Conceptual Evolution Of Newtonian And Relativistic Mechanics
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Conceptual Evolution of Newtonian and Relativistic Mechanics
This book provides an introduction to Newtonian and relativistic mechanics. Unlike other books on the topic, which generally take a 'top-down' approach, it follows a novel system to show how the concepts of the 'science of motion' evolved through a veritable jungle of intermediate ideas and concepts. Starting with Aristotelian philosophy, the text gradually unravels how the human mind slowly progressed towards the fundamental ideas of inertia physics. The concepts that now appear so obvious to even a high school student took great intellectuals more than a millennium to clarify. The book explores the evolution of these concepts through the history of science. After a comprehensive overview of the discovery of dynamics, it explores fundamental issues of the properties of space and time and their relation with the laws of motion. It also explores the concepts of spatio-temporal locality and fields, and offers a philosophical discussion of relative motion versus absolute motion, as well as the concept of an absolute space. Furthermore, it presents Galilean transformation and the principle of relativity, inadequacy of Galilean relativity and emergence of the spatial theory of relativity with an emphasis on physical understanding, as well as the debate over relative motion versus absolute motion and Mach's principle followed by the principle of equivalence. The natural follow-on to this section is the physical foundations of general theory of relativity. Lastly, the book ends with some new issues and possibilities regarding further modifications of the laws of motion leading to the solution of a number of fundamental issues closely connected with the characteristics of the cosmos. It is a valuable resource for undergraduate students of physics, engineering, mathematics, and related disciplines. It is also suitable for interdisciplinary coursework and introductory reading outside the classroom.
Physics of Data Science and Machine Learning
Physics of Data Science and Machine Learning links fundamental concepts of physics to data science, machine learning, and artificial intelligence for physicists looking to integrate these techniques into their work. This book is written explicitly for physicists, marrying quantum and statistical mechanics with modern data mining, data science, and machine learning. It also explains how to integrate these techniques into the design of experiments, while exploring neural networks and machine learning, building on fundamental concepts of statistical and quantum mechanics. This book is a self-learning tool for physicists looking to learn how to utilize data science and machine learning in their research. It will also be of interest to computer scientists and applied mathematicians, alongside graduate students looking to understand the basic concepts and foundations of data science, machine learning, and artificial intelligence. Although specifically written for physicists, it will also help provide non-physicists with an opportunity to understand the fundamental concepts from a physics perspective to aid in the development of new and innovative machine learning and artificial intelligence tools. Key Features: Introduces the design of experiments and digital twin concepts in simple lay terms for physicists to understand, adopt, and adapt. Free from endless derivations; instead, equations are presented and it is explained strategically why it is imperative to use them and how they will help in the task at hand. Illustrations and simple explanations help readers visualize and absorb the difficult-to-understand concepts. Ijaz A. Rauf is an adjunct professor at the School of Graduate Studies, York University, Toronto, Canada. He is also an associate researcher at Ryerson University, Toronto, Canada and president of the Eminent-Tech Corporation, Bradford, ON, Canada.
A Theory of Wonder: Evolution, Brain and the Radical Nature of Science
‘A Theory of Wonder’ aims to determine the best way science can satisfy our sense of wonder by exploring the world. Empiricism tells us that science succeeds because it follows the scientific method: Observation passes judgment on Theory – supporting or rejecting it. Much credit is given to the inventor of the method, Galileo, but when historically-minded philosophers of science like Kuhn and Feyerabend called our attention to what Galileo actually wrote and did, we were shocked to find out that Galileo instead drives a dagger through the heart of empiricism; he strikes down the distinction between theory and observation. Plain facts, like the vertical fall of a stone, ruled out the motion of the Earth. To conclude that the stone really falls vertically, however, we must assume that the Earth does not move. If it does move, then the stone only “seems” to fall vertically. Galileo then replaced the “facts” against the motion of the Earth with “facts” that included such motion. This process is typical during scientific revolutions. A good strategy for science is to elaborate radical alternatives; then, and on their basis, reconsider what counts as evidence. Feyerabend was called irrational for this suggestion; but looking at the practice of science from the perspective of evolution and neuroscience shows that the suggestion is very reasonable instead, and, moreover, explains why science works best as a radical form of knowledge. It also leads to a sensible biological form of relative truth, with preliminary drafts leading to exciting discussions with other researchers in the philosophy of science. This book will be of particular interest to university students, instructors and researchers in history or philosophy of science, as well as those with a general interest in the nature of science.