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MATH 220BC: Mathematical Logic - Course Review

· 62 min read
Xinyu Ma
Research Scientist @ Meta

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 L\mathcal{L} will contain the following:

  • Logical symbols (shared by all languages)
    • Equality relation: ==
    • Connectives: \neq, \wedge
    • The existential quantifier: \exists
    • The variable set: vnv_n, nNn\in\mathbb{N}
  • The signature of L\mathcal{L}
    • A set of constant symbols, C\mathcal{C}.
    • Sets of functions, Fn\mathcal{F}_n for nn-ary functions.
    • Sets of relations, Rn\mathcal{R}_n for nn-ary relations.

We can define disjunction \vee, implication \rightarrow, equivalence \leftrightarrow and the universal quantifier \forall 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: f(t1,,tn)f(t_1,\ldots, t_n), where fFnf\in\mathcal{F}_n and tit_i is a term.
  • An atomic formula is some elementary proposition:
    • t1=t2t_1 = t_2, with t1,t2t_1,t_2 terms.
    • R(t1,,tn)R(t_1, \ldots, t_n), where rRnr\in\mathcal{R}_n and tit_i is a term.
  • A formula is a finite composition of atomic formulas:
    • ϕ\phi, where ϕ\phi is an atomic formula.
    • ¬ϕ\neg\phi, where ϕ\phi is an atomic formula.
    • ϕχ\phi\wedge\chi, where ϕ,χ\phi,\chi are atomic formulas.
    • xϕ\exists x\phi, where ϕ\phi is an atomic formula and xx 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 L\mathcal{L}-structure A\mathfrak{A}:

  • A\mathfrak{A} has a non-empty base set AA.
  • A\mathfrak{A} maps every constant to an element in AA: cAAc^{\mathfrak{A}}\in A for all cCc\in\mathcal{C}.
  • A\mathfrak{A} maps every nn-ary function to a (well-defined) nn-ary function on AA: fA:AnAf^{\mathfrak{A}}: A^n\to A for all fFnf\in\mathcal{F}_n.
  • A\mathfrak{A} maps every nn-ary relation to a (well-defined) nn-ary relation on AA: rAAnr^{\mathfrak{A}}\subseteq A^n for all rRnr\in\mathcal{R}_n.

Then, we can define semantics:

  • An assignment is a function α\alpha that maps variables to the base set.
  • Given a term tt, a model A\mathfrak{A} and an assignment α\alpha, we can calculate the value of tt, tA[α]t^{\mathfrak{A}}[\alpha ] be substitute the variables with assignments.
  • Similarly, we can decide the truth value of a formula. Denote Aϕ[α]\mathfrak{A}\models \phi[\alpha ] 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 L\mathcal{L}-theory TT is a set of L\mathcal{L}-sentences. Its elements are called axioms. A TT-model is an L\mathcal{L}-structure where every axiom of TT is true.

Any sentence ϕ\phi in a theory TT can be one of the three different cases:

  • True in all TT-models. Then, ϕ\phi is called a TT-theorem.
  • False in all TT-models. Equivalent to that ¬ϕ\neg\phi is a theorem.
  • True in some models, but false in others. Then, ϕ\phi is called independent of TT.

A formal proof is a finite sequence of sentences, where each sentence is obtianed by any of the following:

  • An axiom of TT.
  • 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 ϕ\phi to xϕ\forall x\phi).

If a formal proof of TT ends in ϕ\phi, then TT proves ϕ\phi: TϕT\vdash \phi. A theory is consistent if it cannot prove ϕ¬ϕ\phi\wedge\neg\phi for any ϕ\phi. The following theorems show that a sentence has a formal proof iff it's true in all models.

Soundness: If TϕT\vdash\phi, ϕ\phi 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 ϕ\phi be a L1\mathcal{L}_1-sentence and ψ\psi be a L1\mathcal{L}_1-sentence. Suppose ϕψ\models \phi\to\psi. Then, there exists a L0:=L1L2\mathcal{L}_0 := \mathcal{L}_1\cap\mathcal{L}_2 sentence ρ\rho s.t. ϕρ\models\phi\to\rho and ρψ\models\rho\to\psi.

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 M\mathfrak{M} and N\mathfrak{N} are elementarily equivalent MN\mathfrak{M}\equiv\mathfrak{N}, if they satisfy the same sentences.
  • If for every formula ϕ(x1,,xn)\phi(x_1,\ldots, x_n) and aˉMn\bar{a}\in M^n, Mϕ(aˉ)\mathfrak{M}\models\phi(\bar{a}) iff Nϕ(aˉ)\mathfrak{N}\models\phi(\bar{a}), then M\mathfrak{M} is an elementary substructure (or submodel) of N\mathfrak{N}: MN\mathfrak{M}\prec\mathfrak{N}.
  • Clearly, elementary substructures are equivalent. But the reverse is not true, i.e. subset + elementary equivalent ≠ elementary substructure.
    • For example, M=(N+,<)\mathfrak{M} = (\mathbb{N}_+, <) and N=(N,<)\mathfrak{N} = (\mathbb{N}, <) are isomorphic and equivalent, but M\mathfrak{M} is not a elementary substructure of N\mathfrak{N}. Consider ϕ(y):=x(x<y)\phi(y) := \exists x(x< y) and y=1y=1.

Tarski-Vaught Test: Suppose MN\mathfrak{M}\subseteq \mathfrak{N}. Consider formula ϕ(x1,,xn,y)\phi(x_1,\ldots, x_n,y) and aˉ=(a1,,an)Mn\bar{a}=(a_1,\ldots,a_n)\in M^n. If whenever there exists some uNu\in N satisfying ϕ(aˉ,y)\phi(\bar{a},y) (Nyϕ(aˉ,y)\mathfrak{N}\models\exists y\phi(\bar{a}, y)), there also exists some vMv\in M satisfying ϕ(aˉ,y)\phi(\bar{a},y) (Myϕ(aˉ,y)\mathfrak{M}\models\exists y\phi(\bar{a}, y)), then MN\mathfrak{M}\prec\mathfrak{N}.

Downward Löwenheim–Skolem theorem: Let M\mathfrak{M} be a L\mathcal{L}-structure and AMA\subseteq M. Then, for any cardinal κ\kappa s.t. max{L,A}κM\max\{\|\mathcal{L}\|,\|A\|\}\leq \kappa\leq \|M\|, there is an elementary submodel of M\mathfrak{M} of size κ\kappa containing AA. Note: every language is at least countable.

Proof sketch: For every existence formula ϕ:=yψ(x1,,xn,y)\phi:=\exists y\psi(x_1,\ldots, x_n,y), define Skolem function fϕ:MnMf_{\phi}: M^n\to M as follows: if there exists some bb s.t. ψ(a1,,an,b)\psi(a_1,\ldots, a_n,b) is true, let fϕ(a1,,an)f_{\phi}(a_1,\ldots, a_n) be any bb; if there does not exists such bb, let fϕ(a1,,an)f_{\phi}(a_1,\ldots, a_n) be any element. Take a superset SSS\subseteq S' s.t. S=κ\|S'\| = \kappa. Take the closure of SS' under fϕf_{\phi} of all possible ϕ\phi (at most L\|\mathcal{L}\| many).

Note: though this proof uses AC, there exists a proof without AC for the countable case.

