Bringing together the best and most interesting science stories appearing in Quanta Magazine over the past five years, Alice and Bob Meet the Wall of Fire reports on some of the greatest scientific minds as they test the limits of human knowledge. Quanta, under editor-in-chief Thomas Lin, is the only popular publication that offers in-depth coverage of today's challenging, speculative, cutting-edge science. It communicates science by taking it seriously, wrestling with difficult concepts and clearly explaining them in a way that speaks to our innate curiosity about our world and ourselves.In the title story, Alice and Bob--beloved characters of various thought experiments in physics--grapple with gravitational forces, possible spaghettification, and a massive wall of fire as Alice jumps into a black hole. Another story considers whether the universe is impossible, in light of experimental results at the Large Hadron Collider. We learn about quantum reality and the mystery of quantum entanglement; explore the source of time's arrow; and witness a eureka moment when a quantum physicist exclaims: "Finally, we can understand why a cup of coffee equilibrates in a room." We reflect on humans' enormous skulls and the Brain Boom; consider the evolutionary benefits of loneliness; peel back the layers of the newest artificial-intelligence algorithms; follow the "battle for the heart and soul of physics"; and mourn the disappearance of the "diphoton bump," revealed to be a statistical fluctuation rather than a revolutionary new particle. These stories from Quanta give us a front-row seat to scientific discovery.ContributorsPhilip Ball, K. C. Cole, Robbert Dijkgraaf, Dan Falk, Courtney Humphries, Ferris Jabr, Katia Moskvitch, George Musser, Michael Nielsen, Jennifer Ouellette, John Pavlus, Emily Singer, Andreas von Bubnoff, Frank Wilczek, Natalie Wolchover, Carl Zimmer

    Gödel received public recognition of his work in 1951 when he was awarded the first Albert Einstein Award for achievement in the natural sciences--perhaps the highest award of its kind in the United States. The award committee described his work in mathematical logic as "one of the greatest contributions to the sciences in recent times."However, few mathematicians of the time were equipped to understand the young scholar's complex proof. Ernest Nagel and James Newman provide a readable and accessible explanation to both scholars and non-specialists of the main ideas and broad implications of Gödel's discovery. It offers every educated person with a taste for logic and philosophy the chance to understand a previously difficult and inaccessible subject.New York University Press is proud to publish this special edition of one of its bestselling books. With a new introduction by Douglas R. Hofstadter, this book will appeal students, scholars, and professionals in the fields of mathematics, computer science, logic and philosophy, and science.

    Call it the algebra oracle: By plugging in the right variables, GEEK LOGIK answers life’s most persistent questions. It covers Dating and Romance, Career and Finance, and everyday decisions like Should I get a tattoo? Can I still wear tight jeans? Is it time to see a therapist? How many beers should I have at the company picnic? How does it work? Take a simple issue that comes up once or twice a week: Should I call in sick? Fill in the variables honestly, such as D for doctor’s note (enter 1 for “no,†10 for “yes,†and 5 for “yes, but it’s a forgeryâ€), R for importance of job (1-10, with 10 being “personally responsible for Earth’s orbit around Sunâ€), Fj for how much fun you have at work (1-10, with 10 being “personal trainer for underwear modelsâ€), N for how much you need the money (1-10, with 10 being “I owe the mobâ€), then do the math, and voilà—if the product, Hooky, is greater than 1, enjoy your very own Ferris Bueller’s Day Off. Includes a pocket calculator so that prospective geeks can immediately solve the equation on the back cover: Should I buy this book?

    In this new, innovative overview textbook, the authors put special emphasis on the deep ideas of mathematics, and present the subject through lively and entertaining examples, anecdotes, challenges and illustrations, all of which are designed to excite the student's interest. The underlying ideas include topics from number theory, infinity, geometry, topology, probability and chaos theory. Throughout the text, the authors stress that mathematics is an analytical way of thinking, one that can be brought to bear on problem solving and effective thinking in any field of study.

