MATH 220BC: Mathematical Logic - Course Review
This is a review and summary for course MATH 220BC, given by Professor Artem Chernikov and Andrew Marks.
In this post, I listed important theorems (in my mind) like a dictionary, so I can recall what I learnt when I read this in future. Only the overview and summary may be useful to other people.
Overview
This is the first math course I took at UCLA. Due to time schedule, I didn't take 220A, but I read though a online note and memorized important conclusions. I could somehow catch up with B and C part.
220B is based on the textbook A First Journey through Logic. The book is too brief, but the professor's lectures are clear. This part is more related to computer science, as we discussed computability and Turing machines. I heard that CS 181 covers something similar, but I think 220B is more on the math side.
220C is the most tough course I have ever took. The professors made really great lectures, but the course material is very complex and counterintuitive. (Well, maybe because I don't have correct intuitions) I feel that this part is more related to analysis.
Basic Model Theory
Model theory works on formal theories and their models. Most of the following results depend on infinite models. For exmaple, compactness does not hold if we require every model to be finite.
First Order Logic
First order logic is obtained by augmenting propositional logic with two quantifiers: the existential quantifier and the universal quantifier. These quantifiers iterate over all possible values (the base set), but cannot refer to propositional formulas. There are redundencies in logic connectors and quantifiers. A minimal definition of a FOL language will contain the following:
- Logical symbols (shared by all languages)
- Equality relation:
- Connectives: ,
- The existential quantifier:
- The variable set: ,
- The signature of
- A set of constant symbols, .
- Sets of functions, for -ary functions.
- Sets of relations, for -ary relations.
We can define disjunction , implication , equivalence and the universal quantifier based on these symbols.
We can define terms and formulas of this language:
- A term is something that can be interpreted as some value. It can be one of the following:
- A variable.
- A constant symbol.
- A function call: , where and is a term.
- An atomic formula is some elementary proposition:
- , with terms.
- , where and is a term.
- A formula is a finite composition of atomic formulas:
- , where is an atomic formula.
- , where is an atomic formula.
- , where are atomic formulas.
- , where is an atomic formula and is a variable.
- We can define free occurrence, bound occurrence, similtaneous substitution just as we do in programming languages.
- A sentence is a formula with no free variables.
A language decides what formula we can write, but does not specify its meaning. An interpretation of this language, is an -structure :
- has a non-empty base set .
- maps every constant to an element in : for all .
- maps every -ary function to a (well-defined) -ary function on : for all .
- maps every -ary relation to a (well-defined) -ary relation on : for all .
Then, we can define semantics:
- An assignment is a function that maps variables to the base set.
- Given a term , a model and an assignment , we can calculate the value of , be substitute the variables with assignments.
- Similarly, we can decide the truth value of a formula. Denote if its true.
- A formula is universally valid, i.e. tautology, if true in all structures.
- Propositional tautologies, equality axioms and quantifier axioms are always universally valid.
Completeness and Soundness
An -theory is a set of -sentences. Its elements are called axioms. A -model is an -structure where every axiom of is true.
Any sentence in a theory can be one of the three different cases:
- True in all -models. Then, is called a -theorem.
- False in all -models. Equivalent to that is a theorem.
- True in some models, but false in others. Then, is called independent of .
A formal proof is a finite sequence of sentences, where each sentence is obtianed by any of the following:
- An axiom of .
- A predicate calculus tautology, an equality axiom, or a quantifier axiom
- Modus Ponens (MP) from two previous sentences.
- Universal generalization from a previous sentences. (From to ).
If a formal proof of ends in , then proves : . A theory is consistent if it cannot prove for any . The following theorems show that a sentence has a formal proof iff it's true in all models.
Soundness: If , is true in all models.
Gödel's Completeness Theorem or Model existence theorem: Every consistent theory has a model. Hence, a sentence that is true in all models can always be proven.
This is proven by constructing a model for an arbitrary theory. See also: Henkin witness
Craig’s Interpolation Theorem: Let be a -sentence and be a -sentence. Suppose . Then, there exists a sentence s.t. and .
Compactness & Up and Down
Compactness Theorem: A theory is consistent if and only if every finite subset of it is consistent.
This is equivalent to the completeness theorem, as every formal proof must be finite. On the other hand, we can also use Łoś’s Theorem to give a direct model.
- Two structures and are elementarily equivalent , if they satisfy the same sentences.
- If for every formula and , iff , then is an elementary substructure (or submodel) of : .
- Clearly, elementary substructures are equivalent.
But the reverse is not true, i.e. subset + elementary equivalent ≠ elementary substructure.
- For example, and are isomorphic and equivalent, but is not a elementary substructure of . Consider and .
Tarski-Vaught Test: Suppose . Consider formula and . If whenever there exists some satisfying (), there also exists some satisfying (), then .
Downward Löwenheim–Skolem theorem: Let be a -structure and . Then, for any cardinal s.t. , there is an elementary submodel of of size containing . Note: every language is at least countable.