Upward Löwenheim–Skolem theorem: Let M\mathfrak{M} be a L\mathcal{L}-structure. Then, for any cardinal κ\kappa s.t. Mκ|M|\leq \kappa, there is an elementary extension of M\mathfrak{M} of size κ\kappa.

Proof idea: Use diagram method.

Omitting Types Theorem(型排除定理):

  • A partial n-type (in theory TT) is a (usually infinite) set of nn-variable formulas π\pi consistent with TT. Formally, T{vˉϕπkϕ}T\cup\{\exists \bar{v}\bigwedge_{\phi\in\pi_k} \phi\} is consistent for all finite subset πk\pi_k.
  • A model M\mathfrak{M} realizes π\pi if it is satisfiable in M\mathfrak{M}; otherwise, M\mathfrak{M} omits π\pi.
  • π\pi is isolated if there is a single formula ϕ\phi that is equivalent to π\pi, i.e. Tvˉ(ϕψ)T\vdash \exists\bar{v}(\phi\to\psi) for all ψπ\psi\in\pi.
  • A complete n-type is a maximal partial n-type π\pi. That is, for all nn-formula ϕ(vˉ)\phi(\bar{v}), either ϕ(vˉ)π\phi(\bar{v})\in\pi or ¬ϕ(vˉ)π\neg\phi(\bar{v})\in\pi.

The theorem states that for a theory TT of a countable language and any countably many non-isolated partial types, there exists a model of TT that omits all given types.

Saturated Model: Suppose there is an L\mathcal{L}-structure M\mathfrak{M}.

  • For AMA\subseteq M, an partial n-type (of M\mathfrak{M}) over AA is a set of nn-formulas π(xˉ)\pi(\bar{x}) in language LA:=L{ca:aA}\mathcal{L}_A := \mathcal{L}\cup\{c_a: a\in A\}, that is consistent with the theory of M\mathfrak{M}. Formally, for all finite subset πk\pi_k, there is some bMb\in M s.t. Mπk(b)\mathfrak{M}\models\pi_k(b).
  • A complete n-type over AA is a maximal partial nn-type over AA.
  • We define the term realize, omit and isolate similar to types of theories.
  • M\mathfrak{M} is κ\kappa-saturated if for all Aκ\|A\|\leq \kappa, every 1-type over AA is realized.
  • M\mathfrak{M} 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 xϕ\exists x\phi with ϕ\phi 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 Lring\mathcal{L}_{ring}-formula ϕ\phi, the following are equivalent:

  • ϕ\phi is true in some ACF of characteristic 0.
  • ϕ\phi is true in every ACF of characteristic 0.
  • ϕ\phi is true in ACFs of characteristic pp for arbitrarily large pp. (i.e. for an infinite set of prime numbers)
  • ϕ\phi is true in ACFs of characteristic pp for sufficiently large pp. (i.e. for all p>Np>N)

Ax's theorem: For all polynomial functions f:CnCnf:\mathbb{C}^n\to\mathbb{C}^n, if ff is injective, then ff is also surjective.

Recursion Theory

Recursion theory studies computability and computable functions.

Primitive Recursive Functions

Primitive recursive functions: A primitive recursive function is a nn-ary function on natural numbers obtained by the following:

  • Basic functions:
    • Successor S:=λx.x+1S := \lambda x. x+1;
    • Constant zero C00:=λ.0C^0_0 := \lambda. 0;
    • Projection Pjn:=λx1xn.xjP^n_j:=\lambda x_1\cdots x_n.x_j
  • Composition of p.r. functions:
    • f:=g(h1,,hn)f := g(h_1,\ldots, h_n)
  • Recursion:
    • f(x1,,xn,0):=g(x1,,xn)f(x_1,\ldots, x_n, 0) := g(x_1,\ldots, x_n);
    • f(x1,,xn,y+1):=h(x1,,y,f(x1,,xn,y))f(x_1,\ldots, x_n, y+1) := h(x_1,\ldots, y, f(x_1,\ldots, x_n,y))

A subset of Nn\mathbb{N}^n is p.r. iff its characteristic function is p.r.

One can prove that p.r. functions and sets are stable under:

  • Boolean combinations (\cap, \cup, \setminus)
  • Definition by cases
  • Bounded sums and products
  • Bounded μ\mu-operator: f(xˉ,z):=(μtz)((xˉ,t)X)f(\bar{x},z):=(\mu t\leq z)((\bar{x},t)\in X)
    • f(xˉ,z)f(\bar{x},z) is the smallest natural number s.t. (xˉ,t)X(\bar{x},t)\in X; 0 if there does not exist.
  • Bounded quantification.

We can also define the following functions:

  • Combine nn numbers into one.
    • Functions αn,βin\alpha_n, \beta^n_i s.t. βin(αn(x1,,xn))=xi\beta^n_i(\alpha_n(x_1,\ldots, x_n)) = x_i.
  • Finite sequences of natural numbers, Gödel number.
    • \langle \cdot \rangle s.t. x1,,xn\langle x_1,\ldots, x_n \rangle is a natural number
    • lg(x1,,xn)=n\text{lg}(\langle x_1,\ldots, x_n \rangle) = n
    • (x1,,xn)i=xi(\langle x_1,\ldots, x_n \rangle)_i = x_i

Ackermann function: ξ:N2N\xi:\mathbb{N}^2\to\mathbb{N} defined as follows:

  • ξ0(x)=ξ(0,x):=2x\xi_0(x) = \xi(0, x) := 2^x;
  • ξy(0)=ξ(y,0):=1\xi_y(0) = \xi(y, 0) := 1;
  • ξy+1(x+1)=ξ(y+1,x+1):=ξ(y,ξ(y+1,x))\xi_{y+1}(x+1) = \xi(y+1, x+1) := \xi(y, \xi(y+1, x)).

This version is designed for the sake of proof, not the version that people generally use. In this version, ξ0\xi_0 is exponentiation, ξ1\xi_1 is (basically) tetration, and ξ2\xi_2 is (basically) pentation.

The finite powers of Ackermann functions, ξnk=ξnξn\xi^k_n = \xi_n\circ\cdots\circ\xi_n for kk times, give bounds of p.r. functions.

  • A function fF1f\in\mathcal{F}_1 dominates gFng\in\mathcal{F}_n if g(xˉ)f(max(xˉ,N))g(\bar{x}) \leq f(\max(\bar{x},N)) for some NN.
  • If ff is obtained by no more than nn times of recursions, then there exists some kNk\in\mathbb{N} s.t. ξnk\xi_n^k dominates ff.

One can prove that all ξn\xi_n are p.r., but ξ\xi itself is not, because ξnk\xi^k_n cannot bound itself ξ\xi.

More generally, we cannot define "computable functions" concept, say set FF, with all of the following properties:

  1. FF is countable: F={f0,f1,}F = \{f_0, f_1,\ldots\}.
  2. FF is closed under desired operations like recursion, composition, etc.
  3. There is a "computer": uFu\in F, u(n,xˉ)=fn(xˉ)u(n, \bar{x}) = f_n(\bar{x}).
  4. All functions on FF are total: fif_i terminates on all inputs.

This is because λn.u(n,n)+1\lambda n. u(n,n)+1 does not equal to any fif_i. 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 NnN\mathbb{N^n}\to\mathbb{N} is a function f:ANf:A\to \mathbb{N} for some ANnA\subseteq\mathbb{N^n}. We use fFnf\in\mathcal{F}^*_n to denote the set of partial functions. We say ff converges at pp, f(p)f(p)\downarrow, for pAp\in A; ff diverges at pp, f(p)f(p)\uparrow, for pAp\notin A.

