1985, with Harold Abelson, Julie Sussman*Structure and Interpretation of Computer Programs*.*Functional Differential Geometry*. 2013, with Jack Wisdom*Structure and Interpretation of Classical Mechanics: 2nd edn*. 2014, with Jack Wisdom

- Numercial Evidence that the Motion of Pluto is Chaotic. 1988. (In
*Feynman and Computation*) - Cellular Gate Technology. 1998. (In
*Unconventional Models of Computation, UMC'98*) - A Memory. 2002. (In
*Feynman and Computation*) - Cellular computation and communication using engineered genetic regulatory networks. 2004. (In
*Cellular Computing*) - Description and Modeling. 2004. (In
*Unifying Themes in Complex Systems II*) - Genetic process engineering. 2004. (In
*Cellular Computing*)

This book presents a unique conceptual introduction to programming
intended to give readers command of the major techniques used
to control the complexity of large software systems:
building abstractions, establishing conventional interfaces,
and establishing new descriptive languages.

Physics is naturally expressed in mathematical language.
Students new to the subject must simultaneously learn
an idiomatic mathematical language and the content that is expressed in that language.
It is as if they were asked to read *Les Misérables*
while struggling with French grammar.
This book offers an innovative way to learn the differential geometry
needed as a foundation for a deep understanding of general relativity
or quantum field theory as taught at the college level.

The approach taken by the authors (and used in their classes at MIT for many years) differs from the conventional one in several ways, including an avoidance of the use of traditional index notation for tensors in favor of a semantically richer language of vector fields and differential forms. But the single biggest difference is the authors’ integration of computer programming into their explanations. By programming a computer to interpret a formula, the student soon learns whether or not a formula is correct. Students are led to improve their program, and as a result improve their understanding.

We now know that there is much more to classical mechanics than previously suspected.
Derivations of the equations of motion,
the focus of traditional presentations of mechanics, are just the beginning.
This innovative textbook, now in its second edition,
concentrates on developing general methods for studying the behavior of classical systems,
whether or not they have a symbolic solution.
It focuses on the phenomenon of motion and makes extensive use of computer simulation
in its explorations of the topic.
It weaves recent discoveries in nonlinear dynamics throughout the text,
rather than presenting them as an afterthought.
Explorations of phenomena such as the transition to chaos,
nonlinear resonances, and resonance overlap to help
the student develop appropriate analytic tools for understanding.
The book uses computation to constrain notation, to capture and formalize methods,
and for simulation and symbolic analysis.
The requirement that the computer be able to interpret any expression
provides the student with strict and immediate feedback about whether an expression is correctly formulated.

This second edition has been updated throughout, with revisions that reflect insights gained by the authors from using the text every year at MIT. In addition, because of substantial software improvements, this edition provides algebraic proofs of more generality than those in the previous edition; this improvement permeates the new edition.