Proof sketch: For every existence formula , define Skolem function as follows: if there exists some s.t. is true, let be any ; if there does not exists such , let be any element. Take a superset s.t. . Take the closure of under of all possible (at most many).
Note: though this proof uses AC, there exists a proof without AC for the countable case.
Upward Löwenheim–Skolem theorem: Let be a -structure. Then, for any cardinal s.t. , there is an elementary extension of of size .
Proof idea: Use diagram method.
Omitting Types Theorem(型排除定理):
- A partial n-type (in theory ) is a (usually infinite) set of -variable formulas consistent with . Formally, is consistent for all finite subset .
- A model realizes if it is satisfiable in ; otherwise, omits .
- is isolated if there is a single formula that is equivalent to , i.e. for all .
- A complete n-type is a maximal partial n-type . That is, for all -formula , either or .
The theorem states that for a theory of a countable language and any countably many non-isolated partial types, there exists a model of that omits all given types.
Saturated Model: Suppose there is an -structure .
- For , an partial n-type (of ) over is a set of -formulas in language , that is consistent with the theory of . Formally, for all finite subset , there is some s.t. .
- A complete n-type over is a maximal partial -type over .
- We define the term realize, omit and isolate similar to types of theories.
- is -saturated if for all , every 1-type over is realized.
- is recursively saturated if all recursively definable 1-type is realized.
Lindström's Theorem: FOL is the strongest logic satisfying both compactness and Downward Löwenheim–Skolem property.
Algebraic Closed Field
Quantifier elimination: A structure or a theory admits quantifier elimination if every formula is equivalent to a quantifier-free formula. It is proven that if every formula in the form with quantifier free has a quantifier free form, then the theory or structure admits quantifier elimination.
Algebraically closed field: A field is algebraically closed if every non-constant polynomial has a root.
The theory of algebraically closed field, ACF, admits quantifier elimination.
Lefschetz principle: For a -formula , the following are equivalent:
- is true in some ACF of characteristic 0.
- is true in every ACF of characteristic 0.
- is true in ACFs of characteristic for arbitrarily large . (i.e. for an infinite set of prime numbers)
- is true in ACFs of characteristic for sufficiently large . (i.e. for all )
Ax's theorem: For all polynomial functions , if is injective, then is also surjective.
Recursion Theory
Recursion theory studies computability and computable functions.
Primitive Recursive Functions
Primitive recursive functions: A primitive recursive function is a -ary function on natural numbers obtained by the following:
- Basic functions:
- Successor ;
- Constant zero ;
- Projection
- Composition of p.r. functions:
- Recursion:
- ;
A subset of is p.r. iff its characteristic function is p.r.
One can prove that p.r. functions and sets are stable under:
- Boolean combinations (, , )
- Definition by cases
- Bounded sums and products
- Bounded -operator:
- is the smallest natural number s.t. ; 0 if there does not exist.
- Bounded quantification.
We can also define the following functions:
- Combine numbers into one.
- Functions s.t. .
- Finite sequences of natural numbers, Gödel number.
- s.t. is a natural number
Ackermann function: defined as follows:
- ;
- ;
- .
This version is designed for the sake of proof, not the version that people generally use. In this version, is exponentiation, is (basically) tetration, and is (basically) pentation.
The finite powers of Ackermann functions, for times, give bounds of p.r. functions.
- A function dominates if for some .
- If is obtained by no more than times of recursions, then there exists some s.t. dominates .
One can prove that all are p.r., but itself is not, because cannot bound itself .
More generally, we cannot define "computable functions" concept, say set , with all of the following properties:
- is countable: .
- is closed under desired operations like recursion, composition, etc.
- There is a "computer": , .
- All functions on are total: terminates on all inputs.
This is because does not equal to any . We cannot drop 2 and 3, and 1 is implied by 3. Thus, to properly define the concept of "computability", we have to drop 4.
Partial Recursive Functions
A partial function from is a function for some . We use to denote the set of partial functions. We say converges at , , for ; diverges at , , for .
The set of partial recursive functions is the smallest set satisfying the following:
- contains the basic functions.
- is stable under composition (of partial functions).
- is stable under recursion (of partial functions).
- is stable under (unbounded) -operator:
is defined as
- if is the minimal element s.t. and is defined for all .
- is not defined otherwise.
A total function is (total) recursive if it is a partial recursive function.
Recursive functions are computable functions. (Church’s Thesis) Every intuitively computable function is recursive.
Universal Functions
Universal Functions: There exists s.t. every that is partial recursive equals to some . Moreover, is partial recursive.
s-m-n Theorem: For any natural numers and , there exists a p.r. function s.t.
In programming world, this is partial application, or currying.
Kleene’s Fixed Point Theorem: For any total recursive function and , there exists s.t. .
Elimination of Recursion: The set of total recursive functions is the smallest set that
- Contains , , ;
- Contains , , , ;
- Is stable under composition;
- Is stable under total -operator.
- Total -operator is the unbounded -operator but only applicable when it always converges.
