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An arithmetical proof relation represents the effective relation that a natural number encodes a formal proof of the logical formula with a specified Gödel number. With the usual coding apparatus its proof-checking relation is bounded. Existential quantification over the formal proof code gives the ordinary arithmetical provability predicate.

For an effectively axiomatized arithmetic theory, a arithmetical provability predicate expresses that a formal proof of the sentence with a specified code exists. If axioms are only enumerated, proof certificates also record finite stages at which their axioms appear. The resulting predicate is arithmetically expressible.

Take precisely the propositional tautologies as axioms and supply no inference rules. A one-line proof then establishes exactly the valid propositional formulas, so this calculus is sound and complete for theoremhood. Its axiom set is decidable by finite truth tables. This construction does not by itself give strong completeness for consequence from arbitrary assumptions.

An axiom set is the collection of formulas available as axioms in a specified formal proof system. It may be finite or infinite, or specified by an axiom scheme.

Given a bounded-complete one-consistent arithmetic first-order theory with a false theorem, enumerate first-order sentences and successively choose one-consistent one-sentence extensions. Every stage has Sigma-1 soundness, and a false Sigma-1 theorem in the union would already have a formal proof at one stage. The union is therefore one-consistent and complete while retaining the false theorem. It cannot be omega-consistent, since a complete bounded-complete omega-consistent first-order theory is sound.

Examination paper of the University of Oxford, Preliminary Examination in Computer Science, Trinity Term 2015, dated 19 June 2015. The original has seven pages; the last contains the prescribed natural deduction rules. Released archive: Lawrence Attachment.zip, member 2015-cs4.pdf. The paper's printed section order is linear algebra, digital electronics, and introduction to formal proof, despite the different ordering in its cover title.

A first-order theory is consistent when it has no formal proof of a contradiction. This syntactic property concerns the specified calculus; its equivalence with having a first-order model uses the completeness theorem.

A conclusion is formally derivable from premises when a permitted formal proof exists with those premises as its undischarged assumptions. This is a syntactic relation, distinct from semantic entailment.

Establishing specified properties of a system using formal proofs about a precise model. Formal verification connects an implementation to a formal specification; correctness of the model and its assumptions still matters when applying the result to a physical system.

For a small example, the summation loop verification below starts with executable steps and asks two separate questions: does any returned value satisfy the postcondition, and does execution reach that return? A loop invariant answers the first; a loop variant answers the second. This turns an unbounded family of permitted inputs into a few reusable proof obligations.

The model must specify programming language semantics, including the meaning of variable assignments, comparisons and integer arithmetic. A proof about exact mathematical integers need not describe a machine that wraps on integer overflow. Similarly, a correct formal proof of a weak or mistaken formal specification does not establish the intended behavior. Choosing the right formal specification and relating the model to the implemented system remain substantive tasks.

Software testing examines chosen executions and can expose a counterexample. A formal proof instead justifies a statement throughout its stated model; it does not require executing every permitted input. This makes formal verification valuable when rare boundary cases matter, while software testing can still reveal an incorrect model or misunderstood requirement.

In 1969, Tony Hoare presented rules for variable assignment, composition and iteration in a small programming language. His paper explicitly says those rules do not prove successful termination, and discusses the dependence of arithmetic reasoning on the chosen overflow behavior. These reservations already make the model's scope part of the argument.^[ref]

A Hilbert proof system specifies axiom schemes and inference rules, commonly including modus ponens. A formal proof is a finite sequence of axiom instances, permitted assumptions and conclusions obtained from preceding lines by those rules. Soundness and completeness compare this syntactic derivability with semantic validity or semantic entailment. These properties concern the particular chosen axioms and rules.

Starting from a recursively axiomatized arithmetic first-order theory $T_0$ with the usual arithmetical provability predicates, defineIf every stage is first-order consistent, the Gödel second incompleteness theorem makes every step strict in the consistency-strength preorder: the next stage proves the preceding stage's formal consistency statement, which that preceding stage cannot prove. Every formal proof from the effective union $T_{\omega }={\bigcup }_{n<\omega }{T}_n$ uses only finitely many axioms and lies in one stage. Thus the union is first-order consistent under this hypothesis and lies strictly above every finite stage. Arithmetic soundness of $T_0$ is a sufficient starting assumption, since each added formal consistency statement is then true in the standard natural numbers.

