spin liquids
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2022 ◽  
Vol 105 (4) ◽  
Author(s):  
Lucas R. D. Freitas ◽  
Rodrigo G. Pereira
Keyword(s):  

2021 ◽  
Vol 104 (23) ◽  
Author(s):  
Vir B. Bulchandani ◽  
Benjamin Hsu ◽  
Christopher P. Herzog ◽  
S. L. Sondhi

2021 ◽  
Vol 104 (23) ◽  
Author(s):  
Ji-Yao Chen ◽  
Jheng-Wei Li ◽  
Pierre Nataf ◽  
Sylvain Capponi ◽  
Matthieu Mambrini ◽  
...  
Keyword(s):  

Science ◽  
2021 ◽  
Vol 374 (6572) ◽  
pp. 1242-1247
Author(s):  
G. Semeghini ◽  
H. Levine ◽  
A. Keesling ◽  
S. Ebadi ◽  
T. T. Wang ◽  
...  

2021 ◽  
Vol 127 (23) ◽  
Author(s):  
Rui Wang ◽  
Yilin Wang ◽  
Y. X. Zhao ◽  
Baigeng Wang
Keyword(s):  

2021 ◽  
Vol 104 (19) ◽  
Author(s):  
Inti Sodemann Villadiego
Keyword(s):  

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Christian Thurn ◽  
Paul Eibisch ◽  
Arif Ata ◽  
Maximilian Winkler ◽  
Peter Lunkenheimer ◽  
...  

AbstractGeometrical frustration among interacting spins combined with strong quantum fluctuations destabilize long-range magnetic order in favor of more exotic states such as spin liquids. By following this guiding principle, a number of spin liquid candidate systems were identified in quasi-two-dimensional (quasi-2D) systems. For 3D, however, the situation is less favorable as quantum fluctuations are reduced and competing states become more relevant. Here we report a comprehensive study of thermodynamic, magnetic and dielectric properties on single crystalline and pressed-powder samples of PbCuTe2O6, a candidate material for a 3D frustrated quantum spin liquid featuring a hyperkagome lattice. Whereas the low-temperature properties of the powder samples are consistent with the recently proposed quantum spin liquid state, an even more exotic behavior is revealed for the single crystals. These crystals show ferroelectric order at TFE ≈ 1 K, accompanied by strong lattice distortions, and a modified magnetic response—still consistent with a quantum spin liquid—but with clear indications for quantum critical behavior.


2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Luca F. Tocchio ◽  
Arianna Montorsi ◽  
Federico Becca
Keyword(s):  

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Valentin Stanev ◽  
Kamal Choudhary ◽  
Aaron Gilad Kusne ◽  
Johnpierre Paglione ◽  
Ichiro Takeuchi

AbstractArtificial intelligence and machine learning are becoming indispensable tools in many areas of physics, including astrophysics, particle physics, and climate science. In the arena of quantum materials, the rise of new experimental and computational techniques has increased the volume and the speed with which data are collected, and artificial intelligence is poised to impact the exploration of new materials such as superconductors, spin liquids, and topological insulators. This review outlines how the use of data-driven approaches is changing the landscape of quantum materials research. From rapid construction and analysis of computational and experimental databases to implementing physical models as pathfinding guidelines for autonomous experiments, we show that artificial intelligence is already well on its way to becoming the lynchpin in the search and discovery of quantum materials.


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