In other words, recurion is only used to define addition, multiplication and comparison.
Recursively Enumerable Sets
Recursively enumerable sets have many equivalent definitions. Suppose , then the following are equivalent:
- is either empty or the range of a total recursive function .
- That is, there exists a recursive function that enumerates elements of , but not necessarily in order.
- is either empty or the range of a p.r. function.
- is a projection of some recursive set .
- is a projection of some p.r. set .
- is the domain of a partial recursive function .
The set of r.e. sets is stable under intersection, union, projection, bounded universal quantification, image (replacement) under recursive functions.
Theorem of the Complement: A set is recursive if and only if both and are r.e.
the Halting Problem: The domain of is a r.e. set but not recursive. The set of indices of Turing machines that halt on the empty input is r.e. but not recursive.
Rice's Theorem: Suppose is a set of one-variable partial recursive functions that is non-empty nor full. Then, the indices is not recursive.
Kolmogorov complexity: Given , let be the least s.t. . One can prove that there does not exist an infinite r.e. set s.t. for all .
Models of Arithmetic
In this part, we study the models of natural numbers. Since we can encode all programs into natural numbers, we can bring them into FOL formulas and try to formally define "provability".
Decidability
If a language has a finite signature, then we can assign each symbol to a Gödel number, and encode every term, formula, and proof into a natural number.
- The set of codes of formulas and logical axioms of are p.r. sets
- There exist p.r. functions that simulate substitution of terms and formulas.
- The set of formal proofs is a p.r. set.
- The set of tautologies is r.e.
Given a -theory ,
- is recursive if the code of axioms of is recursive.
- is recursively (or effectively) axiomatizable if there exists a recursive theory that has the same theorem of .
- is decidable if the set of codes of theorems of is recursive.
- If is recursive, then the formal proofs of , , is recursive.
- is effectively axiomatizable iff is r.e.
- If is effectively axiomatizable and complete, then is decidable.
- If is decidable, then the theory of plus a finite set of axioms is also decidable.
Peano Arithmetic
We work in the language of arithmetic . In this language, we can express any (standard) natural number as :
- ;
- .
The weak Peano axioms is the finite theory consisting of the following 8 axioms:
- has no predecessor.
- (A1)
- Every non-zero number has a predecessor.
- (A2)
- Two numbers with equal successors are equal.
- (A3)
- is the identity of addition.
- (A4)
- Successor commutes with addition.
- (A5)
- is the zero of multiplication.
- (A6)
- Multiplication is distributive over successor.
- (A7)
- "Less" means "subtractable".
- (A8)
The Peano axioms is the infinite theory PA, consisting of and the axiom (schema) of induction.
- There exists a model of that both addition and multiplication are neither commutative nor associative, and is not a total order.
- The standard natural number is isomorphic to an initial segment of any model.
- In a model of PA:
- Addition and multiplication are commutative and associative.
- Multiplication is distributive w.r.t. addition.
- is a total order.
Arithmetical Hierarchy: Every FOL formula can be classified into the following hierarchy:
- is if is is equivalent to a formula with only bounded quantifiers;
- is , if it is equivalent to a formula in the form , where is ;
- is , if it is equivalent to a formula in the form , where is ;
- is if it is both and .
- Sometimes people write , and . The superscript means counting number quantifiers instead of function quantifiers.
Any sentence satisfied in is a theorem of .
Representability Theorem: Every total recursive function is represented by a formula. A set is r.e. iff there is a formula defining it in . Here, "represent" means:
Overspill: Let be a non-standard model of PA and a formula. If for all , , then there exists non-standard s.t. .
Pigeonhole Principle: For any PA model , -formula and :
In other words, if a predicate maps infinite many numbers () into a finite number of elements (), then there exists a fixed number () that is the image of infinitely many numbers.
MacDowell-Specker Theorem: Any countable model of PA has an elementary end extension.
First Incompleteness Theorem
The Diagonal Argument: For every formula , there exists a sentence s.t. is equivalent to in .
Fixed Point Theorem: For all , there exists a sentence s.t.
Proof: Take .
Tarski’s Theorem on the Non-definability of Truth: In any model of , there does not exist a formula s.t. iff .
Corollary: The theorems of are undecidable.
Church's Theorem: Any consistent theory containing is undecidable.
Corollary 1: The tautologies of the finite language is undecidable.
Corollary 2: The tautologies of a language that consists only one binary relation is undecidable.
Corollary 3: The tautologies of a language that consists of a unary predicate and a constant is decidable.
Gödel’s First Incompleteness Theorem: Any consistent and recursive theory containing is incomplete.
Rosser's Variant: Rosser writes down an independent sentence that witnesses this theorem. Let be consistent and recursive. Let represents the set of formal proofs of , i.e. proves . Let represents the negation of formula, i.e. is . Set:
That means,
- for standard numbers and , proves ;
- for non-standard numbers , there does not exist a proof for the negation of .
Then, is independent.
