Vasilis Pagonis – författare

Thermoluminescence (TL) is a well-established technique widely used in dosimetric and dating applications. Although several excellent reference books exist which document both the theoretical and experimental aspects of TL, there is a general lack of books that deal with specific numerical and practical aspects of analyzing TL data. Many times the practical details of analyzing numerical TL glow curves and of applying theoretical models are difficult to find in the published literature.Numerical and Practical Exercises in Thermoluminescence provides a practical guide for both established researchers and for new graduate students entering the field of TL, and is intended to be used in conjunction with and as a practical supplement to standard textbooks in the field.

This advanced undergraduate textbook presents a new approach to teaching mathematical methods for scientists and engineers. It provides a practical, pedagogical introduction to utilizing Python in Mathematical and Computational Methods courses. Both analytical and computational examples are integrated from its start. Each chapter concludes with a set of problems designed to help students hone their skills in mathematical techniques, computer programming, and numerical analysis. The book places less emphasis on mathematical proofs, and more emphasis on how to use computers for both symbolic and numerical calculations. It contains 182 extensively documented coding examples, based on topics that students will encounter in their advanced courses in Mechanics, Electronics, Optics, Electromagnetism, Quantum Mechanics etc.An introductory chapter gives students a crash course in Python programming and the most often used libraries (SymPy, NumPy, SciPy, Matplotlib). This is followed by chapters dedicated to differentiation, integration, vectors and multiple integration techniques. The next group of chapters covers complex numbers, matrices, vector analysis and vector spaces. Extensive chapters cover ordinary and partial differential equations, followed by chapters on nonlinear systems and on the analysis of experimental data using linear and nonlinear regression techniques, Fourier transforms, binomial and Gaussian distributions. The book is accompanied by a dedicated GitHub website, which contains all codes from the book in the form of ready to run Jupyter notebooks. A detailed solutions manual is also available for instructors using the textbook in their courses.Key Features:A unique teaching approach which merges mathematical methods and the Python programming skills which physicists and engineering students need in their coursesUses examples and models from physical and engineering systems, to motivate the mathematics being taughtStudents learn to solve scientific problems in three different ways: traditional pen-and-paper methods, using scientific numerical techniques with NumPy and SciPy, and using Symbolic Python (SymPy).

Classical Mechanics: A Computational Approach with Examples using Python and Mathematica provides a unique, contemporary introduction to classical mechanics, with a focus on computational methods. In addition to providing clear and thorough coverage of key topics, this textbook includes integrated instructions and treatments of computation.This newly updated and revised second edition includes two new appendices instructing the reader in both the Python and Mathematica languages. All worked example problems in the second edition contain both Python and Mathematica code. New end-of-chapter problems explore the application of computational methods to classical mechanics problems.Full of pedagogy, it contains both analytical and computational example problems within the body of each chapter. The example problems teach readers both analytical methods and how to use computer algebra systems and computer programming to solve problems in classical mechanics. End-of-chapter problems allow students to hone their skills in problem solving with and without the use of a computer. The methods presented in this book can then be used by students when solving problems in other fields both within and outside of physics.It is an ideal textbook for undergraduate students in physics, mathematics, and engineering studying classical mechanics.Key Features:Gives readers the "big picture" of classical mechanics and the importance of computation in the solution of problems in physicsNumerous example problems using both analytical and computational methods, as well as explanations as to how and why specific techniques were usedOnline resources containing specific example codes to help students learn computational methods and write their own algorithmsA solutions manual is available via the Routledge Instructor Hub and all example codes in the book are available via the Support Material tab, and at the book’s GitHub page: https://github.com/vpagonis/Classical_Mechanics_2nd_Edition

Classical Mechanics: A Computational Approach with Examples using Python and Mathematica provides a unique, contemporary introduction to classical mechanics, with a focus on computational methods. In addition to providing clear and thorough coverage of key topics, this textbook includes integrated instructions and treatments of computation.This newly updated and revised second edition includes two new appendices instructing the reader in both the Python and Mathematica languages. All worked example problems in the second edition contain both Python and Mathematica code. New end-of-chapter problems explore the application of computational methods to classical mechanics problems.Full of pedagogy, it contains both analytical and computational example problems within the body of each chapter. The example problems teach readers both analytical methods and how to use computer algebra systems and computer programming to solve problems in classical mechanics. End-of-chapter problems allow students to hone their skills in problem solving with and without the use of a computer. The methods presented in this book can then be used by students when solving problems in other fields both within and outside of physics.It is an ideal textbook for undergraduate students in physics, mathematics, and engineering studying classical mechanics.Key Features:Gives readers the "big picture" of classical mechanics and the importance of computation in the solution of problems in physicsNumerous example problems using both analytical and computational methods, as well as explanations as to how and why specific techniques were usedOnline resources containing specific example codes to help students learn computational methods and write their own algorithmsA solutions manual is available via the Routledge Instructor Hub and all example codes in the book are available via the Support Material tab, and at the book’s GitHub page: https://github.com/vpagonis/Classical_Mechanics_2nd_Edition

Thermoluminescence (TL) is a well-established technique widely used in dosimetric and dating applications. Although several excellent reference books exist which document both the theoretical and experimental aspects of TL, there is a general lack of books that deal with specific numerical and practical aspects of analyzing TL data. Many times the practical details of analyzing numerical TL glow curves and of applying theoretical models are difficult to find in the published literature. Numerical and Practical Exercises in Thermoluminescence provides a practical guide for both established researchers and for new graduate students entering the field of TL, and is intended to be used in conjunction with and as a practical supplement to standard textbooks in the field.

In this volume, international leading experts in the study of thermally and optically stimulated luminescence give an up-to-date, comprehensive coverage of the theoretical and experimental aspects of these subjects, as well as their applications.The theory of thermoluminescence (TL) and optically stimulated luminescence (OSL) are discussed in detail including mainly solid state models of localized and delocalized transitions. These models cover the effects occurring during the excitation by irradiation and the read-out by heating or by exposure to light. The methods described consist of analytical mathematical considerations as well as numerical simulations.The main application of these effects, namely radiation dosimetry, includes personal and environmental dosimetry, as well as retrospective dosimetry and the dosimetry of cosmic radiation and space missions. Also discussed in detail are archaeological and geological dating, the use of luminescence dosimetry in medical physics as well as general applications in geosciences, other model subjects such as time-resolved luminescence and thermally assisted OSL, and the sister-subject of thermoluminescence in photosynthetic materials.

?This book covers applications of R to the general discipline of radiation dosimetry and to the specific areas of luminescence dosimetry, luminescence dating, and radiation protection dosimetry.

This book compiles and presents a complete package of open-access Python software code for luminescence signal analysis in the areas of radiation dosimetry, luminescence dosimetry, and luminescence dating.