Consistency of $T_0$ alone does not ensure consistency of the next stage. Assuming Peano arithmetic is first-order consistent, $T_0=\mathrm{PA}+\neg \mathrm{Con}(\mathrm{PA})$ is first-order consistent by the Gödel second incompleteness theorem. Proof inclusion makes it prove $\neg \mathrm{Con}(T_0)$, so adding $\mathrm{Con}(T_0)$ produces an inconsistent next stage. The hypotheses for a progression must therefore distinguish a consistent starting theory from consistency of all its iterates.

Logical falsity, written $\perp$, is a zero-input logical connective interpreted as false under every Boolean valuation. In standard Intuitionistic propositional logic and classical propositional logic, it has no introduction rule that produces it without premises. The logical falsity elimination rule permits deriving any logical formula from it.

A formal proof can derive $\perp$ from contradictory assumptions: $P$ together with $\neg P$ gives it by the negation elimination rule. A first-order theory is first-order consistent when it has no assumption-free proof of $\perp$ from its own axioms. Thus having no proof is a consistency property of a specified formal proof system, rather than an unconditional definition of logical falsity.

Mathematical logic studies formal languages, formal proofs, model theory, computability theory, and the foundations of mathematics. It makes the rules of reasoning explicit enough that reasoning itself becomes an object of mathematics. Proof theory studies deductions; model theory studies interpretations in which statements hold.

Three questions organize the subject: is an expression a well-formed first-order formula, is it true in a specified first-order structure, and does it have a formal proof from specified axioms? These questions are distinct. For example, $\exists n(n+n=1)$ is a first-order sentence in an appropriate first-order language; it is false in the natural numbers but true in the rational numbers, with $n=1/2$.

The beauty of mathematical logic is that the same logical connectives and rules of universal quantification and existential quantification organize arguments across mathematics. Classical propositional logic uses two truth values; Intuitionistic propositional logic interprets logical implication through constructions on proofs, without unrestricted law of excluded middle. This proof-based framework is developed in Frank Pfenning, Natural Deduction, sections 1–3.

A mathematical proof is a finite deductive argument from stated assumptions to a conclusion. It explains why the conclusion follows for every instance covered by its hypotheses. An informal mathematical proof can omit routine detail while making its assumptions and deductions clear; a formal proof expresses them in a specified formal language with specified inference rules. The distinction between assumptions, propositions, and deductions is introduced in Leighton and Rubinfeld, What is a proof?, sections 1–3.

Checking examples can suggest a pattern, but need not establish a universally quantified claim. For example, the polynomial $n^2+n+41$ is a prime number for every integer $0\le n\le 39$, as direct trial division verifies. At $n=40$ it equals $1681=41^2$, a composite number. Those first forty successes do not prove the claim for all natural numbers; one counterexample disproves it. The point is not to discard computation: it can find a conjecture, detect a mistake, or verify a finite exhaustive case analysis. The question is whether the cases checked cover the statement being claimed.

For a positive example, the sum of two even integers is even: writing them as $2a$ and $2b$ with $a,b\in \mathbb{Z}$ gives $2a+2b=2(a+b)$, and $a+b$ is an integer. This direct argument handles every allowed pair at once. A useful mathematical proof therefore does more than certify an answer: it exposes the mechanism and the exact assumptions that make the answer transferable.

Suppose both extensions were inconsistent. By the explosion argument in (i), the extension by $\varphi$ proves $\neg \varphi$, and the extension by $\neg \varphi$ proves $\varphi$. The deduction theorem for propositional logic therefore yieldsThe identity theorem gives $⊢\neg \varphi \to \neg \varphi$ and $⊢\varphi \to \varphi$. Apply E to the first displayed logical implication and the identity logical implication with antecedent $\neg \varphi$ to obtain $\Gamma ⊢\neg \varphi$. Apply E to the identity logical implication with antecedent $\varphi$ and the second displayed logical implication to obtain $\Gamma ⊢\varphi$. This contradicts propositional consistency of $\Gamma$.

Consequently at least one of the two one-formula extensions is propositionally consistent. The formal proof uses the source's own calculus, including its rule E, rather than assuming an unproved completeness theorem for this presentation.

Inclusion gives $|\mathbb{R}\setminus \mathbb{Q}|\le \mathfrak{c}$. If $\kappa =|\mathbb{R}\setminus \mathbb{Q}|$, the disjoint decomposition of $\mathbb{R}$ givesThe irrational numbers are infinite, for instance $n+\sqrt{2}$ are pairwise distinct irrationals. Standard infinite cardinal addition gives ${\aleph }_0+\kappa =\max ({\aleph }_0,\kappa )$. Since Cantor's theorem gives $\mathfrak{c}>{\aleph }_0$, the equality forces $\kappa =\mathfrak{c}$. ThereforeThis is the permitted cardinal-arithmetic formal proof; it does not subtract infinite cardinals as though they were finite numbers.

