Zobrazeno 1 - 10
of 18 746
pro vyhledávání: '"LESLIE, M."'
Autor:
Mathur, Nitish, Cheng, Guangming, Ballester, Francesc, Carrel, Gabrielle, Plisson, Vincent M., Yuan, Fang, Zheng, Jiangchang, Chen, Caiyun, Lee, Scott B., Singha, Ratnadwip, Chatterjee, Sudipta, Burch, Kenneth S., Jäck, Berthold, Errea, Ion, Vergniory, Maia G., Yao, Nan, Schoop, Leslie M.
A single material can exist in different states, with solids, liquids, and gases being the most familiar examples. In materials, these states can exhibit periodic structures spanning from atomic to macroscopic length scales. The conventional wisdom i
Externí odkaz:
http://arxiv.org/abs/2409.19783
Image classification models, including convolutional neural networks (CNNs), perform well on a variety of classification tasks but struggle under conditions of partial occlusion, i.e., conditions in which objects are partially covered from the view o
Externí odkaz:
http://arxiv.org/abs/2409.10775
Autor:
Jia, Yanyu, Song, Tiancheng, Zheng, Zhaoyi Joy, Cheng, Guangming, Uzan, Ayelet J, Yu, Guo, Tang, Yue, Pollak, Connor J., Yuan, Fang, Onyszczak, Michael, Watanabe, Kenji, Taniguchi, Takashi, Lei, Shiming, Yao, Nan, Schoop, Leslie M, Ong, N. P., Wu, Sanfeng
Introducing superconductivity in topological materials can lead to innovative electronic phases and device functionalities. Here, we present a new strategy for quantum engineering of superconducting junctions in moire materials through direct, on-chi
Externí odkaz:
http://arxiv.org/abs/2409.04594
Autor:
Berry, Tanya, Moya, Jaime M., Smiadak, David, Lee, Scott B., Aharon, Sigalit, Zevalkink, Alexandra, McQueen, Tyrel M., Schoop, Leslie M.
While $\sim$30% of materials are reported to be topological, topological insulators are rare. Magnetic topological insulators (MTI) are even harder to find. Identifying crystallographic features that can host the coexistence of a topological insulati
Externí odkaz:
http://arxiv.org/abs/2409.00455
Efficient and effective modeling of complex systems, incorporating cloud physics and precipitation, is essential for accurate climate modeling and forecasting. However, simulating these systems is computationally demanding since microphysics has cruc
Externí odkaz:
http://arxiv.org/abs/2407.20886
Beyond Linear Decomposition: a Nonlinear Eigenspace Decomposition for a Moist Atmosphere with Clouds
A linear decomposition of states underpins many classical systems. This is the case of the Helmholtz decomposition, used to split vector fields into divergence-free and potential components, and of the dry Boussinesq system in atmospheric dynamics, w
Externí odkaz:
http://arxiv.org/abs/2405.11107
Autor:
Tang, Yue, Song, Tiancheng, Guan, Haosen, Jia, Yanyu, Yu, Guo, Zheng, Zhaoyi Joy, Uzan, Ayelet J., Onyszczak, Michael, Singha, Ratnadwip, Gui, Xin, Watanabe, Kenji, Taniguchi, Takashi, Cava, Robert J., Schoop, Leslie M., Ong, N. P., Wu, Sanfeng
The detection of Landau-level-like energy structures near the chemical potential of an insulator is essential to the search for a class of correlated electronic matter hosting charge-neutral fermions and Fermi surfaces, a long-proposed concept that r
Externí odkaz:
http://arxiv.org/abs/2405.09665
We consider a rotating non-hydrostatic flow with arbitrary stratification and argue that 1) the appropriate form of potential vorticity (PV) for this system is in terms of isopycnal deviation and 2) the decomposition into energetically orthogonal sol
Externí odkaz:
http://arxiv.org/abs/2403.20269
Autor:
Jia, Yanyu, Yu, Guo, Song, Tiancheng, Yuan, Fang, Uzan, Ayelet J, Tang, Yue, Wang, Pengjie, Singha, Ratnadwip, Onyszczak, Michael, Zheng, Zhaoyi Joy, Watanabe, Kenji, Taniguchi, Takashi, Schoop, Leslie M, Wu, Sanfeng
Two-dimensional (2D) transition metal dichalcogenides (TMDs) is a versatile class of quantum materials of interest to various fields including, e.g., nanoelectronics, optical devices, and topological and correlated quantum matter. Tailoring the elect
Externí odkaz:
http://arxiv.org/abs/2403.19877
Autor:
Liu, Yanjun, Jovanovic, Milena, Mallayya, Krishnanand, Maddox, Wesley J., Wilson, Andrew Gordon, Klemenz, Sebastian, Schoop, Leslie M., Kim, Eun-Ah
The advent of material databases provides an unprecedented opportunity to uncover predictive descriptors for emergent material properties from vast data space. However, common reliance on high-throughput ab initio data necessarily inherits limitation
Externí odkaz:
http://arxiv.org/abs/2312.02796