This introduction to quantum algorithms is concise but comprehensive, covering many key algorithms. It is mathematically rigorous but requires minimal background and assumes no knowledge of quantum theory or quantum mechanics. The book explains quantum computation in terms of elementary linear algebra; it assumes the reader will have some familiarity with vectors, matrices, and their basic properties, but offers a review of all the relevant material from linear algebra. By emphasizing computation and algorithms rather than physics, this primer makes quantum algorithms accessible to students and researchers in computer science without the complications of quantum mechanical notation, physical concepts, and philosophical issues.
After explaining the development of quantum operations and computations based on linear algebra, the book presents the major quantum algorithms, from seminal algorithms by Deutsch, Jozsa, and Simon through Shor’s and Grover’s algorithms to recent quantum walks. It covers quantum gates, computational complexity, and some graph theory. Mathematical proofs are generally short and straightforward; quantum circuits and gates are used to illuminate linear algebra; and the discussion of complexity is anchored in computational problems rather than machine models.
Quantum Algorithms via Linear Algebra is suitable for classroom use or as a reference for computer scientists and mathematicians.
In this book, Sanjoy Mahajan shows us that the way to master complexity is through insight rather than precision. Precision can overwhelm us with information, whereas insight connects seemingly disparate pieces of information into a simple picture. Unlike computers, humans depend on insight. Based on the author’s fifteen years of teaching at MIT, Cambridge University, and Olin College, The Art of Insight in Science and Engineering shows us how to build insight and find understanding, giving readers tools to help them solve any problem in science and engineering.
To master complexity, we can organize it or discard it. The Art of Insight in Science and Engineering first teaches the tools for organizing complexity, then distinguishes the two paths for discarding complexity: with and without loss of information. Questions and problems throughout the text help readers master and apply these groups of tools. Armed with this three-part toolchest, and without complicated mathematics, readers can estimate the flight range of birds and planes and the strength of chemical bonds, understand the physics of pianos and xylophones, and explain why skies are blue and sunsets are red.
The Art of Insight in Science and Engineering will appear in print and online under a Creative Commons Noncommercial Share Alike license.
Category theory was invented in the 1940s to unify and synthesize different areas in mathematics, and it has proven remarkably successful in enabling powerful communication between disparate fields and subfields within mathematics. This book shows that category theory can be useful outside of mathematics as a rigorous, flexible, and coherent modeling language throughout the sciences. Information is inherently dynamic; the same ideas can be organized and reorganized in countless ways, and the ability to translate between such organizational structures is becoming increasingly important in the sciences. Category theory offers a unifying framework for information modeling that can facilitate the translation of knowledge between disciplines.
Written in an engaging and straightforward style, and assuming little background in mathematics, the book is rigorous but accessible to non-mathematicians. Using databases as an entry to category theory, it begins with sets and functions, then introduces the reader to notions that are fundamental in mathematics: monoids, groups, orders, and graphs—categories in disguise. After explaining the “big three” concepts of category theory—categories, functors, and natural transformations—the book covers other topics, including limits, colimits, functor categories, sheaves, monads, and operads. The book explains category theory by examples and exercises rather than focusing on theorems and proofs. It includes more than 300 exercises, with solutions.
Category Theory for the Sciences is intended to create a bridge between the vast array of mathematical concepts used by mathematicians and the models and frameworks of such scientific disciplines as computation, neuroscience, and physics.
Downloadable instructor resources available for this title: 193 exercises, separate from those included in the book, with solutions
The combination of two of the twentieth century’s most influential and revolutionary scientific theories, information theory and quantum mechanics, gave rise to a radically new view of computing and information. Quantum information processing explores the implications of using quantum mechanics instead of classical mechanics to model information and its processing. Quantum computing is not about changing the physical substrate on which computation is done from classical to quantum but about changing the notion of computation itself, at the most basic level. The fundamental unit of computation is no longer the bit but the quantum bit or qubit. This comprehensive introduction to the field offers a thorough exposition of quantum computing and the underlying concepts of quantum physics, explaining all the relevant mathematics and offering numerous examples. With its careful development of concepts and thorough explanations, the book makes quantum computing accessible to students and professionals in mathematics, computer science, and engineering. A reader with no prior knowledge of quantum physics (but with sufficient knowledge of linear algebra) will be able to gain a fluent understanding by working through the book.
