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We introduce various ways of representing structures so that we can analyze their computational complexity. At the end of the chapter, see how to code binary information on presentations of structures.
The basic concepts from computablity theory are quickly introduced for readers that haven't seen them in a while, or for readers that are used to different notation.
A relation is nothing more than a set of tuples from a structure. The study of the complexity and definability of this basic concept is one of the main components of computable structure theory.
Among the main objectives of computable structure theory is measuring the computational complexity of structures. There are various ways of doing this. The most common one is through degree spectra.
Existential types capture important computability-theoretic information. When a class of structures realizes much fewer types than possible, there is usually an interesting reason why.
In mathematics, we know there are some concepts - objects, constructions, structures, proofs - that are more complex and difficult to describe than others. Computable structure theory quantifies and studies the complexity of mathematical structures, structures such as graphs, groups, and orderings. Written by a contemporary expert in the subject, this is the first full monograph on computable structure theory in 20 years. Aimed at graduate students and researchers in mathematical logic, it brings new results of the author together with many older results that were previously scattered across the literature and presents them all in a coherent framework, making it easier for the reader to learn the main results and techniques in the area for application in their own research. This volume focuses on countable structures whose complexity can be measured within arithmetic; a forthcoming second volume will study structures beyond arithmetic.