Teach Yourself Physics

This is a handbook containing all the advice and recommendations about learning physics I wished someone had told me when I was younger. It is neither a career guide nor a comprehensive textbook. What’s inside? - Understand why self-learning is an effective strategy. Learn why most university students never develop a deep understanding and what alternatives are possible. - Grasp the internal structure of physics. Learn how the fundamental theories of physics are connected and why physics works at all. - Develop an understanding of the landscape. Read bird's eye overviews that give a first taste of what the various theories of physics are all about. - Everything you need to get started. Read detailed reading and learning recommendations that allow you to carve out a personal learning path.

Finally figure out physics! Teach Yourself Physics introduces you to physics gradually by building a foundation of appropriate mathematical skills. Easy-to-understand diagrams help you understand key points.

IN THE NEWS Q&A: Kenneth Ford on Textbooks, Popularizations, and Scientific Secrecy Physics Today, June 2017 This reissued version of the classic text Basic Physics will help teachers at both the high-school and college levels gain new insights into, and deeper understanding of, many topics in both classical and modern physics that are commonly taught in introductory physics courses. All of the original book is included with new content added. Short sections of the previous book (174 in number) are labeled "Features." These Features are highlighted in the book, set forth in a separate Table of Contents, and separately indexed. Many teachers will value this book as a personal reference during a teaching year as various topics are addressed. Ford's discussions of the history and meaning of topics from Newton's mechanics to Feynman's diagrams, although written first in 1968, have beautifully withstood the test of time and are fully relevant to 21st-century physics teaching. Request Inspection Copy

This book on the teaching and learning of physics is intended for college-level instructors, but high school instructors might also find it very useful.Some ideas found in this book might be a small 'tweak' to existing practices whereas others require more substantial revisions to instruction. The discussions of student learning herein are based on research evidence accumulated over decades from various fields, including cognitive psychology, educational psychology, the learning sciences, and discipline-based education research including physics education research. Likewise, the teaching suggestions are also based on research findings. As for any other scientific endeavor, physics education research is an empirical field where experiments are performed, data are analyzed and conclusions drawn. Evidence from such research is then used to inform physics teaching and learning.While the focus here is on introductory physics taken by most students when they are enrolled, however, the ideas can also be used to improve teaching and learning in both upper-division undergraduate physics courses, as well as graduate-level courses. Whether you are new to teaching physics or a seasoned veteran, various ideas and strategies presented in the book will be suitable for active consideration.

A master teacher presents the ultimate introduction to classical mechanics for people who are serious about learning physics "Beautifully clear explanations of famously 'difficult' things," -- Wall Street Journal If you ever regretted not taking physics in college -- or simply want to know how to think like a physicist -- this is the book for you. In this bestselling introduction to classical mechanics, physicist Leonard Susskind and hacker-scientist George Hrabovsky offer a first course in physics and associated math for the ardent amateur. Challenging, lucid, and concise, The Theoretical Minimum provides a tool kit for amateur scientists to learn physics at their own pace.

This book presents research contributions focussing on the introduction of contemporary physics topics – mainly, but not exclusively, quantum physics – into high school currciula. Despite the important advances and discoveries in quantum physics and relativity which have revolutionized our views of nature and our everyday lives, the presence of these topics in high school physics education is still lacking. In this book physics education researchers report on the teaching and learning of quantum physics from different perspectives and discuss the design and use of different pedagogical approaches and educational pathways. There is still much debate as to what content is appropriate at high school level as well what pedagogical approaches and strategies should be adopted to support student learning. Currently there is a greater focus on how to teach modern physics at the high school level rather than classical physics. However, teachers still lack experience and availability of appropriate teaching and learning materials to support the coherent integration of Quantum Physics in high school curricula. All of the 19 papers presented in this book discuss innovative approaches for enhancing physics education in schools.

What is deep learning for those who study physics? Is it completely different from physics? Or is it similar? In recent years, machine learning, including deep learning, has begun to be used in various physics studies. Why is that? Is knowing physics useful in machine learning? Conversely, is knowing machine learning useful in physics? This book is devoted to answers of these questions. Starting with basic ideas of physics, neural networks are derived naturally. And you can learn the concepts of deep learning through the words of physics. In fact, the foundation of machine learning can be attributed to physical concepts. Hamiltonians that determine physical systems characterize various machine learning structures. Statistical physics given by Hamiltonians defines machine learning by neural networks. Furthermore, solving inverse problems in physics through machine learning and generalization essentially provides progress and even revolutions in physics. For these reasons, in recent years interdisciplinary research in machine learning and physics has been expanding dramatically. This book is written for anyone who wants to learn, understand, and apply the relationship between deep learning/machine learning and physics. All that is needed to read this book are the basic concepts in physics: energy and Hamiltonians. The concepts of statistical mechanics and the bracket notation of quantum mechanics, which are explained in columns, are used to explain deep learning frameworks. We encourage you to explore this new active field of machine learning and physics, with this book as a map of the continent to be explored.

Calculus Made Easy by Silvanus P. Thompson and Martin Gardner has long been the most popular calculus primer, and this major revision of the classic math text makes the subject at hand still more comprehensible to readers of all levels. With a new introduction, three new chapters, modernized language and methods throughout, and an appendix of challenging and enjoyable practice problems, Calculus Made Easy has been thoroughly updated for the modern reader.