Particle Detectors

Author(s):  
Hermann Kolanoski ◽  
Norbert Wermes

The book describes the fundamentals of particle detectors in their different forms as well as their applications, presenting the abundant material as clearly as possible and as deeply as needed for a thorough understanding. The target group for the book are both, students who want to get an introduction or wish to deepen their knowledge on the subject as well as lecturers and researchers who intend to extent their expertise. The book is also suited as a preparation for instrumental work in nuclear, particle and astroparticle physics and in many other fields (addressed in chapter 2). The detection of elementary particles, nuclei and high-energetic electromagnetic radiation, in this book commonly designated as ‘particles’, proceeds through interactions of the particles with matter. A detector records signals originating from the interactions occurring in or near the detector and (in general) feeds them into an electronic data acquisition system. The book describes the various steps in this process, beginning with the relevant interactions with matter, then proceeding to their exploitation for different detector types like tracking detectors, detectors for particle identification, detectors for energy measurements, detectors in astroparticle experiments, and ending with a discussion of signal processing and data acquisition. Besides the introductory and overview chapters (chapters 1 and 2), the book is divided into five subject areas: – fundamentals (chapters 3 to 5), – detection of tracks of charged particles (chapters 6 to 9), – phenomena and methods mainly applied for particle identification (chapters 10 to 14), – energy measurement (accelerator and non-accelerator experiments) (chapters 15, 16), – electronics and data acquisition (chapters 17 and 18). Comprehensive lists of literature, keywords and abbreviations can be found at the end of the book.

Author(s):  
T. Gary Yip

Abstract This paper describes a three-week long project for teaching microcomputer-based data acquisition. The project is part of a senior level laboratory course for mechanical engineering students at Santa Clara University. The subject of investigation is the lift coefficient of an airfoil. Students in groups of two carried out the project in three phases. The laboratory activities in each phase are designed to provide the students hands-on experience with the basic functions, hardware and software of a microcomputer-based data acquisition system. Typical results obtained by the students are presented. The project has been proved to be successful for the students to learn and practice the three basic concepts in data acquisition which are measurements, controls and programming.


Author(s):  
O. M. Korchazhkina

The article presents a methodological approach to studying iterative processes in the school course of geometry, by the example of constructing a Koch snowflake fractal curve and calculating a few characteristics of it. The interactive creative environment 1C:MathKit is chosen to visualize the method discussed. By performing repetitive constructions and algebraic calculations using ICT tools, students acquire a steady skill of work with geometric objects of various levels of complexity, comprehend the possibilities of mathematical interpretation of iterative processes in practice, and learn how to understand the dialectical unity between finite and infinite parameters of flat geometric figures. When students are getting familiar with such contradictory concepts and categories, that replenishes their experience of worldview comprehension of the subject areas they study through the concept of “big ideas”. The latter allows them to take a fresh look at the processes in the world around. The article is a matter of interest to schoolteachers of computer science and mathematics, as well as university scholars who teach the course “Concepts of modern natural sciences”.


Author(s):  
Aleksey Klokov ◽  
Evgenii Slobodyuk ◽  
Michael Charnine

The object of the research when writing the work was the body of text data collected together with the scientific advisor and the algorithms for processing the natural language of analysis. The stream of hypotheses has been tested against computer science scientific publications through a series of simulation experiments described in this dissertation. The subject of the research is algorithms and the results of the algorithms, aimed at predicting promising topics and terms that appear in the course of time in the scientific environment. The result of this work is a set of machine learning models, with the help of which experiments were carried out to identify promising terms and semantic relationships in the text corpus. The resulting models can be used for semantic processing and analysis of other subject areas.


Author(s):  
K. Maystrenko ◽  
A. Budilov ◽  
D. Afanasev

Goal. Identify trends and prospects for the development of radar in terms of the use of convolutional neural networks for target detection. Materials and methods. Analysis of relevant printed materials related to the subject areas of radar and convolutional neural networks. Results. The transition to convolutional neural networks in the field of radar is considered. A review of papers on the use of convolutional neural networks in pattern recognition problems, in particular, in the radar problem, is carried out. Hardware costs for the implementation of convolutional neural networks are analyzed. Conclusion. The conclusion is made about the need to create a methodology for selecting a network topology depending on the parameters of the radar task.


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