Remark: If we directly use as , then cannot prove , but may prove . does not imply when is non-standard, so no contradiction.
Second Incompleteness Theorem
Though general satisfiability is undecidable, if we limit the complexity of formula, we can get decidable results. For example, satisfiability of formulas.
Provably Total Functions: Suppose represents . If PA proves that for any (even non-standard) numbers , there is exactly one that satisfies , then is provably total . Formally,
- Every p.r. function is provably total
- Not every recursive function is provably total (though representable).
- There is a universal provably total function , in the sense that: for every provably total function there exists s.t. .
Definability of Satisfiability for Formulas: There exists a -formula s.t. for all -sentence ,
The proof uses certificate method.
Definition of Provability: For a recursive theory , there exists an operator on sentences s.t.
- If is a -sentence, ;
- For any sentence , .
Löb's Axioms: for any sentence ,
- (Necessitation Rule, N) ;
- (Distribution Axiom, K) ;
- (4) .
Corollaries:
- If , then ;
- (GL) ;
- If , then ;
- If , then .
See also: Modal Logic, Provability Logic, Kripke Semantics.
Gödel’s Second Incompleteness Theorem: Let be a computable theory. Then, it is impossible to prove for any in . More specifically, let denote the consistency of : . Then, cannot prove .
Tenenbaum’s Theorem: There is no recursive non-standard model of PA. That is, for any countable non-standard model of PA, there is no way to code the elements of the model as (standard) natural numbers such that either the addition or multiplication operation of the model is a computable on the codes. SA: Non-standard model of arithmetic, Standard and Nonstandard Numbers.
Set Theory
Axiomatic set theory studies models of set theory. Since the whole world of logic is built upon set theory, we cannot find a structure like and define it as a "standard model". However, assuming the consistency of the theory, there are models developed based on the universe that we are in.
Cumulative Hierarchy
Language of Set Theory: . Other symbols can be developed as abbreviations of -formulas.
The Axiom Schema of Comprehension: The only axiom for naive set theory, is that every logic formula has a set corresponding to it:
Cantor's Diagonal Argument: For all set , there is no surjection .
- Cantor's paradox: Let . Then, is part of .
Russel's Paradox: Let . Then, is not a set. This proves that the axiom schema of comprehension is inconsistent.
The Axioms of ZF: To avoid the inconsistency, the construction of sets must be limited. Basic axioms of axiomatic set theory include the following. Models of set theory generally satisfy all or a major part of them:
- The axiom of Extensionality: Every set is determined by its members.
- .
- The axiom of Foundation: Every non-empty set contains a -minimal element.
- Let abbreviate .
- The axiom of Pairing: Given two sets, there is a set containing exactly them.
- .
- We can let denote this set; use denote .
- We can define ordered pair .
- The axiom of Union:
Given any set of sets , there is set containing exactly all the element of these sets.
- Let denote .
- .
- The axiom of Nullset: There is a set with no elements.
- The axiom of Infinity: There exists an inductive set.
- .
- The axiom of Powerset: For every set x, there is a set containing all the subsets of this set.
- Let abbreviate .
- Let abbreviate .
- The axiom schema of Separation: Every definable subset of a set exists.
- The collection of a formula is a class .
- Let abbreviate .
- Note that a proper class "does not exist": .
- We can define cartesian products, relations and functions with this axiom schema.
- The axiom schema of Collection:
If is a set, and defines a class from each element of , then there is a set which meets all these classes.
- .
- The axiom schema of Replacement:
The image of a set under a definable class function is a set.
- .
- This is equivalent to Seperation + Collection in ZF-(Sep+Col).
Axiom of Choice (AC): Every set of pairwise disjoint nonempty sets has a “choice set”.
AC has many equivalent theorems. AC also has some pathological results. However, without a choice axiom, one cannot prove a countble union of countble set is countble. People developed ZF+DC+AD for set theory models that AC is not satisfied. AD is incompatible with AC.
- A strict partial order is a irreflecive and transitive binary relation.
- A strict partial order is linear if any two elements are comparable.
- A strict partial order is wellfounded if every subset contains a minimal element.
- A wellordering is linear wellfounded strict partial order.
- Theorem: Given two wellorderings, either they two are isomorphic, or one is isomorphic to an initial segment of the other. Furthermore, the isomorphism is unique.
- A set is transitive if forall , implies .
- Note: is not necessarily a transitive relation on . For exmaple, .
- An ordinal is a transitive set s.t. on is a wellordering.
- Let denote the class of ordinals.
- Define iff . Then, is a wellordering on .
- Any wellordered set is isomorphic to a unique ordinal, called the order type of .
- Let .
- If , is a successor ordinal;
- Otherwise, is a limit ordinal.
- Let be the intersection of all inductive sets. Then, is the least non-zero limit ordinal. The elements of are natural numbers. Let .
- A class is equal to ORD if it satisfies the following:
- ;
- For all , ;
- If is a (non-zero) limit ordinal, .
- Let be a class function. Then, there is a unique class function s.t. for all ,
.
