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Definable Closure and Algebraic Independence

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Definable Closure and Algebraic ClosureStability Theory: IntroductionMorley Rank and Degree: Dimension in Strongly Minimal Sets
definable-closure algebraic-closure independence dimension

Core Idea

In a model M, the definable closure dcl(A) is the set of elements definable by formulas with parameters from A; the algebraic closure acl(A) is the set of elements in finitely-defined sets from A. These notions generalize field-theoretic closures and provide a dimension notion for any model. Independence of sets is captured via forking: sets are independent if no element in one is algebraic over the other.

Explainer

You already know from definable and algebraic closure that a model M provides two natural ways to extend a parameter set A inward. The definable closure dcl(A) collects every element b in M that is uniquely pinned down by some first-order formula with parameters from A — that is, the formula φ(x, ā) is satisfied by b and b alone. The algebraic closure acl(A) is more permissive: it collects every element b that lives in a finite set definable with parameters from A. The formula φ(x, ā) may have finitely many solutions, and b is one of them. So dcl(A) ⊆ acl(A) always. In a dense linear order, acl(A) = A itself because no finite set of points is definable from finitely many endpoints unless the point is already there. In an algebraically closed field, acl(A) is exactly the field-theoretic algebraic closure of A.

The field analogy is the right one to carry forward. In field theory, a set of elements is algebraically independent over a base field F if no element of the set is algebraic over F and the others — that is, no element satisfies a nonzero polynomial with coefficients in F ∪ {the others}. Model theory generalizes this: a set B is independent over A if no element of B is algebraic over A ∪ (B minus that element). The precise technical definition uses forking: B is independent from C over A if the type of B over A ∪ C does not fork over A. In stable theories, forking captures exactly the failure of algebraic independence — an element forks over A if it is algebraically constrained by the new parameters beyond what A already forced.

The payoff is a robust dimension theory that works for any sufficiently well-behaved model. A basis of M over A is a maximal independent set; all bases have the same cardinality, called the dimension (or Morley rank in the categorical case). This mirrors the fact that all bases of a vector space have the same cardinality, or all transcendence bases of a field extension have the same degree. The model-theoretic version applies not just to fields and vector spaces but to any stable theory — including certain theories of graphs, groups, and combinatorial structures — wherever forking defines a well-behaved independence relation. Recognizing that dcl, acl, and independence are three interlocking tools that together give a model-theoretic substitute for linear algebra is the central conceptual step in understanding stability theory and its applications.

Practice Questions 5 questions

Prerequisite Chain

Understanding ZeroThe Number ZeroCounting to FiveCounting to 10Counting to 20Counting a Set of Objects Up to 20Cardinality: The Last Number CountedMatching Numerals to QuantitiesSubitizing Small QuantitiesAddition Within 10Number Bonds to 10Addition Within 20Doubles and Near DoublesDoubles Facts Within 10Near Doubles Facts Within 20Mental Math Strategies for AdditionMental Math: Adding and Subtracting TensAddition Within 100Repeated Addition as MultiplicationMultiplication as Equal GroupsMultiplication: ArraysBasic Multiplication Facts (0s, 1s, 2s, 5s, 10s)Multiplication Facts Within 100Division as Equal SharingDivision as Grouping (Measurement Division)Division: Grouping (Repeated Subtraction) ModelDivision: Fair Sharing ModelDivision as Equal SharingDivision as GroupingBasic Division FactsDivision Facts Within 100Multiplication and Division Fact FamiliesRelationship Between Multiplication and DivisionDivision Facts as Inverse of MultiplicationRemainders and Quotients in DivisionDivision Word ProblemsMulti-Step Word ProblemsSolving Multi-Step Word ProblemsMultiplication Word ProblemsDivision Word ProblemsIntroduction to Long DivisionFactors and MultiplesPrime and Composite NumbersEquivalent FractionsRelating Fractions and DecimalsDecimal Place ValueIntegers and the Number LineComparing and Ordering IntegersAbsolute ValueAdding IntegersSubtracting IntegersMultiplying IntegersIntroduction to ExponentsOrder of OperationsInteger Order of OperationsVariable ExpressionsThe Distributive PropertyVariables and Expressions ReviewIntroduction to PolynomialsAdding and Subtracting PolynomialsMultiplying PolynomialsFactorialPermutationsCombinationsCounting Principles: Addition and Multiplication RulesIntroduction to Graph TheoryPropositional Logic FoundationsLogical EquivalencesBoolean AlgebraIntroduction to Propositional LogicIntroduction to Predicate Logic (First-Order Logic)First-Order Logic SyntaxTerms and Atomic Formulas in FOLVariable Binding and ScopeOpen and Closed Formulas in First-Order LogicVariable Substitution and Capture-Avoidance in First-Order LogicQuantifier Instantiation Rules in First-Order Proof SystemsUniversal Quantification: Meaning and ScopeFree Variables and Bound VariablesSubstitution and Instantiation in Predicate LogicTerms and Atomic FormulasFormulas and Well-Formed ExpressionsStructures and InterpretationsModel Interpretation and SatisfactionInterpretation, Truth, and Satisfaction of FormulasLogical Consequence and EntailmentSatisfiability and UnsatisfiabilityConsistency and Inconsistency of TheoriesConsistency and InconsistencyBasic Model TheoryCompactness Theorem in Model TheoryLöwenheim-Skolem Theorems: Overview and UnificationUpward Löwenheim-Skolem TheoremCategorical Theories and Uniqueness of ModelsMorley's Theorem on Uncountable CategoricityStability Theory: IntroductionDefinable Closure and Algebraic Independence

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