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    This is just as well, according to Mark Lynas in Nuclear 2.0, because nuclear energy is essential to avoid catastrophic global warming. Using the latest world energy statistics Lynas shows that with wind and solar still at only about 1 percent of global primary energy, asking renewables to deliver all the world’s power is “dangerously delusional”. Moreover, there is no possibility of using less energy, he reminds us, when the developing world is fast extricating itself from poverty and adding the equivalent of a new Brazil to global electricity consumption each year. The anti-nuclear movement of the 1970s and 80s succeeded only in making the world more dependent on fossil fuels, he shows: its history is “not lit by sunshine, but shrouded in coal smoke”. Instead of making the same mistake again, all those who want to see a low-carbon future need to join forces, he insists, concluding the book with an ambitious proposal for an Apollo Program-style combined investment in wind, solar and nuclear power. Mark Lynas is an environmental writer and campaigner. His previous books have drawn attention to the perils of global warming, and he was Climate Advisor to the President of the Maldives from 2009-2011. He is a Visiting Research Associate at Oxford University’s School of Geography and the Environment, and a member of the World Economic Forum’s Global Agenda Council on Emerging Technologies. He recently featured in the movie documentary Pandora’s Promise, which inspired the writing of this book.

    But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that.This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples.By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to:- How to measure your own level of uncertainty in a conclusion or belief- Calculate Bayes theorem and understand what it's useful for- Find the posterior, likelihood, and prior to check the accuracy of your conclusions- Calculate distributions to see the range of your data- Compare hypotheses and draw reliable conclusions from themNext time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.

    Recently, however, serious scientists from a range of fields have been uncovering evidence that our thoughts, emotions and beliefs can ease pain, heal wounds, fend off infection and heart disease and even slow the progression of AIDS and some cancers.In Cure, award-winning science writer Jo Marchant travels the world to meet the physicians, patients and researchers on the cutting edge of this new world of medicine. We learn how meditation protects against depression and dementia, how social connections increase life expectancy and how patients who feel cared for recover from surgery faster. We meet Iraq war veterans who are using a virtual arctic world to treat their burns and children whose ADHD is kept under control with half the normal dose of medication. We watch as a transplant patient uses the smell of lavender to calm his hostile immune system and an Olympic runner shaves vital seconds off his time through mind-power alone.Drawing on the very latest research, Marchant explores the vast potential of the mind's ability to heal, lays out its limitations and explains how we can make use of the findings in our own lives. With clarity and compassion, Cure points the way towards a system of medicine that treats us not simply as bodies but as human beings.

    You'll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you'll put your new knowledge into practice with three substantial projects: a Space Invaders-inspired arcade game, data visualizations with Python's super-handy libraries, and a simple web app you can deploy online.As you work through Python Crash Course, you'll learn how to: Use powerful Python libraries and tools, including matplotlib, NumPy, and PygalMake 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progressesWork with data to generate interactive visualizationsCreate and customize simple web apps and deploy them safely onlineDeal with mistakes and errors so you can solve your own programming problemsIf you've been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!

    Ask them the meaning of 'relativity' and few of them will be able to tell you what it is.The basic principles of relativity have not changed since Russell first published his lucid guide for the general reader. The ABC of Relativity is Bertrand Russell's most brilliant work of scientific popularisation. With marvellous lucidity he steers the reader who has no knowledge of maths or physics through the subtleties of Einstein's thinking. In easy, assimilable steps, he explains the theories of special and general relativity and describes their practical application to, amongst much else, discoveries about gravitation and the invention of the hydrogen bomb.

    In this one-of-a-kind text, author V. Anton Spraul breaks down the ways that programmers solve problems and teaches you what other introductory books often ignore: how to Think Like a Programmer. Each chapter tackles a single programming concept, like classes, pointers, and recursion, and open-ended exercises throughout challenge you to apply your knowledge. You'll also learn how to:Split problems into discrete components to make them easier to solve Make the most of code reuse with functions, classes, and libraries Pick the perfect data structure for a particular job Master more advanced programming tools like recursion and dynamic memory Organize your thoughts and develop strategies to tackle particular types of problems Although the book's examples are written in C++, the creative problem-solving concepts they illustrate go beyond any particular language; in fact, they often reach outside the realm of computer science. As the most skillful programmers know, writing great code is a creative art—and the first step in creating your masterpiece is learning to Think Like a Programmer.

    The book also provides a balanced presentation of time-varying and static fields, preparingstudents for employment in today's industrial and manufacturing sectors. Streamlined to facilitate student understanding, this edition features worked examples in every chapter that explain how to use the theory presented in the text to solve different kinds of problems. Numerical methods, including MATLAB and vector analysis, are also included to help students analyzesituations that they are likely to encounter in industry practice. Elements of Electromagnetics, Fifth Edition, is designed for introductory undergraduate courses in electromagnetics.

    This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.

    Book by Waring, Chris

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.