- Note: Generally, people prove uniqueness first, and then existence.
- We can define ordinal addition, multiplication and exponentiation by recursion.
Cantor normal form: For any ordinal , there uniquely exist natural numbers and ordinals s.t.
Note: It's possible that .
- For each ordinal , define set as:
- ;
- , for any ;
- , for a limit ordinal.
- Let the class be the union of all .
- For , define its rank to be the least ordinal that .
- One can verify that
- The transitive closure of is defined as the smallest transtive set containing ,
- For any , let and . Then, the transitive closure is .
- Assume (ZF minus Foundation), then the axiom of foundation is equivalent to .
- Note: is actually the shorthand for .
Mostowski Collapse: If a relation on a class is wellfounded, setlike and extensional, then there exists a unique transitive class and a unique isomorphism .
- wellfounded: For every non-empty subset of , there exists an -minimal element.
- setlike: is always a set;
- extensional: iff .
Cardinal Arithmetic
Equivalence of AC:
- Zorn's lemma: Given a strict partial order, if every chain has an upper bound, then there is a maximal element.
- Hausdorff Maximality principle: Every partial ordered set has a maximal chain.
- Zermelo’s wellordering theorem or :
Every set can be well-ordered.
- Note: Whether there exists a computable well-ordering of is independent of ZFC.
- The cardinalities of any pair of sets are comparable.
- For all infinite sets , .
AC also implies the partition principle: If there is a surjection from to , then there is an injection from to . But whether this principle implies AC is still open.
Cantor-Shröder-Bernstein theorem:
- Define if there is a bijection.
- Define if there is an injection from to .
- (ZF) If and , then .
- An ordinal is a cardinal if for all , .
- Let denote the -th infinite cardinal; let denote its cardinality.
- Let denote the least cardinal of cardinality greater than .
- Similarly, is a successor cardinal; A non-zero cardinal not in this form is a limit cardinals.
- .
- (ZF) For any set , there is an ordinal that cannot be injected into .
- This ordinal is called Hartog’s number .
- Given an ordinal and , if there does not exist a that is strict greater than
all elements of , then is cofinal in .
- Since no one cares successor ordinals, an equivalent definition is .
- The cofinality is the minimum of order-types of the cofinal subsets of .
- For all , .
- For all , is a cardinal not greater than .
- A cardinal is regular if ; otherwise, singular.
- (ZFC) Every successor cardinal is regular.
- .
- (ZFC) .
- The gimel function of an infinite cardinal is:
.
- Note: If is regular, .
König's theorem: Suppose for all . Then,
Cardinal powers: Suppose are infinite cardinals, then can be one of the following:
- If , then .
- If and , then .
- If and ,
- if , then .
- if , then .
Generalized continuum hypothesis (GCH): GCH states that for all infinite .
- GCH implies that for infinite cardinals
- If , .
- If , .
- If , .
Cardinal exponentiation: Define . Suppose is an infinite cardinal.
- If is regular, then .
- If is singular and is eventually constant as (so is this constant value), then .
- If is singular and is not eventually constant as , then .
Singular cardinals hypothesis (SCH): If singular and , then .
- A (weak) limit cardinal is a cardinal that is neither a successor cardinal nor zero.
- A strong limit cardinal is not reachable by power: for all , .
- A regular limit cardinal is weakly inaccessible.
- If is an uncountable weakly inaccessible cardinal, then is a model of ZFC.
- An uncountable regular cardinal is strongly inaccessible if it is a strong limit:
for all , .
- Then, is a model of ZFC.
- ZFC cannot prove the existence of any uncountable inaccessible cardinal.
Infinitary Combinatorics
- A filter on a set is a collection of subsets of s.t.
- is upward closed under : .
- is non-empty: .
- is closed under finite intersections: .
- is non-trivial if .
- Dually, we can define ideal as a collection of subsets s.t. is downward closed, non-empty and closed under finite union.
- Given a filter , its dual ideal is .
- Given an ideal and its dual filter , a set is -positive/-positive
if .
- A filter is a collection of "large" sets; an ideal is "small"; -positive sets are "not small".
- For , then is the filter generated by .
- A filter is -complete if it is closed under intersections of size less than .
- A ultrafilter
is a filter s.t. for all , exactly one of or .
- Ultrafilters are exactly the filters maximal w.r.t. .
- (The ultrafilter lemma) (ZFC) every filter can be exteneded into an ultrafilter.
- An ultrafilter is principal if there is s.t. iff .
- Suppose is a filter on , is a sequence of real numbers. Then iff for all , .
- This limit satisfies all the usual limit laws.
- If is a non-principal ultrafilter on , then any bounded sequence has an ultralimit .
- A cardinal is measurable if there is a -complete ultrafilter on .
- A cardinal is called real-valued measurable if there is a -additive probability measure on the power set of that vanishes on singletons.
- An atomless measurement on is that, for every with , there is with .