The set of partial recursive functions is the smallest set EE satisfying the following:

  • EE contains the basic functions.
  • EE is stable under composition (of partial functions).
  • EE is stable under recursion (of partial functions).
  • EE is stable under (unbounded) μ\mu-operator: g(xˉ):=μy(f(xˉ,y)=0)g(\bar{x}) := \mu y(f(\bar{x},y)=0) is defined as
    • g(xˉ)=zg(\bar{x}) = z if zz is the minimal element s.t. f(xˉ,z)=0f(\bar{x},z) = 0 and f(xˉ,y)f(\bar{x},y) is defined for all yzy\leq z.
    • g(xˉ)g(\bar{x})\uparrow 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 φpFp+1\varphi^p\in\mathcal{F}^*_{p+1} s.t. every fFpf\in \mathcal{F}^*_{p} that is partial recursive equals to some φip=λxˉ.φp(i,xˉ)\varphi^p_i = \lambda \bar{x}.\varphi^p(i,\bar{x}). Moreover, φp\varphi^p is partial recursive.

s-m-n Theorem: For any natural numers mm and nn, there exists a p.r. function snmFn+1s^m_n\in\mathcal{F}_{n+1} s.t.

φin+m(x1,,xn,y1,,ym)=φsnm(i,x1,,xn)m(y1,,ym)\varphi^{n+m}_i(x_1,\ldots,x_n,y_1,\ldots,y_m) = \varphi^{m}_{s^m_n(i,x_1,\ldots,x_n)}(y_1,\ldots,y_m)

In programming world, this is partial application, or currying.

Kleene’s Fixed Point Theorem: For any total recursive function αF1\alpha\in\mathcal{F}_1 and m>0m > 0, there exists iNi\in\mathbb{N} s.t. φim=φα(i)m\varphi^m_{i} = \varphi^m_{\alpha(i)}.

Elimination of Recursion: The set of total recursive functions is the smallest set that

  • Contains SS, C00C^0_0, PinP^n_i;
  • Contains ++, \cdot, 1=1_=, 1<1_<;
  • Is stable under composition;
  • Is stable under total μ\mu-operator.
    • Total μ\mu-operator is the unbounded μ\mu-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 SNnS\subseteq\mathbb{N}^n, then the following are equivalent:

  • SS is either empty or the range of a total recursive function f:NNnf:\mathbb{N}\to\mathbb{N}^n.
    • That is, there exists a recursive function that enumerates elements of SS, but not necessarily in order.
  • SS is either empty or the range of a p.r. function.
  • SS is a projection of some recursive set TNn+1T\subset\mathbb{N}^{n+1}.
  • SS is a projection of some p.r. set TNn+1T\subset\mathbb{N}^{n+1}.
  • SS is the domain of a partial recursive function f:NnNf: \mathbb{N}^n\to\mathbb{N}.

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 XNnX\subseteq\mathbb{N}^n is recursive if and only if both XX and NnX\mathbb{N}^n\setminus X are r.e.

the Halting Problem: The domain of φn\varphi^n 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 χ\chi is a set of one-variable partial recursive functions that is non-empty nor full. Then, the indices I={i:φi1χ}I = \{i: \varphi^1_i\in\chi\} is not recursive.

Kolmogorov complexity: Given nNn\in\mathbb{N}, let K(n)K(n) be the least iNi\in\mathbb{N} s.t. φi1(0)=n\varphi^1_i(0) = n. One can prove that there does not exist an infinite r.e. set AN2A\subseteq\mathbb{N}^2 s.t. K(n)=iK(n)=i for all (n,i)A(n,i)\in A.

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 L\mathcal{L} 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 L\mathcal{L} are p.r. sets
  • There exist p.r. functions that simulate substitution of terms and formulas.
  • The set of formal proofs Prf={(##d,#ϕ):d is a formal proof of ϕ}\mathrm{Prf}=\{(\#\#d, \#\phi): d\text{ is a formal proof of }\phi\} is a p.r. set.
  • The set of tautologies U={#ϕ: φ}U=\{\#\phi:\ \vdash\varphi\} is r.e.

Given a L\mathcal{L}-theory TT,

  • TT is recursive if the code of axioms of TT is recursive.
  • TT is recursively (or effectively) axiomatizable if there exists a recursive theory TT' that has the same theorem of TT.
  • TT is decidable if the set of codes of theorems #Thm(T)\#\mathrm{Thm}(T) of TT is recursive.
  • If TT is recursive, then the formal proofs of TT, Prf(T)\mathrm{Prf}(T), is recursive.
  • TT is effectively axiomatizable iff #Thm(T)\#\mathrm{Thm}(T) is r.e.
  • If TT is effectively axiomatizable and complete, then TT is decidable.
  • If TT is decidable, then the theory of TT plus a finite set of axioms is also decidable.

Peano Arithmetic

We work in the language of arithmetic Lar={0,S,+,,<}\mathcal{L}_{ar} = \{0,S,+,\cdot, < \}. In this language, we can express any (standard) natural number nNn\in\mathbb{N} as n\underline{n}:

  • 00\underline{0} \equiv 0;
  • n+1S(n)\underline{n+1} \equiv S(\underline{n}).

The weak Peano axioms is the finite theory PA0\mathrm{PA}_0 consisting of the following 8 axioms:

  1. 00 has no predecessor.
  • (A1) x¬Sx=0\forall x \neg Sx=0
  1. Every non-zero number has a predecessor.
  • (A2) xy(¬x=0Sy=x)\forall x\exists y(\neg x=0\to Sy=x)
  1. Two numbers with equal successors are equal.
  • (A3) xy(Sx=Syx=y)\forall x\forall y(Sx=Sy\to x=y)
  1. 00 is the identity of addition.
  • (A4) x x+0=0\forall x\ x+0 = 0
  1. Successor commutes with addition.
  • (A5) xy x+Sy=S(x+y)\forall x\forall y\ x+Sy =S(x+y)
  1. 00 is the zero of multiplication.
  • (A6) x x0=0\forall x\ x\cdot 0 = 0
  1. Multiplication is distributive over successor.
  • (A7) xy xSy=xy+x\forall x\forall y\ x\cdot Sy =x\cdot y + x
  1. "Less" means "subtractable".
  • (A8) xy(x<yx=y(z x+z=y))\forall x\forall y(x< y\leftrightarrow \neq x=y\wedge (\exists z\ x+z=y))

The Peano axioms is the infinite theory PA, consisting of PA0\mathrm{PA}_0 and the axiom (schema) of induction.

  • There exists a model of PA0\mathrm{PA}_0 that both addition and multiplication are neither commutative nor associative, and << is not a total order.
  • The standard natural number N\mathbb{N} is isomorphic to an initial segment of any PA0\mathrm{PA}_0 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 ϕ\phi can be classified into the following hierarchy:

  • ϕ\phi is Σ0=Π0=Δ0\Sigma_0 = \Pi_0 = \Delta_0 if is is equivalent to a formula with only bounded quantifiers;
  • ϕ\phi is Σn+1\Sigma_{n+1}, if it is equivalent to a formula in the form x1xmψ\exists x_1\cdots\exists x_m\psi, where ψ\psi is Πn\Pi_{n};
  • ϕ\phi is Πn+1\Pi_{n+1}, if it is equivalent to a formula in the form x1xmψ\forall x_1\cdots\forall x_m\psi, where ψ\psi is Σn\Sigma_{n};
  • ϕ\phi is Δn\Delta_{n} if it is both Σn\Sigma_{n} and Πn\Pi_{n}.
  • Sometimes people write Σn0\Sigma^0_n, Πn0\Pi^0_n and Δn0\Delta^0_n. The superscript 00 means counting number quantifiers instead of function quantifiers.