In the natural science of ancient Greece, music formed the meeting place between numbers and perception; for the next two millennia, Pesic tells us in Music and the Making of Modern Science, “liberal education” connected music with arithmetic, geometry, and astronomy within a fourfold study, the quadrivium. Peter Pesic argues provocatively that music has had a formative effect on the development of modern science—that music has been not just a charming accompaniment to thought but a conceptual force in its own right.
Pesic explores a series of episodes in which music influenced science, moments in which prior developments in music arguably affected subsequent aspects of natural science. He describes encounters between harmony and fifteenth-century cosmological controversies, between musical initiatives and irrational numbers, between vibrating bodies and the emergent electromagnetism. He offers lively accounts of how Newton applied the musical scale to define the colors in the spectrum; how Euler and others applied musical ideas to develop the wave theory of light; and how a harmonium prepared Max Planck to find a quantum theory that reengaged the mathematics of vibration. Taken together, these cases document the peculiar power of music—its autonomous force as a stream of experience, capable of stimulating insights different from those mediated by the verbal and the visual.
This title is available in an enhanced iBook version through the iTunes iBook store. This innovative e-book for iOS devices gives seamless and easy access to the text and illustrations; you need merely touch a sound example to hear it and see the score in a moving line.
Quantum chemistry--a discipline that is not quite physics, not quite chemistry, and not quite applied mathematics--emerged as a field of study in the 1920s. It was referred to by such terms as mathematical chemistry, subatomic theoretical chemistry, molecular quantum mechanics, and chemical physics until the community agreed on the designation of quantum chemistry. In Neither Physics Nor Chemistry, Kostas Gavroglu and Ana Simões examine the evolution of quantum chemistry into an autonomous discipline, tracing its development from the publication of early papers in the 1920s to the dramatic changes brought about by the use of computers in the 1970s. The authors focus on the culture that emerged from the creative synthesis of the various traditions of chemistry, physics, and mathematics. They examine the concepts, practices, languages, and institutions of this new culture as well as the people who established it, from such pioneers as Walter Heitler and Fritz London, Linus Pauling, and Robert Sanderson Mulliken, to later figures including Charles Alfred Coulson, Raymond Daudel, and Per-Olov Löwdin. Throughout, the authors emphasize six themes: epistemic aspects and the dilemmas caused by multiple approaches; social issues, including academic politics, the impact of textbooks, and the forging of alliances; the contingencies that arose at every stage of the developments in quantum chemistry; the changes in the field when computers were available to perform the extraordinarily cumbersome calculations required; issues in the philosophy of science; and different styles of reasoning.
In 2000, Russian scientist Zhores Alferov shared the Nobel Prize for Physics for his discovery of the heterojunction, a semiconductor device the practical applications of which include LEDs, rapid transistors, and the microchip. The Prize was the culmination of a career in Soviet science that spanned the eras of Stalin, Khrushchev, and Gorbachev--and continues today in the postcommunist Russia of Putin and Medvedev. In Lenin’s Laureate, historian Paul Josephson tells the story of Alferov’s life and work and examines the bureaucratic, economic, and ideological obstacles to doing state-sponsored scientific research in the Soviet Union. Lenin and the Bolsheviks built strong institutions for scientific research, rectifying years of neglect under the Czars. Later generations of scientists, including Alferov and his colleagues, reaped the benefits, achieving important breakthroughs: the first nuclear reactor for civilian energy, an early fusion device, and, of course, the Sputnik satellite. Josephson’s account of Alferov’s career reveals the strengths and weaknesses of Soviet science--a schizophrenic environment of cutting-edge research and political interference. Alferov, born into a family of Communist loyalists, joined the party in 1967. He supported Gorbachev’s reforms in the 1980s, but later became frustrated by the recession-plagued postcommunist state’s failure to fund scientific research adequately. An elected member of the Russian parliament since 1995, he uses his prestige as a Nobel laureate to protect Russian science from further cutbacks. Drawing on extensive archival research and the author’s own discussions with Alferov, Lenin’s Laureate offers a unique account of Soviet science, presented against the backdrop of the USSR’s turbulent history from the revolution through perestroika.