There is a three-line Hilbert formal proof. Use A1 with $\alpha =\chi$, $\beta =\psi$; then use A3 with $\alpha =\chi$, $\beta =(\psi \to \chi )$:This is a direct logical derivation in the displayed Hilbert proof system. Neither the deduction theorem for propositional logic nor a completeness theorem for propositional logic is needed: the desired logical implication is just the contrapositive, supplied by A3, of the particular A1 instance on line 1.

Yes, for soundness and completeness of theoremhood. An axiom-only complete propositional calculus is obtained as follows. Declare every propositional tautology, and only such a tautology, to be an axiom; supply no inference rules. A formal proof then consists of a single axiom. Every proved logical formula is valid, giving soundness, and every valid logical formula is already an axiom, giving completeness.

This is not merely an unspecified collection: whether a finite propositional formula is a tautology is decidable by its finite truth table, so the axiom set can be recognized effectively. It is a deliberately uninformative Hilbert proof system, since all the work has been put into axiom recognition. If one instead asked for strong completeness of derivations from arbitrary additional assumptions, a system whose only formal proof lines are axioms or assumptions would not suffice; the affirmative construction here concerns $⊢\varphi$ versus $\models \varphi$.

Gödel's completeness theorem for first-order sentences says that, in a standard sound first-order Hilbert calculus,Equivalently every first-order consistent set of first-order sentences has a first-order model: apply this existence statement to $T\cup \{\neg \sigma \}$ for the consequence formulation.

For the first-order model existence formal proof use a Henkin construction. Enlarge the language by fresh constant symbols and adjoin Henkin witness axiomsFreshness of $c_{\theta }$ preserves first-order consistency. In detail, if a contradiction followed after adjoining one witness axiom, the deduction theorem for first-order logic would yield its negation, from which one obtains both $\exists x\theta (x)$ and $\neg \theta (c_{\theta })$ over the old theory. Since the new constant symbol does not occur in that theory or in $\theta$, replace it by a fresh logical variable and generalize to derive $\forall x\neg \theta (x)$, a contradiction. Finitely many witness additions preserve first-order consistency successively, and unions preserve first-order consistency because formal proofs are finite. Iterate the enlargement so that logical formulas involving newly introduced constant symbols also receive witnesses. Include at least one constant symbol to guarantee closed terms.

Extend the resulting first-order consistent witnessed first-order theory to a maximal consistent set of first-order sentences $H$. In the equality-free case make the domain the set of closed terms. Interpret constant symbols and function symbols by their formal first-order term constructions; interpret an atomic formula byThe truth lemma for a Henkin term model follows by induction on logical formulas with closed terms substituted for their free variables. The logical connective steps use maximal consistency of a first-order theory. In the existential step, membership of $\exists x\theta$ supplies a witness constant and hence a first-order term satisfying $\theta$; conversely a satisfying closed term gives the existential sentence by an inference of the calculus. The term model consequently satisfies $H$ and the original theory. Equality is absent here, so distinct closed terms may remain distinct domain elements without further identifications.

For a countable first-order language, the Henkin construction introduces only countably many constant symbols: each round needs at most one for each logical formula, there are countably many finite strings in a countable alphabet, and countably many rounds suffice. There are therefore at most countably many closed terms. The term model, and also its quotient set by equality, has at most countably many elements.

It follows that every satisfiable theory in a countable first-order language has an at most countable first-order model. If the theory has no finite first-order model, the constructed first-order model is countably infinite. More generally the same counting argument gives a first-order model of cardinality at most $\max (|L|,{\aleph }_0)$ for any satisfiable theory in language $L$.

For the elementary-substructure version of the downward Löwenheim-Skolem theorem, begin with a first-order structure $M$ and a set $S$ of designated elements. Close $S$, the named constant symbols and one initial element under the language's functions and under chosen witnesses in $M$ for existential formulas with parameters already chosen. Iterate countably often. The resulting set has cardinality at most $\max (|L|,|S|,{\aleph }_0)$, and its induced substructure $N$ is elementary: induction on logical formulas proves the truth equivalence, with the existential case supplied by the chosen witnesses. This is the same witness mechanism as the Henkin formal proof, now keeping witnesses inside a given first-order model.