116 citations
- Shandong Academy of SciencesCN14 papers
- Shandong UniversityCN12 papers
- Northwestern Polytechnical UniversityCN6 papers
- University of Science and Technology of ChinaCN5 papers
- Harbin Institute of TechnologyCN4 papers
- Institut Universitaire de FranceFR4 papers
- Université de MontpellierFR4 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- Chinese Academy of SciencesCN3 papers
- Istituto Nazionale di Fisica NucleareIT3 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di PerugiaIT3 papers
- Laboratoire Charles CoulombFR3 papers
30 papers
Diverse properties of electron Forbush decreases revealed by the Dark Matter Particle Explorer
F. Alemanno, Q. An, P. Azzarello +147
The Forbush decrease (FD) of cosmic rays is an important probe of the interplanetary environment disturbed by solar activities. In this work, we study the properties of 8 FDs elect…
Casimir radiation with Weyl semimetals
Yang Hu, Xiaohu Wu, Haotuo Liu +2
When Casimir friction torque acts upon a rotated nanoparticle (NP), mechanical energy can be transformed into thermal energy, known as Casimir radiation, which significantly affect…
Meson properties and symmetry emergence based on the deep neural network
Xin Tong, Wei Feng, Weiwei Xu +3
As a key property of hadrons, the total width is quite difficult to obtain in theory due to the extreme complexity of the strong and electroweak interactions. In this work, a deep…
Deep learning for jet modification in the presence of the QGP background
Ran Li, Yi-Lun Du, Shanshan Cao
Jet interactions with the color-deconfined QCD medium in relativistic heavy-ion collisions are conventionally assessed by measuring the modification of the distributions of jet obs…
Discovering quasiorder parameters in the Potts model: A bridge between machine learning and critical phenomena
Yi-Lun Du, Nan Su, Konrad Tywoniuk
Machine-learning (ML) models trained on Ising spin configurations have demonstrated surprising effectiveness in classifying phases of Potts models, even when processing severely re…
Extending the Low-Frequency Limit of Time-Domain Thermoreflectance via Periodic Waveform Analysis
Mingzhen Zhang, Tao Chen, Shangzhi Song +5
Time-domain thermoreflectance (TDTR) is a powerful technique for characterizing the thermal properties of layered materials. However, its effectiveness at modulation frequencies be…