Any Σ1\Sigma_1 sentence satisfied in N\mathbb{N} is a theorem of PA0\mathrm{PA}_0.

Nϕ[m1,,mn]PA0ϕ(m1,,mn)\mathbb{N}\models\phi[m_1,\ldots, m_n] \Rightarrow \mathrm{PA}_0\models\phi(\underline{m_1},\ldots, \underline{m_n})

Representability Theorem: Every total recursive function is represented by a Σ1\Sigma_1 formula. A set is r.e. iff there is a Σ1\Sigma_1 formula defining it in N\mathbb{N}. Here, ϕ\phi "represent" ff means:

PA0y[ϕ(n1,,np,y)y=f(n1,,np)]\mathrm{PA}_0\models \forall y\left[ \phi(\underline{n_1},\ldots,\underline{n_p},y) \leftrightarrow y = \underline{f(n_1,\ldots, n_p)} \right]

Overspill: Let M\mathfrak{M} be a non-standard model of PA and ϕ(x)\phi(x) a formula. If for all nNn\in\mathbb{N}, Mϕ(n)\mathfrak{M}\models\phi(\underline{n}), then there exists cMc\in M non-standard s.t. Mϕ(c)\mathfrak{M}\models\phi(c).

Pigeonhole Principle: For any PA model M\mathfrak{M}, Lar(M)\mathcal{L}_{ar}(M)-formula θ(v,z)\theta(v,z) and aMa\in M:

M[x(z>x)(v<a)θ(v,z)](v<a)x(z>x)θ(v,z)\mathfrak{M}\models \left[ \forall x(\exists z>x)(\exists v< a)\theta(v,z) \right] \to (\exists v< a)\forall x(\exists z>x)\theta(v,z)

In other words, if a predicate maps infinite many numbers (z>xz> x) into a finite number of elements (v<av< a), then there exists a fixed number (vv) 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 ϕ(v)\phi(v), there exists a sentence Δϕ\Delta_{\phi} s.t. ϕ(#Δϕ)\phi(\underline{\#\Delta_{\phi}}) is equivalent to ¬Δϕ\neg\Delta_{\phi} in PA0\mathrm{PA}_0.

Fixed Point Theorem: For all ϕ(v)\phi(v), there exists a sentence ψ\psi s.t.

PA0ϕ(#ψ)ψ\mathrm{PA}_0\vdash \phi(\underline{\#\psi})\leftrightarrow\psi

Proof: Take ψ:Δ¬ϕ\psi :\equiv \Delta_{\neg\phi}.

Tarski’s Theorem on the Non-definability of Truth: In any model M\mathfrak{M} of PA0\mathrm{PA}_0, there does not exist a formula S(v)S(v) s.t. Mϕ\mathfrak{M}\models\phi iff MS(#ϕ)\mathfrak{M}\models S(\underline{\#\phi}).

Corollary: The theorems of N\mathbb{N} are undecidable.

Church's Theorem: Any consistent theory containing PA0\mathrm{PA}_0 is undecidable.

Corollary 1: The tautologies of the finite language Lar\mathcal{L}_{ar} 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 PA0\mathrm{PA}_0 is incomplete.

Rosser's Variant: Rosser writes down an independent sentence that witnesses this theorem. Let TPA0T\supseteq \mathrm{PA}_0 be consistent and recursive. Let PT(x,y)P_T(x,y) represents the set of formal proofs of TT, i.e. yy proves xx. Let ν(x,y)\nu(x, y) represents the negation of formula, i.e. yy is ¬x\neg x. Set:

PTR(x,y):PT(x,y)¬(zy)u(PT(u,z)ν(x,u))P^R_T(x,y) :\equiv P_T(x,y)\wedge\neg(\exists z\leq y)\exists u(P_T(u,z)\wedge \nu(x,u))

That means,

  • for standard numbers xx and yy, yy proves xx;
  • for non-standard numbers yy, there does not exist a proof zz for the negation of xx.

Then, ΔTR:ΔyPTR(x,y)\Delta_T^R :\equiv \Delta_{\exists y P^R_T(x,y)} is independent.

Remark: If we directly use PTP^T as ΔT:ΔyPT(x,y)\Delta_T :\equiv \Delta_{\exists y P_T(x,y)}, then TT cannot prove ΔT\Delta_T, but TT may prove ¬ΔT\neg\Delta_T. PT(#ΔT,y)P_T(\#\Delta_T, y) does not imply TΔTT\vdash \Delta_T when yy 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 Σ1\Sigma_1 formulas.

Provably Total Σ1\Sigma_1 Functions: Suppose χf\chi_f represents ff. If PA proves that for any (even non-standard) numbers x1,,xnx_1,\ldots, x_n, there is exactly one yy that satisfies χf\chi_f, then ff is provably total Σ1\Sigma_1. Formally,

PAx1,,xn!y χf(x1,,xn,y)\text{PA}\vdash \forall x_1,\ldots,x_n\exists !y\ \chi_f(x_1,\ldots, x_n,y)
  • Every p.r. function is provably total Σ1\Sigma_1
  • Not every recursive function is provably total Σ1\Sigma_1 (though representable).
    • There is a universal provably total Σ1\Sigma_1 function gF3g\in\mathcal{F}_3, in the sense that: for every provably total Σ1\Sigma_1 function ff there exists a,bNa,b\in\mathbb{N} s.t. f=λn.g(a,b,n)f = \lambda n.g(a,b,n).

Definability of Satisfiability for Σ1\Sigma_1 Formulas: There exists a Σ1\Sigma_1-formula Sat(v)\mathrm{Sat}(v) s.t. for all Σ1\Sigma_1-sentence ϕ\phi,

PAϕSat(#ϕ)\mathrm{PA}\vdash \phi\leftrightarrow \mathrm{Sat}(\underline{\#\phi})

The proof uses certificate method.

Definition of Provability: For a recursive theory TT, there exists an operator T\Box_T on sentences s.t.

  • If ϕ\phi is a Σ1\Sigma_1-sentence, PAϕTϕ\text{PA}\vdash \phi\to\Box_T\phi;
  • For any sentence ψ\psi, NTψ    Tψ\mathbb{N}\models \Box_T\psi \iff T\vdash \psi.

Löb's Axioms: for any sentence ϕ,ψ\phi,\psi,

  1. (Necessitation Rule, N) TϕTTϕT\vdash \phi \Rightarrow T\vdash \Box_T\phi;
  2. (Distribution Axiom, K) T[TϕT(ϕψ)]TψT\vdash [\Box_T\phi\wedge \Box_T(\phi\to\psi)]\to \Box_T\psi;
  3. (4) TTϕTTϕT\vdash \Box_T\phi\to\Box_T\Box_T\phi.

