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19952026
most citedA Survey on Metaverse: Fundamentals, Security, and Privacy

1.3k citations

Showing 2024Show all

18 papers · 1 filter

cond-mat.str-el2024★ 19 cited

Collinear Altermagnets and their Landau Theories

Hana Schiff, Paul McClarty, Jeffrey G. Rau +1

Altermagnets exhibit spontaneously spin-split electronic bands in the zero spin-orbit coupling (SOC) limit arising from the presence of collinear compensated magnetic order. The di…

physics.med-ph2024★ 6 cited

ezyMRI: How to build an MRI machine from scratch -- Experience from a four-day hackathon

Shaoying Huang, José Miguel Algarín, Joseba Alonso +25

Nuclear magnetic resonance instruments are becoming available to the do-it-yourself community. The challenges encountered in the endeavor to build a magnetic resonance imaging inst…

cs.CG2024

Noncrossing Longest Paths and Cycles

Greg Aloupis, Ahmad Biniaz, Prosenjit Bose +7

Edge crossings in geometric graphs are sometimes undesirable as they could lead to unwanted situations such as collisions in motion planning and inconsistency in VLSI layout. Short…

cond-mat.str-el2024★ 4 cited

Pulling order back from the brink of disorder: Observation of a nodal line spin liquid and fluctuation stabilized order in KIrCl

Qiaochu Wang, Alberto de la Torre, Jose A. Rodriguez-Rivera +8

Competing interactions in frustrated magnets can give rise to highly degenerate ground states from which correlated liquid-like states of matter often emerge. The scaling of this d…

cond-mat.str-el2024★ 5 cited

Unraveling the magnetic ground-state in alkali-metal lanthanide oxide NaPrO

Ifeanyi John Onuorah, Jonathan Frassineti, Qiaochu Wang +8

A comprehensive set of muon spin spectroscopy and neutron scattering measurements supported by ab-initio and model Hamiltonian simulations have been used to investigate the magneti…

cs.CV2024

Efficient unsupervised domain adaptation via self-supervised vision transformer and synergistic cross-domain alignment

Ali Abedi, Q. M. Jonathan Wu, Ning Zhang +1

Unsupervised domain adaptation (UDA) aims to mitigate domain shift, where the distribution of labeled source data differs from that of unlabeled target data. Despite recent advance…