Here is a list of books you wouldn’t want to be without (except for those in section 5). It was compiled in response to a question about what books should be included in a “starter kit" for a college library.
Astonishing masterpieces. I have read these books over and over again. They have been called “a physicist’s physics books”. Every physicist and every physics student should have instant access to them.
Many people are inspired by these books. As reference books or supplemental texts they are wonderful. As primary texts they are appropriate for some but not for all; weaker students get “indigestion" as Feynman himself noted in the epilogue.
Exceptional, epochal high school physics text.
A review in The Textbook Letter (May-June 1992) called this “an outstanding and inspiring book, strongly recommended” and “the best high-school physics textbook that we have seen.” http://www.textbookleague.org/32pssc1.htm
|This book is for people who want to understand the material.||In contrast, the general herd of textbooks seem to merely go through the motions of covering the material, allowing people to check off the little boxes that say “we covered this” and “we covered that”.|
|This book has remarkably good “quality control”. That is, you can generally believe what it says.||Textbooks in the general herd are riddled with errors and misconceptions.|
I recommend that everyone who teaches introductory physics should read this book, and keep a copy in the classroom as a reference, for the use of teacher and students alike.
Uncommonly good. The gold standard. Compared to other calculus texts, these books are full of surprises: sometimes more practical, sometimes more rigorously formal, and sometimes both at once. See reference 1.
‘The” book on special relativity. Takes the geometric approach, which is far easier to understand than the older approach. Simple as well as profound. Intuitive as well as practical.
A masterpiece. The “Track 1" sections are quite readable, even poetic in places. Some “Track 2" sections are quite advanced. Includes a modern, no-nonsense discussion of special relativity, which is the best I’ve seen anywhere.
Marking the sections Track 1 and Track 2 is a nice feature unto itself. It supports the spiral approach. Plan on reading the book more than once. On each successive iteration you can incorporate more of the Track 2 material.
The gold standard. Authoritative, but not particularly easy to read.
Widely known and revered in the mathematics community, but almost unknown elsewhere, for no good reason. Recommended for anybody who is (or plans to become) either a practitioner or a teacher in any branch of science, math, or engineering.
This book is remarkable for talking about the thinking process itself, and also about the teaching process. That includes thinking about teaching, and teaching about thinking.
A wonderful book. Easy to read. Starts with the basics and progresses to advanced topics. Combines elegant theory with down-to-earth practical advice.
Far and away the most sensible thermo text I’ve seen. Gets right many things that other books get wrong. May be too terse for some students in introductory courses, i.e. some supplementary explanation of the key ideas may be helpful.
A standard. Surprisingly readable.
The gold standard. Remarkably readable and remarkably informative.
This book covers a huge range of material, starting at a low level and progressing to a high level. (I don’t think any human could learn it all in one year, so if you use the book as a text, a first course would have to stop in the middle ... and an advanced course would have to start in the middle. Either way, it makes a good reference book.)
All books on this topic suffer from a chicken-and-egg problem: you can’t understand the physics until you have learned the math, and you can’t motivate the math until you have learned the physics. This book deals with this issue better than most similar books. That is, the book is a bit dry, but not nearly as dry as you might have feared given the topic.
Good algorithms, good focus on scientific applications, good explanations.
A classic. Brilliant. Getting slightly dated in a few places, but still well worth reading.
Get the “Student Edition" – identical contents, half the price.
Beware: lots of misprints and typos in the equations ... but the ideas are there, with the usual Feynmanesque mixture of practicality and sophistication.
Some people love it, some look down on it ... which is fine for a library book (but not for a required text).
This is good solid physics. (Don’t be put off by the title.)
Readable enough for 8-year-olds; informative enough for adults.
I would hope the library already has this!
A monumental masterpiece.
Still worth reading, not just a conversation piece.
Actually what you want is Stillman Drake, Two New Sciences 2nd edition, which is a nicely annotated English translation of the above.
You can still learn from this book, even after all these years. It’s amazing how far Galileo got, especially considering how little he had to start with. Parts of it read like an open letter to Newton, telling him what to do. The book is more likely to appeal to hard-core physicists than to casual students.
This contains the entire text of Sobel’s Longitude, plus illustrations.
The history of cryptography up to but not including public-key cryptography. Reads like a novel.
Book lists similar in spirit to this one can be found in reference 2 and reference 3.
Note: When shopping for books, you should not place much faith in the ratings on the amazon.com web site. It is disappointing but not terribly surprising that a merchant might find ways to filter out unflattering reviews.
As far as I can tell, there aren’t any good books on data analysis or experimention in general. Bevington is better than Taylor, but that’s nothing to brag about.
A library might be obliged to carry one or both of these books, but I can’t say I recommend either of them.
This book includes some data-analysis software, which is a good idea in principle, but the quality of the software is terrible, including loops that could (and commonly do) loop forever, depending on the data. If you get the rough ideas from this book, and then use algorithms from some other source such as item 15, that might be the best you can do at the moment.
This is sometimes called “the train book” because of the cover, which features a crashed train at the Gare Montparnasse, 22 October 1895. It’s a beautiful photograph, but alas it conveys completely the wrong idea about what we mean by “error” in the context of error analysis.
In the first 70 pages, the book contains many formulas, none of which can safely be applied to real data, as far as I can tell.