Corollaries:

  • If TϕψT\vdash \phi\to\psi, then TTϕTψT\vdash \Box_T\phi\to\Box_T\psi;
  • (GL) TT(Tϕϕ)TϕT\vdash \Box_T(\Box_T\phi\to\phi)\to\Box_T\phi;
  • If TTϕϕT\vdash \Box_T\phi\to\phi, then TTϕT\vdash \Box_T\phi;
  • If T¬TϕT\vdash \neg\Box_T\phi, then TTϕT\vdash \Box_T\phi.

See also: Modal Logic, Provability Logic, Kripke Semantics.

Gödel’s Second Incompleteness Theorem: Let TT be a computable theory. Then, it is impossible to prove Tϕ\Box_T\phi for any ϕ\phi in TT. More specifically, let ConT\text{Con}_T denote the consistency of TT: ConT:¬T(0=1)\text{Con}_T :\equiv \neg\Box_T(0=1). Then, TT cannot prove ConT\text{Con}_T.

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 N\mathbb{N} 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: Lset={}\mathcal{L}_{set} = \{\in \}. Other symbols can be developed as abbreviations of Lset\mathcal{L}_{set}-formulas.

The Axiom Schema of Comprehension: The only axiom for naive set theory, is that every logic formula ϕ\phi has a set corresponding to it:

wˉyz (zyϕ(z,wˉ))\forall\bar{w}\exists y\forall z\ (z\in y\leftrightarrow \phi(z, \bar{w}))

Cantor's Diagonal Argument: For all set XX, there is no surjection f:XP(X)f: X\to\mathcal{P}(X).

  • Cantor's paradox: Let V={x:x}V = \{x: \forall x\}. Then, P(V)\mathcal{P}(V) is part of VV.

Russel's Paradox: Let D={x:xx}D = \{x: x\notin x\}. Then, DD 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.
    • xy[x=yz(zx=zy)]\forall x\forall y[x=y \leftrightarrow \forall z(z\in x = z\in y)].
  • The axiom of Foundation: Every non-empty set contains a \in-minimal element.
    • Let xx\neq \varnothing abbreviate y(xx)\exists y(x\in x).
    • x[xyxzx(zy)]\forall x[x\neq\varnothing \to \exists y\in x\forall z\in x(z\notin y)]
  • The axiom of Pairing: Given two sets, there is a set containing exactly them.
    • xyw[xwywz(zwz=xz=y)]\forall x\forall y\exists w[x\in w\wedge y\in w\wedge \forall z(z\in w\to z=x\vee z=y)].
    • We can let {x,y}\{x,y\} denote this set; use {x}\{x\} denote {x,x}\{x,x\}.
    • We can define ordered pair (x,y)={x,{x,y}}(x,y) = \{x, \{x, y\}\}.
  • The axiom of Union: Given any set of sets xx, there is set containing exactly all the element of these sets.
    • Let y=xy=\bigcup x denote z[zywx(yw)]\forall z[z\in y\leftrightarrow \exists w\in x(y\in w)].
    • xy[y=x]\forall x\exists y[y = \bigcup x].
  • The axiom of Nullset: There is a set with no elements.
    • x[x=]\exists x[x = \varnothing]
  • The axiom of Infinity: There exists an inductive set.
    • x[xy(yxy{y}x)]\exists x[\varnothing\in x\wedge\forall y(y\in x\to y\cup\{y\}\in x) ].
  • The axiom of Powerset: For every set x, there is a set containing all the subsets of this set.
    • Let yxy\subseteq x abbreviate z(zxzy)\forall z(z\in x\to z\in y).
    • Let y=P(x)y=\mathcal{P}(x) abbreviate z(zyzx)\forall z(z\in y\leftrightarrow z\subseteq x).
    • xy[y=P(x)]\forall x\exists y[ y=\mathcal{P}(x)]
  • The axiom schema of Separation: Every definable subset of a set exists.
    • x,wˉyz[zyzxϕ(z,wˉ)]\forall x,\bar{w}\exists y\forall z[z\in y\leftrightarrow z\in x\wedge\phi(z, \bar{w})]
    • The collection of a formula is a class Y={z:ϕ(z,wˉ)}Y = \{z: \phi(z,\bar{w})\}.
    • Let zYz\in Y abbreviate ϕ(z,wˉ)\phi(z,\bar{w}).
    • Note that a proper class YY "does not exist": ¬yx[xyxY]\neg \exists y\forall x[x\in y\leftrightarrow x\in Y].
    • We can define cartesian products, relations and functions with this axiom schema.
  • The axiom schema of Collection: If xx is a set, and ϕ\phi defines a class from each element of xx, then there is a set which meets all these classes.
    • x,vˉyzx[wϕ(w,z,vˉ)wyϕ(w,z,vˉ)]\forall x,\bar{v}\exists y\forall z\in x[ \exists w\phi(w,z,\bar{v})\to \exists w\in y\phi(w,z,\bar{v})].
  • The axiom schema of Replacement: The image of a set under a definable class function is a set.
    • x,wˉ[((ax)(!y)ϕ(a,y,wˉ))zy(yz(ax)ϕ(a,y,wˉ))]\forall x,\bar{w}[((\forall a\in x)(\exists! y)\phi(a,y,\bar{w}))\to \exists z \forall y(y\in z\leftrightarrow (\exists a\in x)\phi(a,y,\bar{w})) ].
    • 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.

Wellordering:

  • 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.

Ordinals:

  • A set xx is transitive if forall axa\in x, bab\in a implies bxb\in x.
    • Note: \in is not necessarily a transitive relation on xx. For exmaple, {,{},{{}}}\{\varnothing, \{\varnothing\}, \{\{\varnothing\}\}\}.
  • An ordinal is a transitive set α\alpha s.t. \in on α\alpha is a wellordering.
  • Let ORD\text{ORD} denote the class of ordinals.
  • Define α<β\alpha < \beta iff αβ\alpha \in \beta. Then, << is a wellordering on ORD\text{ORD}.
  • Any wellordered set PP is isomorphic to a unique ordinal, called the order type of PP.
  • Let α+1=α{α}\alpha+1 = \alpha\cup\{\alpha\}.
    • If α=β+1\alpha = \beta+1, α\alpha is a successor ordinal;
    • Otherwise, α\alpha is a limit ordinal.
  • Let ω\omega be the intersection of all inductive sets. Then, ω\omega is the least non-zero limit ordinal. The elements of ω\omega are natural numbers. Let 0:=0 := \varnothing.

Transfinite Induction:

  • A class CC is equal to ORD if it satisfies the following:
    • 0C0\in C;
    • For all α\alpha, αCα+1C\alpha\in C\to \alpha+1\to C;
    • If λ\lambda is a (non-zero) limit ordinal, (α<λ)αCλC(\forall\alpha<\lambda) \alpha\in C\to\lambda\in C.
  • Let GG be a class function. Then, there is a unique class function FF s.t. for all αORD\alpha\in\text{ORD}, F(α)=G(Fα)F(\alpha) = G(F\restriction\alpha).
    • 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 α\alpha, there uniquely exist natural numbers n,k0,,kn1n,k_0,\ldots, k_{n-1} and ordinals αβ0>>βn1\alpha \geq \beta_0 > \cdots > \beta_{n-1} s.t.

α=ωβ0k0++ωβn1kn1\alpha = \omega^{\beta_0}\cdot k_0 + \cdots + \omega^{\beta_{n-1}}\cdot k_{n-1}

Note: It's possible that α=ωα\alpha = \omega^{\alpha}.

