Person

Shuai Liu

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Related publications (22)

Please note that this is not a complete list of this person’s publications. It includes only semantically relevant works. For a full list, please refer to Infoscience.

Hosing of a Long Relativistic Particle Bunch in Plasma

Patrick Blanchard, Ambrogio Fasoli, Ivo Furno, Yanis Andrebe, Alban Sublet, Sun Hee Kim, Riccardo Agnello, Christine Stollberg, Shuai Liu

Experimental results show that hosing of a long particle bunch in plasma can be induced by wakefields driven by a short, misaligned preceding bunch. Hosing develops in the plane of misalignment, selfmodulation in the perpendicular plane, at frequencies clo ...

Amer Physical Soc2024

Development of the self-modulation instability of a relativistic proton bunch in plasma

Patrick Blanchard, Ambrogio Fasoli, Ivo Furno, Samuel Rey-Mermet, Yanis Andrebe, Alban Sublet, Sun Hee Kim, Ana Francisca Leal Silva Soares, Riccardo Agnello, Christine Stollberg, Shuai Liu

Self-modulation is a beam-plasma instability that is useful to drive large-amplitude wakefields with bunches much longer than the plasma skin depth. We present experimental results showing that, when increasing the ratio between the initial transverse size ...

2023

Search for relativistic fractionally charged particles in space

Songmei Wu, Johan Juul Chang, Zhirui Xu, Jennifer Maria Frieden, Siyuan Wang, Junqiu Liu, Jian Wang, Yi Zhang, Yong Yang, Hao Liu, Ming Gao, Cheng Zhao, Xuan Li, Arshia Ruina, Chiara Perrina, Andrii Kotenko, Wenyu Zhang, Xiao Wang, Yi Wang, Wei Li, Jie Chen, Shuai Liu, Yao Zhang

More than a century after the performance of the oil drop experiment, the possible existence of fractionally charged particles (FCPs) still remains unsettled. The search for FCPs is crucial for some extensions of the Standard Model in particle physics. Mos ...

American Physical Society2022

People doing similar research (32)

Roberto Castello is a senior scientist and group leader at the EPFL Laboratory of Solar Energy and Building Physics. Physicist by training, he has extensive experience in collecting, classifying and interpreting large datasets using advanced data mining techniques and statistical methods. He received his MSc (2007) in Particle Physics and PhD (2010) in Physics and Astrophysics from the University of Torino. He worked as a postdoctoral researcher at the Belgian National Research Fund (2011-2014) and at the CERN Experimental Physics Department (2015-2017) as a research fellow and data scientist. He is primary author of more than 20 peer-reviewed publications and he presented at major international conferences in the high energy physics domain. In 2018 he joined the Solar Energy and Building Physics Laboratory (LESO-PB) to work on data mining and Machine Learning techniques for the built environment and renewable energy. His main research interests are: spatio-temporal modeling of renewable energy potential, energy consumption forecasting techniques, anomaly detection, and computer vision techniques for automated classification in the built environment. He leads the group of Urban Data Mining, Intelligence and Simulation at LESO-PB and he is a member of the NRP75 Big Data project (HyEnergy) of the Swiss National Science Foundation. He is a member of the Swiss Competence Centre for Energy Research (SCCER) and deputy leader of the working group on Leveraging Ubiquitous Energy Data. He has served as a scientific committee member, workshop organizer and speaker at international conferences (ICAE 2020, Applied Machine Learning Days 2019 and 2020, CISBAT 2019 and 2021 and SDS2020). Since 2017 he is member of the Geneva 2030 Ecosystem network, promoting the United Nations agenda towards the realization of the Sustainable Development Goals (SDGs).

Yiming Li

Xin Chen