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. By a result in descriptive complexity, a set of natural numbers is a spectrum if and only if it can be recognized in nondeterministic exponential time.
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Definition
Let ψ be a sentence in firstorder 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 secondorder logic (ESOL) quantified over the relations, over the empty vocabulary. A generalised spectrum is the set of models of a general ESOL sentence.
Examples
 The spectrum of the firstorder 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 secondorder 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 cofinite sets is the set of spectra of firstorder logic with the successor relation.
 The set of ultimately periodic sets is the set of spectra of monadic secondorder logic with a unary function. It is also the set of spectra of monadic secondorder logic with the successor function.
Descriptive complexity
Fagin's theorem is a result in descriptive complexity theory that states that the set of all properties expressible in existential secondorder 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).
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 firstorder 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 nondeterministic Turing machine running in exponential time ( for input length x), there is a firstorder formula such that the set of numbers represented by these binary strings are the spectrum of .
Jones and Selman mention that the spectrum of firstorder formulas without equality is just the set of all natural numbers not smaller than some minimal cardinality.
Other properties
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 socalled Asser's problem. By the result of Jones and Selman, it is equivalent to the problem of whether NEXPTIME = coNEXPTIME; that is, whether NEXPTIME is closed under complementation.^{[2]}
See also
References
 ^ Jones, Neil D.; Selman, Alan L. (1974). "Turing machines and the spectra of firstorder formulas". J. Symb. Log. 39 (1): 139–150. doi:10.2307/2272354. JSTOR 2272354. Zbl 0288.02021.
 ^ Szwast, Wiesław (1990). "On the generator problem". Zeitschrift für Mathematische Logik und Grundlagen der Mathematik. 36 (1): 23–27. doi:10.1002/malq.19900360105. MR 1030536.
 Fagin, Ronald (1974). "Generalized FirstOrder Spectra and PolynomialTime Recognizable Sets" (PDF). In Karp, Richard M. (ed.). Complexity of Computation. Proc. Syp. App. Math. SIAMAMS 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: SpringerVerlag. doi:10.1007/3540688048. ISBN 9783540004288. Zbl 1133.03001.
 Immerman, Neil (1999). Descriptive Complexity. Graduate Texts in Computer Science. New York: SpringerVerlag. pp. 113–119. ISBN 0387986006. 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. S2CID 9507429.