# Spectrum of a sentence

In mathematical logic, the **spectrum of a sentence** is the set of natural numbers occurring as the size of a finite model in which a given sentence is true.

## Definition[edit]

Let *ψ* be a sentence in first-order logic. The *spectrum* of *ψ* is the set of natural numbers *n* such that there is a finite model for *ψ* with *n* elements.

If the vocabulary for *ψ* consists only of relational symbols, then *ψ* can be regarded as a sentence in existential second-order logic (ESOL) quantified over the relations, over the empty vocabulary. A *generalised spectrum* is the set of models of a general ESOL sentence.

## Examples[edit]

- The spectrum of the first-order formula

is , the set of powers of a prime number. Indeed, with for and for , this sentence describes the set of fields; the cardinality of a finite field is the power of a prime number.

- The spectrum of the monadic second-order logic formula is the set of even numbers. Indeed, is a bijection between and , and and are a partition of the universe. Hence the cardinality of the universe is even.
- The set of finite and co-finite sets is the set of spectra of first-order logic with the successor relation.
- The set of ultimately periodic sets is the set of spectra of monadic second-order logic with a unary function. It is also the set of spectra of monadic second-order logic with the successor function.

## Properties[edit]

*Fagin's theorem* is a result in descriptive complexity theory that states that the set of all properties expressible in existential second-order logic is precisely the complexity class NP. It is remarkable since it is a characterization of the class NP that does not invoke a model of computation such as a Turing machine. The theorem was proven by Ronald Fagin in 1974 (strictly, in 1973 in his doctoral thesis).

### Equivalence to Turing machines[edit]

As a corollary, Jones and Selman showed that a set is a spectrum if and only if it is in the complexity class NEXP.^{[1]}

One direction of the proof is to show that, for every first-order formula , the problem of determining whether there is a model of the formula of cardinality *n* is equivalent to the problem of satisfying a formula of size polynomial in *n*, which is in NP(n) and thus in NEXP of the input to the problem (the number *n* in binary form, which is a string of size log(*n*)).

This is done by replacing every existential quantifier in with disjunction over all the elements in the model and replacing every universal quantifier with conjunction over all the elements in the model. Now every predicate is on elements in the model, and finally every appearance of a predicate on specific elements is replaced by a new propositional variable. Equalities are replaced by their truth values according to their assignments.

For example:

For a model of cardinality 2 (i.e. *n*= 2) is replaced by

Which is then replaced by

where is truth, is falsity, and , are propositional variables. In this particular case, the last formula is equivalent to , which is satisfiable.

The other direction of the proof is to show that, for every set of binary strings accepted by a non-deterministic Turing machine running in exponential time ( for input length x), there is a first-order formula such that the set of numbers represented by these binary strings are the spectrum of .

Jones and Selman mention that the spectrum of first-order formulas without equality is just the set of all natural numbers not smaller than some minimal cardinality.

### Other properties[edit]

The set of spectra of a theory is closed under union, intersection, addition, and multiplication. In full generality, it is not known if the set of spectra of a theory is closed by complementation; this is the so-called Asser's Problem.

## See also[edit]

## References[edit]

**^*** Jones, Neil D.; Selman, Alan L. (1974). "Turing machines and the spectra of first-order formulas".*J. Symb. Log*.**39**(1): 139–150. doi:10.2307/2272354. JSTOR 2272354. Zbl 0288.02021.

- Fagin, Ronald (1974). "Generalized First-Order Spectra and Polynomial-Time Recognizable Sets" (PDF). In Karp, Richard M. (ed.).
*Complexity of Computation*. Proc. Syp. App. Math. SIAM-AMS Proceedings. Vol. 7. pp. 27–41. Zbl 0303.68035. - Grädel, Erich; Kolaitis, Phokion G.; Libkin, Leonid; Maarten, Marx; Spencer, Joel; Vardi, Moshe Y.; Venema, Yde; Weinstein, Scott (2007).
*Finite model theory and its applications*. Texts in Theoretical Computer Science. An EATCS Series. Berlin: Springer-Verlag. doi:10.1007/3-540-68804-8. ISBN 978-3-540-00428-8. Zbl 1133.03001. - Immerman, Neil (1999).
*Descriptive Complexity*. Graduate Texts in Computer Science. New York: Springer-Verlag. pp. 113–119. ISBN 0-387-98600-6. Zbl 0918.68031. - Durand, Arnaud; Jones, Neil; Markowsky, Johann; More, Malika (2012). "Fifty Years of the Spectrum Problem: Survey and New Results".
*Bulletin of Symbolic Logic*.**18**(4): 505–553. arXiv:0907.5495. Bibcode:2009arXiv0907.5495D. doi:10.2178/bsl.1804020.