increasingly crucial in the diagnosis of neurological disorders. However, most existing researches tend to focus on isolated brain network sequence segmented by sliding windows, and they are difficult to effectively uncover the higher-order spatio-temporal topological pattern in DBNs. Meantime, it remains a challenge to utilize the structure connectivity prior in the DBNs analysis.
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