- (Ulam) There are two cases for a real-valued measurable :
- , there is an atomless measurement on . There is also a measure on the full powerset extending Lebesgue measure.
- is measurable. (actually a strong limit). Every measurement on has an atom which yields a -additive -complete ultrafilter.
Ultraproducts: Suppose are structures, and is an ultrafilter on . Let be the set of -sequences that pick one element from each structure:
Let be the equivalence relation on where iff they coincide at the ultrafilter . Now, let the ultraproduct be the structure on universe :
- For each constant of , let ;
- For each relation of , let be true iff ;
- For each function of , let be .
If for all , then is called the ultrapower of by .
Łoś's Theorem: For any -formula and , iff . In particular, the ultraproduct models a sentence iff there is a "large" number of models modeling it.
Keisler-Shelah isomorphism theorem: Two structures and are elementarily equivalent iff there is an ultrafilter s.t. the two ultraproducts are isomorphic .
Asympototic Cone:
- Suppose is a sequence of metric spaces and are base points. Let be the set of sequences where the sequence is bounded. Let be the equivalence relation that if . Let be the metric on where . We define ultraproduct to be .
- Suppose is a given metric space with a base point . The asymptotic cone of is .
- The asymptotic cone is a way of viewing from “infinitely far away”.
- The asymptotic cone of with usual metric is isomorphic to .
Club:
- Suppose a limit ordinal (generally a regular uncountable cardinal) and .
- is closed if it contains all its limit points less than . Formally, for all , being cofinal in implies .
- is unbounded if for all , there exists s.t. .
- A closed unbounded subset is called a club set.
- Suppose a limit ordinal with . Then, the intersection of finitely many clubs is a club.
- Suppose a cardinal with . Then, for all , the intersection of many clubs is a club.
Club filter: Suppose is a regular uncountable cardinal.
- The filter generated by the club sets on is called the club filter on .
- The club filter is -complete.
- A subset of is stationary if it intersects with every club. In other words, club filter positive.
- The dual ideal of the club filter is the nonstationary ideal.
- Note: a set in the club filter is not necessarily a club. It's a set containing club.
Diagonal intersection: Let be a sequence of many subsets of . Their diagonal intersection is defined to be
- The diagonal intersection of many clubs is a club.
- A filter is called normal if it's closed under diagonal intersection. The club filter is normal.
- A non-trivial normal -complete filter on a regular uncountable cardinal includes every club of .
Properties of stationary sets:
- Given a club and stationary set , is stationary.
- A stationary set is unbounded.
- If is stationary, then is also stationary.
- If we partition a stationary set into many sets, then one of them will be stationary.
- An ordinal function on a set is regressive if for every , .
- If is a regressive function on a stationary set of , then there is a stationary subset that fixed . Formally, there exists and a stationary set s.t. for all .
- Example: Suppose there is a train passing through an infinite number of stations. At every station, there is exactly 1 person getting off, and then finitely many people getting on. We know that after stations there could be arbitrarily many people on the train. Fodor's lemma shows that after stations, there must be 0 people on it.
- Suppose is a collection of sets. If for all distinct , , we call a -system with root .
- Suppose is an uncountable set of finite sets. Then there are an uncountable subset and a finite set s.t. is a -system with root .
- Suppose are infinite regular cardinals s.t. for all , . Let be a collection of many sets of cardinality less than . Then, there is a subset of size which is a -system.
Silver’s Theorem:
- If is a singular cardinal of uncountable cofinality and for a stationary set of , then .
- If SCH holds for all singular cardinals of cofinality , then it holds for all singular cardinals.
Infinite trees:
- A tree is a -tree if its height is and every level has size less than .
- Kőnig's lemma: An -tree has an infinite branch.
- Aronszajn tree: There is a -tree with no branches of order type .
- Suslin line
- A linear order on is dense if for all there exists s.t. .
- A subset is dense in if for all there exists s.t. .
- A linear order is complete if any set with an upper bound has a least one, and any set with a lower bound has a greatest one.
- An endpoint is a maximum or minimum element.
- Any two countable dense linear orders without endpoints are isomorphic.
- is isomorphic to any complete dense linear order without endpoints that has a countable dense subset.
- A linear order on is a Suslin line if is a complete dense linear order without endpoints s.t. every set of disjoint open intervals is countable, but has no countable dense set (thus not isomorphic to ).
- Suslin tree
- A Suslin tree is an -tree such that every chain and antichain is countable.
- There is a Suslin line iff there is a Suslin tree.
- Suslin tree is independent of ZFC.
- A -sequence is a sequence where s.t. for all , is stationary.
- is the statement that there exists a -sequence.
- implies CH.
- implies there is a Suslin tree.
- A -sequence is a sequence where s.t. for all , there exists a club s.t. for all , both and are in .
- A -sequence is a sequence where s.t. for all , is stationary.
- is the statement that there exists a -sequence; is the statement that there exists a -sequence.
- implies ; is equivalent to .
Constructible Hierarchy
- By the downward L-S theorem, there exists a countable model of ZFC. However, ZFC proves there exist uncountable ordinals.