The cumulative hierarchy:

  • For each ordinal α\alpha, define set VαV_{\alpha} as:
    • V0=V_0 = \varnothing;
    • Vα+1=P(Vα)V_{\alpha+1} = \mathcal{P}(V_{\alpha}), for any α\alpha;
    • Vλ=β<λVβV_{\lambda} = \bigcup_{\beta<\lambda}V_{\beta}, for λ\lambda a limit ordinal.
  • Let the class VV be the union of all VαV_{\alpha}.
  • For xVx\in V, define its rank to be the least ordinal α\alpha that xVαx\in V_{\alpha}.
    • One can verify that rank(x)=sup{rank(y)+1:yx}\mathrm{rank}(x) = \sup\{\mathrm{rank}(y)+1: y\in x\}
  • The transitive closure of xx is defined as the smallest transtive set containing xx,
    • For any xx, let x0=xx_0 = x and xn+1=xnxnx_{n+1} = x_n\cup\bigcup x_n. Then, the transitive closure is TC(x)=n<ωxn\mathrm{TC}(x)=\bigcup_{n< \omega} x_n.
  • Assume ZF\text{ZF}^- (ZF minus Foundation), then the axiom of foundation is equivalent to x(xV)\forall x(x\in V).
    • Note: xVx\in V is actually the shorthand for α[αORDxVα]\exists \alpha[\alpha\in\mathrm{ORD} \wedge x\in V_{\alpha}].

Mostowski Collapse: If a relation RR on a class XX is wellfounded, setlike and extensional, then there exists a unique transitive class YY and a unique isomorphism (X,R)(Y,)(X,R)\cong (Y,\in).

  • wellfounded: For every non-empty subset of XX, there exists an RR-minimal element.
  • setlike: R1(x)R^{-1}(x) is always a set;
  • extensional: R1(x)=R1(y)R^{-1}(x) = R^{-1}(y) iff x=yx=y.

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 AC+\mathrm{AC}^+: Every set can be well-ordered.
    • Note: Whether there exists a computable well-ordering of R\mathbb{R} is independent of ZFC.
  • The cardinalities of any pair of sets are comparable.
  • For all infinite sets X,YX,Y, X+Y=X×Y\|X\|+\|Y\| = \|X\|\times \|Y\|.

AC also implies the partition principle: If there is a surjection from XX to YY, then there is an injection from YY to XX. But whether this principle implies AC is still open.

Cantor-Shröder-Bernstein theorem:

  • Define X=Y\|X\| = \|Y\| if there is a bijection.
  • Define XY\|X\| \leq \|Y\| if there is an injection from XX to YY.
  • (ZF) If XY\|X\| \leq \|Y\| and YX\|Y\| \leq \|X\|, then X=Y\|X\| = \|Y\|.

Cardinal:

  • An ordinal α\alpha is a cardinal if for all β<α\beta<\alpha, β<α\|\beta\| < \|\alpha\|.
  • Let ωα\omega_{\alpha} denote the α\alpha-th infinite cardinal; let α\aleph_{\alpha} denote its cardinality.
  • Let κ+\kappa^+ denote the least cardinal of cardinality greater than κ\kappa.
    • Similarly, κ+\kappa^+ is a successor cardinal; A non-zero cardinal not in this form is a limit cardinals.
  • α+β=αβ=max{α,β}\aleph_{\alpha} + \aleph_{\beta} = \aleph_{\alpha} \cdot \aleph_{\beta} = \max\{\aleph_{\alpha}, \aleph_{\beta}\}.

Hartogs's theorem:

  • (ZF) For any set XX, there is an ordinal that cannot be injected into XX.
  • This ordinal is called Hartog’s number h(X)h(X).

Cofinality:

  • Given an ordinal α\alpha and CαC\subseteq\alpha, if there does not exist a βα\beta\in\alpha that is strict greater than all elements of CC, then CC is cofinal in α\alpha.
    • Since no one cares successor ordinals, an equivalent definition is supC=α\sup C = \alpha.
  • The cofinality cf(α)\mathrm{cf}(\alpha) is the minimum of order-types of the cofinal subsets of α\alpha.
  • For all α\alpha, cf(cf(α))=cf(α)\mathrm{cf}(\mathrm{cf}(\alpha)) = \mathrm{cf}(\alpha).
  • For all α\alpha, cf(α)\mathrm{cf}(\alpha) is a cardinal not greater than α\alpha.

Regular cardinals:

  • A cardinal κ\kappa is regular if cf(κ)=κ\mathrm{cf}(\kappa)=\kappa; otherwise, singular.
  • (ZFC) Every successor cardinal is regular.
  • κ<κcf(κ)\kappa < \kappa^{\mathrm{cf}(\kappa)}.
  • (ZFC) cf(2κ)>κ\mathrm{cf}(2^\kappa) > \kappa.
  • The gimel function of an infinite cardinal κ\kappa is: (κ)=κcf(κ)\gimel(\kappa) = \kappa^{\mathrm{cf}(\kappa)}.
    • Note: If κ\kappa is regular, (κ)=κκ=2κ\gimel(\kappa) = \kappa^\kappa = 2^\kappa.

König's theorem: Suppose κi<λi\kappa_i < \lambda_i for all iIi\in I. Then,

iIκi<iIλi\sum_{i\in I} \kappa_i < \prod_{i\in I} \lambda_i

Cardinal powers: Suppose κ,λ\kappa, \lambda are infinite cardinals, then κλ\kappa^{\lambda} can be one of the following:

  • If κ<λ\kappa < \lambda, then κλ=2λ\kappa^{\lambda} = 2^{\lambda}.
  • If κ>λ\kappa > \lambda and (μ<κ)μλκ(\exists \mu<\kappa)\mu^{\lambda} \geq \kappa, then κλ=μλ\kappa^{\lambda} = {\mu}^{\lambda}.
  • If κ>λ\kappa > \lambda and (μ<κ)μλ<κ(\forall \mu<\kappa)\mu^{\lambda} < \kappa,
    • if cf(κ)>λ\mathrm{cf}(\kappa) > \lambda, then κλ=κ\kappa^{\lambda} = \kappa.
    • if cf(κ)λ\mathrm{cf}(\kappa) \leq \lambda, then κλ=κcf(κ)\kappa^{\lambda} = \kappa^{\mathrm{cf}(\kappa)}.

Generalized continuum hypothesis (GCH): GCH states that 2κ=κ+2^{\kappa} = \kappa^+ for all infinite κ\kappa.

  • GCH implies that for κ,λ\kappa, \lambda infinite cardinals
    • If λ<cf(κ)\lambda < \mathrm{cf}(\kappa), κλ=κ\kappa^{\lambda} = \kappa.
    • If cf(κ)λ<κ\mathrm{cf}(\kappa)\leq \lambda <\kappa, κλ=κ+\kappa^{\lambda} = \kappa^+.
    • If κλ\kappa \leq \lambda, κλ=λ+\kappa^{\lambda} = \lambda^+.

Cardinal exponentiation: Define κ<λ=μ<λκμ\kappa^{<\lambda} = \bigcup_{\mu<\lambda}\kappa^{\mu}. Suppose κ\kappa is an infinite cardinal.

