Time-averaged spatially resolved measurements are used in many fields of physics to determine spatial distributions of a physical quantity. Although one could think that time averaging suppresses all information on time variation, there are some situations in which a link can be established between time averaging and time variability. In this paper, we consider a simple system composed of a particle bunch that moves in space without deforming, and a detector placed at a point in space. The detector continuously counts the number of particles in its neighborhood. Upon sampling, the detector signal gives rise to a time series with, in general, nonvanishing variance. Time series obtained by placing the detector at different locations can then be used to obtain a time-average distribution of the number of particles by computing the time average of all the time series. We show that there is a close relationship between this average profile and higher-order statistics of the time series, including the variance and skewness. We also show a simple procedure by which individual time series can be used to determine features of the shape of the particle bunch.
Rakesh Chawla, Andrea Rizzi, Matthias Finger, Federica Legger, Matteo Galli, Sun Hee Kim, Jian Zhao, João Miguel das Neves Duarte, Tagir Aushev, Hua Zhang, Alexis Kalogeropoulos, Yixing Chen, Tian Cheng, Ioannis Papadopoulos, Gabriele Grosso, Valérie Scheurer, Meng Xiao, Qian Wang, Michele Bianco, Varun Sharma, Joao Varela, Sourav Sen, Ashish Sharma, Seungkyu Ha, David Vannerom, Csaba Hajdu, Sanjeev Kumar, Sebastiana Gianì, Kun Shi, Abhisek Datta, Miao Hu, Siyuan Wang, Muhammad Waqas, Anton Petrov, Jian Wang, Yi Zhang, Muhammad Ansar Iqbal, Yong Yang, Xin Sun, Muhammad Ahmad, Donghyun Kim, Matthias Wolf, , , , , , , , , , , , , , , , , , , , , , , , , , ,
Victor Panaretos, Laya Ghodrati