- This is not a real paradox, because given the same sets , it is possible that in there exists a bijection from to , but an inner model lacks this bijection.
- Cardinality is not absolute.
- (Theorem) By compactness, there exists a model of ZFC s.t. is not well-founded.
- Such models are not necessarily recursive.
- (Theorem) By Mostowski collapse, every well-founded model is isomorphic to some .
- A model when is a transitive set is called a transitive model.
- A countable transitive model is often abbreviated as ctm.
- Note: ZFC+Con(ZFC) does not imply there is a well-founded set model of ZFC.
Models relation:
- By Tarski’s undefinability of truth, is a well-defined relation only if is a set.
- For any sentence , let denote the sentence where all quantifiers and
are replaced with and .
- For any transitive set model, iff is true.
- When is a proper class, we use to abbreviate .
The Lévy hierarchy: Similar to arithmetic hierarchy, every formula in set theory is categorized into , and .
- If is a formula and is a transitive class. Then for all , we have iff .
- Suppose , are transitive classes and .
- If is , then implies . (upward absoluteness)
- If is , then implies . (downward absoluteness)
- If is , then .
The model :
- If is a limit ordinal, then is a model of Extensionality, Foundation, Pairing, Union, Nullset, Separation, and Powerset.
- If , then is a model of Infinity.
- If is a strongly inaccessible cardinal, then is a model of Collection.
The model :
- If is a cardinal, then is the collection of sets whose transitive closure has size less than .
- For every regular cardinal , is a model of ZFC - Powerset.
- Suppose is a cumulative hierarchy:
- is transitive.
- For all , .
- (Continuous) If is a limit, .
- Let . Then for every formula , there exists a closed and unbounded set of ordinals , s.t. for all sets , iff .
- Corollary: For every finite set of axioms of ZFC, ZFC proves that there is a ctm of these axioms.
- Note: One must give the axioms first, and then find the set.
- Note: It is "For all ..., ZFC proves that ...", but not "ZFC proves that for all ...". Therefore, the compactness theorem does not work here.
- Corollary: ZFC is not finitely axiomatizable.
Gödel's :
- For a set , let be the set of definable sets over with parameters of . The function is .
- Replace with in the definition of , and we will get the constructible universe .
- .
- , for any ;
- , for a limit ordinal;
- .
Properties of :
- (ZF) For all ordinals ,
- and are transitive. is a cumulative hierarchy.
- , so contains all ordinals.
- for each infinite .
- (ZF) is a model of ZF.
- Define a strict partial order on as follows: if the rank of in is less than that of ;
or they have the same -rank but the minimal number of formula defining is less than that of .
Then, is a well-ordering on .
- (ZF) .
- Let abbreviate .
- (The absoluteness of constructibility) If is a transitive class inner model of ZF that contains all ordinals, then . Further, .
- Corollary: is the smallest transitive inner model that contains all ordinals.
- There is a finite set of axioms of ZF-Powerset s.t. if and , then for some limit ordinal .
- There is a sentence s.t. for every transitive set , iff for some limit ordinal .
- For every limit ordinal , if is an elementary submodel, then the transitive collaps of is for some limit ordinal .
- Assume . If is a cardinal and , then for some
.
- models GCH.
- .
- If is an uncountable regular cardinal, then models ZF-Powerset.
- If , then for all cardinals.
Other properties of :
- implies .
- If is weakly inaccessible, then models ZFC.
- implies there is no measurable cardinals.
Forcing
I don't fully understand this topic, so only put basic ideas here.
Forcing is a secret weapon of the logicians. To show that a sentence is consistent of ,
- First, start with a model in which is not necessarily true.
- Punch new elements into and get a structure , where is true.
- Show that is still a model of .
Since downward absolute sentences cannot be forced, forcing only works for "complex enough" sentences.
Since we must "understand" the elements we want to add into , we cannot choose . To have more choices on the missing elements, we want as simple as possible. Therefore, we can use a ctm . The consistency of ZFC does not promise the existence of ctm, but that's a minor issue that can be fixed.
Now, suppose that we want to prove the negation of CH. Observe that:
- has , since it's absolute.
- does not have all subsets of , because otherwise cannot be countable.
- In , there is an injection from to , but cannot see it.
Now, we want to inject this injection into . We cannot directly take a union, because there is no guarantee that we can have a model. Therefore, we use the idea of compactness here: Let be finite partial functions . Define a partial relation to be the reverse of inclusion. (Due to historical reasons, we want small elements be finer) Then,
- There is a unique maximal .
- Every element is part of a multimap from to , .
- Let , then will be a partial function .
- in , because both and are in .
- If , then we say extends or refines .
- If there is some extends both and , we say and are compatible.
- Intuitively, two compatible elements look like in a sublattice, though there does not exist a real lattice. For example, and . Then, refines both and .
- A subset of is called filter if it's upward closed and pointwise compatible.
- This is similar to a lattice filter: nonempty, upward closed, and closed under join .