  • If κ\kappa is regular, then 2κ=(κ)2^{\kappa} = \gimel(\kappa).
  • If κ\kappa is singular and 2λ2^{\lambda} is eventually constant as λκ\lambda\to\kappa (so 2<κ2^{<\kappa} is this constant value), then 2κ=2<κ2^{\kappa} = 2^{<\kappa}.
  • If κ\kappa is singular and 2λ2^{\lambda} is not eventually constant as λκ\lambda\to\kappa, then 2κ=(2<κ)2^{\kappa} = \gimel(2^{<\kappa}).

Singular cardinals hypothesis (SCH): If κ\kappa singular and 2cf(κ)<κ2^{\mathrm{cf}(\kappa)} < \kappa, then κcf(κ)=κ+\kappa^{\mathrm{cf}(\kappa)} = \kappa^+.

Inaccessible cardinals:

  • A (weak) limit cardinal is a cardinal that is neither a successor cardinal nor zero.
  • A strong limit cardinal κ\kappa is not reachable by power: for all λ<κ\lambda<\kappa, 2λ<κ2^{\lambda} < \kappa.
  • A regular limit cardinal is weakly inaccessible.
    • If κ\kappa is an uncountable weakly inaccessible cardinal, then LκL_{\kappa} is a model of ZFC.
  • An uncountable regular cardinal κ\kappa is strongly inaccessible if it is a strong limit: for all λ<κ\lambda<\kappa, 2λ<κ2^{\lambda} < \kappa.
    • Then, VκV_{\kappa} is a model of ZFC.
  • ZFC cannot prove the existence of any uncountable inaccessible cardinal.

Infinitary Combinatorics

Filters:

  • A filter FF on a set XX is a collection of subsets of XX s.t.
    • FF is upward closed under \subseteq: (AFBXAB)BF(A\in F\wedge B\subseteq X\wedge A\subseteq B)\to B\in F.
    • FF is non-empty: XFX\in F.
    • FF is closed under finite intersections: (AFBF)ABF(A\in F\wedge B\in F)\to A\cap B\in F.
  • FF is non-trivial if F\varnothing\notin F.
  • Dually, we can define ideal II as a collection of subsets s.t. II is downward closed, non-empty and closed under finite union.
  • Given a filter FF, its dual ideal is {XA:AF}\{X\setminus A: A\in F\}.
  • Given an ideal II and its dual filter FF, a set AXA\subseteq X is II-positive/FF-positive if AIA\notin I.
    • A filter is a collection of "large" sets; an ideal is "small"; II-positive sets are "not small".
  • For SP(X)S\subseteq\mathcal{P}(X), then F={AX:(BS)(BA)}F = \{A\subseteq X: (\exists B\in S)(B\subseteq A)\} is the filter generated by SS.
  • A filter is κ\kappa-complete if it is closed under intersections of size less than κ\kappa.
  • A ultrafilter is a filter s.t. for all AXA\subseteq X, exactly one of AFA\in F or (XA)F(X\setminus A)\in F.
    • Ultrafilters are exactly the filters maximal w.r.t. \subseteq.
  • (The ultrafilter lemma) (ZFC) every filter can be exteneded into an ultrafilter.
  • An ultrafilter is principal if there is AXA\subseteq X s.t. BFB\in F iff ABA\subseteq B.

Ultralimits:

  • Suppose FF is a filter on ω\omega, an:nω\langle a_n: n\in\omega \rangle is a sequence of real numbers. Then limFan=x\lim_F a_n = x iff for all ε>0\varepsilon>0, {n:anx<ε}F\{n: \|a_n - x\| < \varepsilon \}\in F.
  • This limit satisfies all the usual limit laws.
  • If UU is a non-principal ultrafilter on ω\omega, then any bounded sequence has an ultralimit limUan\lim_U a_n.

Measurable cardinal:

  • A cardinal κ\kappa is measurable if there is a kappakappa-complete ultrafilter on κ\kappa.
  • A cardinal κ\kappa is called real-valued measurable if there is a κ\kappa-additive probability measure on the power set of κ\kappa that vanishes on singletons.
  • An atomless measurement μ\mu on κ\kappa is that, for every AκA\subseteq\kappa with μ(A)>0\mu(A)> 0, there is BAB\subseteq A with 0<μ(B)<μ(A)0 < \mu(B) < \mu(A).
  • (Ulam) There are two cases for a real-valued measurable κ\kappa:
    1. κ20\kappa \leq 2^{\aleph_0}, there is an atomless measurement on κ\kappa. There is also a measure on the full powerset P([0,1])\mathcal{P}([0, 1]) extending Lebesgue measure.
    2. κ\kappa is measurable. κ>20\kappa > 2^{\aleph_0} (actually a strong limit). Every measurement on κ\kappa has an atom which yields a κ\kappa-additive κ\kappa-complete ultrafilter.

Ultraproducts: Suppose Mi:iI\langle M_i: i\in I \rangle are L\mathcal{L} structures, and UU is an ultrafilter on II. Let XX be the set of II-sequences that pick one element from each structure:

X={f:dom(f)=I(iI)(f(i)Mi)}X = \{ f: \mathrm{dom}(f)=I\wedge (\forall i\in I)(f(i) \in M_i) \}

Let \sim be the equivalence relation on XX where fgf\sim g iff they coincide at the ultrafilter {i:f(i)=g(i)}U\{i: f(i)=g(i)\}\in U. Now, let the ultraproduct UMi\prod_U M_i be the structure on universe X/X/\sim:

  • For each constant cc of L\mathcal{L}, let cUMi=[icMi]c^{\prod_U M_i} = [i\mapsto c^{M_i} ]_{\sim};
  • For each relation RR of L\mathcal{L}, let RUMi([f1],,[fn])R^{\prod_U M_i}([f_1 ]_{\sim},\ldots,[f_n ]_{\sim}) be true iff {i:RMi(f1(i),,fn(i))}U\{i: R^{M_i}(f_1(i),\ldots,f_n(i))\}\in U;
  • For each function gg of L\mathcal{L}, let gUMi([f1],,[fn])g^{\prod_U M_i}([f_1 ]_{\sim},\ldots,[f_n ]_{\sim}) be [igMi(f1(i),,fn(i))][i\mapsto g^{M_i}(f_1(i),\ldots,f_n(i)) ]_{\sim}.

If Mi=MM_i = M for all iIi\in I, then UM\prod_ U M is called the ultrapower of MM by UU.

Łoś's Theorem: For any L\mathcal{L}-formula φ\varphi and [fi]X/[f_i ]_{\sim}\in X/\sim, UMiφ([f1],,[fn])\prod_ U M_i\models \varphi([f_1 ]_{\sim},\ldots, [f_n ]_{\sim}) iff {i:Miφ(f1(i),,fn(i))}U\{i: M_i\models \varphi(f_1(i),\ldots,f_n(i)) \}\in U. In particular, the ultraproduct models a sentence iff there is a "large" number of models modeling it.

Keisler-Shelah isomorphism theorem: Two structures MM and NN are elementarily equivalent MNM\equiv N iff there is an ultrafilter UU s.t. the two ultraproducts are isomorphic limUMlimUN\lim_U M \cong \lim_U N.