More than half the globe is covered by visible clouds. Clouds control major parts of the Earth’s energy balance, influencing both incoming shortwave solar radiation and outgoing longwave thermal radiation. Latent heating and cooling related to cloud processes modify atmospheric circulation, and, by modulating sea surface temperatures, clouds affect the oceanic circulation. Clouds are also an essential component of the global water cycle, on which all terrestrial life depends. Yet clouds constitute the most poorly quantified, least understood, and most puzzling aspect of atmospheric science, and thus the largest source of uncertainty in the prediction of climate change. Because clouds are influenced by climate change, and because complex, unidentified feedback systems are involved, science is faced with many unanswered questions. This volume begins by indentifying and describing the baffling nature of clouds. It explores the boundaries of current knowledge on the spatial/temporal variability of clouds and cloud-related aerosols as well as the factors that control clouds, and examines the extent and nature of anthropogenic perturbations. Particular emphasis is given to the connections of clouds to climate through radiation, dynamics, precipitation, and chemistry, and to the difficulties in understanding the obvious but elusive fact that clouds must be affected by climate change. Utilizing the insights of this unique gathering of experts, the book offers recommendations to improve the current state of knowledge and direct future research in fields ranging from chemistry and theoretical physics to climate modeling and remote satellite sensing.
This text offers an introduction to quantum computing, with a special emphasis on basic quantum physics, experiment, and quantum devices. Unlike many other texts, which tend to emphasize algorithms, Quantum Computing without Magic explains the requisite quantum physics in some depth, and then explains the devices themselves. It is a book for readers who, having already encountered quantum algorithms, may ask, "Yes, I can see how the algebra does the trick, but how can we actually do it?" By explaining the details in the context of the topics covered, this book strips the subject of the "magic" with which it is so often cloaked.
Quantum Computing without Magic covers the essential probability calculus; the qubit, its physics, manipulation and measurement, and how it can be implemented using superconducting electronics; quaternions and density operator formalism; unitary formalism and its application to Berry phase manipulation; the biqubit, the mysteries of entanglement, nonlocality, separability, biqubit classification, and the Schroedinger's Cat paradox; the controlled-NOT gate, its applications and implementations; and classical analogs of quantum devices and quantum processes.
Quantum Computing without Magic can be used as a complementary text for physics and electronic engineering undergraduates studying quantum computing and basic quantum mechanics, or as an introduction and guide for electronic engineers, mathematicians, computer scientists, or scholars in these fields who are interested in quantum computing and how it might fit into their research programs.
Control and communications engineers, physicists, and probability theorists, among others, will find this book unique. It contains a detailed development of approximation and limit theorems and methods for random processes and applies them to numerous problems of practical importance. In particular, it develops usable and broad conditions and techniques for showing that a sequence of processes converges to a Markov diffusion or jump process. This is useful when the natural physical model is quite complex, in which case a simpler approximation (a diffusion process, for example) is usually made.
The book simplifies and extends some important older methods and develops some powerful new ones applicable to a wide variety of limit and approximation problems. The theory of weak convergence of probability measures is introduced along with general and usable methods (for example, perturbed test function, martingale, and direct averaging) for proving tightness and weak convergence.
Kushner's study begins with a systematic development of the method. It then treats dynamical system models that have state-dependent noise or nonsmooth dynamics. Perturbed Liapunov function methods are developed for stability studies of non-Markovian problems and for the study of asymptotic distributions of non-Markovian systems. Three chapters are devoted to applications in control and communication theory (for example, phase-locked loops and adoptive filters). Small-noise problems and an introduction to the theory of large deviations and applications conclude the book.
This book is the sixth in The MIT Press Series in Signal Processing, Optimization, and Control, edited by Alan S. Willsky.