- is a partial function .
Now we want to make sure that
- The union of is a total function .
- The function that the union of leads to is an injection.
- By augmenting with , we can get a ZFC model.
The concept of generics solves these issues:
- A subset is dense if it can refine every element of .
- is dense below if it can refine every element .
- Suppose is a transitive model containing . A filter is -generic if it meets every dense set. That is, for all dense in , we have .
- For each , the set is dense. Thus, is a total function.
- For all , the set is also dense. Thus, the function is an injection from to .
Now we go back to augment . We want to get a new model s.t. and . Intuitively, consider that we put associate each element and each formula with a "probability". (See Boolean-valued model. Not every textbook discusses this because the evil in details often makes things more complicated.) For every , we bind a "probability" to it as . However, we cannot use because it's clearly not a model: Let and , then cannot be represented. Therefore, we need to define a cumulative hierarchy:
- A set is a -name if every element in is an ordered pair , where is a -name and .
- Equivalently, we have the following hierarchy:
- ;
- ;
- ;
- ;
- Since being a -name is absolute, the set of -names in equals .
What we define is like the language , but works on a "fuzzy" structure with "probabilities". If we cut the "probability" with a "threshold", then hopefully we will get a definite model.
- Let be a -generic. For every -name , the value of under is defined by recursion: .
- For example, let . Suppose . Then is in . Hence, if , ; otherwise, .
- Let be the set of for every -name that is in .
Intuitively, is like a threshold cut, plus Mostowski collapse.
Now we have:
- is transitive.
- By the hierarchical definition of values.
- .
- Let for . Then . Because the maximal is always in , just like probability 1.
- .
- Let . Then, .
Such is not constructibly defined, but always exists, because the following lemma:
- If is a ctm, then for every forcing poset and , there is a -generic filter containing .
- Note: the existence of generic filters comes from that can only see finite subsets of . For example, let be an infinite binary tree. If , then there do not exist a generic filter. Because for every filter , the complement set is dense.
Now we need to show that is a model of ZFC. To show this, we simulate the "threshold cut" process for formulas: for each formula, we define a "probabilistic" value, and then cut it with . Formally, we define the forcing relation s.t.
Note that is well-defined in , since every -name and is in . The only thing does not know is .
We define it as follows:
- Atomic formula :
- An element is in a set if it equals to some element in the set.
- ,
where is the principal ideal .
- Note: in a complete boolean algebra generated by a poset topological space, is , but is not . Actually, is . Here, means the complement set of its closure. And of course, is . For example, in a poset of finite binary strings, does not include the string , but .
- Note; To understand why here we use , consider that an event with probability . It happens when is greater than the cut , which is equivalent to .
- iff is dense below .
- iff is dense below .
- Atomic formula :
- A set is equal to if .
-
- Here, means .
- iff for all and all , .
- iff for all , is dense below , and for all , is dense below .
- Formula :
- .
- iff and .
- Formula :
- .
- iff is dense below .
- Formula :
- iff there is no s.t.
- Formula :
- .
- iff the set of s.t. there exists a -name satisfying is dense below .
- Formula :
- .
- iff for all -name , .
The forcing relation has the following properties:
- Force = Truth lemma. Described above.
- Definability. is a well-defined relation in .
- Coherence.
- If , then for all , .
- If the set is dense below , then .
Now we can prove that is a model by showing evidence as -names in .
Lemma: If is a transitive model and is a -generic, then .
One thing we need to ensure is that in , is the in . This is given by ccc.
Countable chain condition (ccc):
- A poset is ccc if every strong antichain is countable.
- A strong antichain is an antichain whose elements are pairwise incompatible.
- If proves is ccc, then and have exactly the same cardinals.
At last, let's handle the existence of ctm. Not every model of ZFC has a ctm. However, from a metatheorem's view, the reflection theorem ensure that arbitrarily large finite subsets of ZFC axioms have a ctm. If the subset is large enough s.t. whatever we used till now is included, then we can force . Then, by the conpactness theorem, must be consistent with ZFC.
Summary
Things I have learnt:
- Have a basic understanding of mathematical logic. Know what mathematicians in the last century did.
- Logic objects are often organized in an infinite hierarchy. There does not exist an ultimate theory.
- Most useful theory is not complete. There are always not expected models.
- Therefore, the strenth of the theory limits what we can prove.
- Infinite numbers are often counterintuitive.
- The existence of something does not imply is understandable by human beings.
- In different universe, people have different views of the same concept.
References
- Martin Hils, and François Loeser. A First Journey through Logic. American Mathematical Society, 2019.
- Andrew Marks. Set Theory Notes. 2020.
- There are some typos, but none of them will affect the understanding.
- Yiannis N. Moschovakis. Lecture Notes in Logic. 2014.
- Robert I. Soare. Turing Computability: Theory and Applications (1st. ed.). Springer, 2016.
- Thomas Jech. Set Theory: The Third Millennium Edition, revised and expanded. Springer, 2003.
