Book Reviews

Six months ago I sent out an appeal, especially to young people in the field, asking them to let me know if they are interested in writing book reviews for SIAM. I've received several responses, for which I am grateful. In most of these cases I have not yet found an appropriate book for you, but when I do, you will hear from me. There may be some of you out there who have been thinking of contacting me but have not yet done so. If so, it's not too late. Send me an e-mail telling me a little bit about yourself and what you'd like to review. If there is a specific book that you would like to review, by all means let me know. I might just assign it to you. As I said before, writing book reviews can be a fun and rewarding activity.

Our featured review, by Rob Corless, tells us about Nick Trefethen's book Approximation Theory and Approximation Practice. This novel text does not replace the standard works in approximation theory; it complements them by heading off in new directions. It also challenges a number of items of conventional wisdom, for example, the notion that high-degree polynomial interpolants are not good approximants. If you have not had a chance to look at this book, I hope you'll take time to read the review. Since the book's publishing model is novel, a discussion of publishing models is also included.

Of the several other interesting books reviewed in this issue, I was most intrigued by Quantum Algorithms via Linear Algebra: A Primer, by Richard Lipton and Kenneth Regan, reviewed by Rajesh Pereira. No knowledge of physics or quantum mechanics is required. All of the algorithms are explained using linear algebra and basic computer science. Just as we can use a conventional computer to solve problems without knowing about the physics of the computer's components, we can also use quantum algorithms without knowing about the physics of a quantum computer. I've added this to my reading list, and I hope I'll be able to get to it soon.

In this issue we also have informative reviews of books on nonlinear optimization, signal processing, finite elements and fast iterative solvers, linear algebra, uncertainty quantification, and partial differential equations. Please have a look.