128 citations · 1.4k across the 57 of their papers we have counts for
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Direct prediction of phonon density of states with Euclidean neural networks
Zhantao Chen, Nina Andrejevic, Tess Smidt +6
Machine learning has demonstrated great power in materials design, discovery, and property prediction. However, despite the success of machine learning in predicting discrete prope…
Signature of Many-Body Localization of Phonons in Strongly Disordered Superlattices
Thanh Nguyen, Nina Andrejevic, Hoi Chun Po +17
Many-body localization (MBL) has attracted significant attention due to its immunity to thermalization, role in logarithmic entanglement entropy growth, and opportunities to reach…
Machine learning spectral indicators of topology
Nina Andrejevic, Jovana Andrejevic, B. Andrei Bernevig +7
Topological materials discovery has emerged as an important frontier in condensed matter physics. While theoretical classification frameworks have been used to identify thousands o…
Anomalous Phonon-mode Dependence in Polarized Raman Spectroscopy of Topological Weyl Semimetal TaP
Kunyan Zhang, Xiaoqi Pang, Tong Wang +8
Topological Weyl semimetals (WSMs) have attracted widespread interests due to the chiral Weyl fermions and surface Fermi arcs that enable unique optical and transport phenomena. In…