Asympototic Cone:

  • Suppose Xn,dn:nω\langle X_n, d_n: n\in\omega \rangle is a sequence of metric spaces and xnXnx_n\in X_n are base points. Let XX be the set of sequences anXn:nω\langle a_n\in X_n: n\in\omega\rangle where the sequence dn(an,xn)d_n(a_n, x_n) is bounded. Let \sim be the equivalence relation that anbn\langle a_n\rangle \sim \langle b_n\rangle if limUdn(an,bn)=0\lim_U d_n(a_n, b_n) = 0. Let dd be the metric on X/X/\sim where d(an,bn)=limUdn(an,bn)d(\langle a_n\rangle, \langle b_n\rangle) = \lim_U d_n(a_n, b_n). We define ultraproduct U(Xn,dn,xn)\prod_U(X_n, d_n, x_n) to be (X/,d)(X/\sim, d).
  • Suppose (X,d)(X, d) is a given metric space with a base point pXp\in X. The asymptotic cone of (X,d)(X, d) is U(X,d/n)\prod_U(X, d/n).
  • The asymptotic cone is a way of viewing (X,d)(X, d) from “infinitely far away”.
  • The asymptotic cone of Z\mathbb{Z} with usual metric is isomorphic to R\mathbb{R}.

Club:

  • Suppose λ\lambda a limit ordinal (generally a regular uncountable cardinal) and CλC\subseteq \lambda.
    • CC is closed if it contains all its limit points less than λ\lambda. Formally, for all ν<λ\nu<\lambda, CνC\cap \nu being cofinal in ν\nu implies νC\nu\in C.
    • CC is unbounded if for all α<λ\alpha<\lambda, there exists βC\beta\in C s.t. β≰α\beta\not\leq \alpha.
    • A closed unbounded subset is called a club set.
  • Suppose λ\lambda a limit ordinal with cf(λ)>ω\mathrm{cf}(\lambda)>\omega. Then, the intersection of finitely many clubs is a club.
  • Suppose λ\lambda a cardinal with cf(λ)>ω\mathrm{cf}(\lambda)>\omega. Then, for all β<cf(λ)\beta< \mathrm{cf}(\lambda), the intersection of β\beta many clubs α<βCα\cap_{\alpha< \beta}C_{\alpha} is a club.

Club filter: Suppose κ\kappa is a regular uncountable cardinal.

  • The filter generated by the club sets on κ\kappa is called the club filter on κ\kappa.
  • The club filter is κ\kappa-complete.
  • A subset of κ\kappa 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 Xα:α<κ\langle X_{\alpha}: \alpha<\kappa \rangle be a sequence of κ\kappa many subsets of κ\kappa. Their diagonal intersection is defined to be

α<κXα={β<κ:βα<βXα}=α<κ(Xα{β:βα})\bigtriangleup_{\alpha< \kappa} X_{\alpha} = \left\{ \beta< \kappa: \beta\in\bigcap_{\alpha< \beta} X_{\alpha} \right\} = \bigcap_{\alpha < \kappa}\left( X_{\alpha}\cup\{\beta: \beta\leq\alpha\} \right)
  • The diagonal intersection of κ\kappa 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 κ\kappa-complete filter on a regular uncountable cardinal κ\kappa includes every club of κ\kappa.

Properties of stationary sets:

  • Given a club CC and stationary set SS, CSC\cap S is stationary.
  • A stationary set is unbounded.
  • If SS is stationary, then {λS:λ is a limit ordinal}\{\lambda\in S: \lambda\text{ is a limit ordinal}\} is also stationary.
  • If we partition a stationary set SκS\subseteq\kappa into λ<κ\lambda<\kappa many sets, then one of them will be stationary.

Fodor's lemma:

  • An ordinal function ff on a set SS is regressive if f(α)<αf(\alpha) < \alpha for every αS\alpha\in S, α>0\alpha > 0.
  • If ff is a regressive function on a stationary set SS of κ\kappa, then there is a stationary subset that fixed ff. Formally, there exists γ<κ\gamma < \kappa and a stationary set TST\subseteq S s.t. f(α)=γf(\alpha) = \gamma for all αT\alpha\in T.
  • 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 ω\omega stations there could be arbitrarily many people on the train. Fodor's lemma shows that after ω1\omega_1 stations, there must be 0 people on it.

The ∆-system lemma:

  • Suppose XX is a collection of sets. If for all distinct A,BXA,B\in X, AB=rA\cap B = r, we call XX a Δ\Delta-system with root rr.
  • Suppose XX is an uncountable set of finite sets. Then there are an uncountable subset XXX'\subseteq X and a finite set rr s.t. XX' is a Δ\Delta-system with root rr.
  • Suppose κ>λ\kappa > \lambda are infinite regular cardinals s.t. for all δ<κ\delta<\kappa, δ<λ<κ\delta^{< \lambda} < \kappa. Let XX be a collection of κ\kappa many sets of cardinality less than λ\lambda. Then, there is a subset XX' of size κ\kappa which is a Δ\Delta-system.

Silver’s Theorem:

  • If κ\kappa is a singular cardinal of uncountable cofinality and 2λ=λ+2^{\lambda} = \lambda^+ for a stationary set of λ<κ\lambda < \kappa, then 2κ=κ+2^{\kappa} = \kappa^{+}.
  • If SCH holds for all singular cardinals of cofinality ω\omega, then it holds for all singular cardinals.

Infinite trees:

  • A tree TT is a κ\kappa-tree if its height is κ\kappa and every level has size less than κ\kappa.
  • Kőnig's lemma: An ω\omega-tree has an infinite branch.
  • Aronszajn tree: There is a ω1\omega_1-tree with no branches of order type ω1\omega_1.
  • Suslin line
    • A linear order << on XX is dense if for all a<ba < b there exists cXc\in X s.t. a<c<ba < c < b.
    • A subset AXA\subseteq X is dense in XX if for all a<ba < b there exists cAc\in A s.t. a<c<ba < c < b.
    • 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.
    • R\mathbb{R} is isomorphic to any complete dense linear order without endpoints that has a countable dense subset.
    • A linear order on XX 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 R\mathbb{R}).
  • Suslin tree
    • A Suslin tree is an ω1\omega_1-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.

Diamond:

  • A \diamondsuit-sequence is a sequence Aα:α<ω1\langle A_{\alpha}:\alpha<\omega_1\rangle where AααA_{\alpha}\subseteq\alpha s.t. for all Xω1X\subseteq\omega_1, {α:Xα=Aα}\{\alpha: X\cap\alpha = A_{\alpha}\} is stationary.
  • \diamondsuit is the statement that there exists a \diamondsuit-sequence.
  • \diamondsuit implies CH.
  • \diamondsuit implies there is a Suslin tree.
  • A +\diamondsuit^+-sequence is a sequence Aα:α<ω1\langle \mathcal{A}_{\alpha}:\alpha<\omega_1\rangle where AαP(α)\mathcal{A}_{\alpha}\subseteq\mathcal{P}(\alpha) s.t. for all Xω1X\subseteq\omega_1, there exists a club Cω1C\subseteq\omega_1 s.t. for all αC\alpha\in C, both XαX\cap \alpha and CαC\cap\alpha are in Aα\mathcal{A}_{\alpha}.
  • A \diamondsuit^--sequence is a sequence Aα:α<ω1\langle \mathcal{A}_{\alpha}:\alpha<\omega_1\rangle where AαP(α)\mathcal{A}_{\alpha}\subseteq\mathcal{P}(\alpha) s.t. for all Xω1X\subseteq\omega_1, {α:XαAα}\{\alpha: X\cap\alpha \in \mathcal{A}_{\alpha}\} is stationary.
  • +\diamondsuit^+ is the statement that there exists a +\diamondsuit^+-sequence; \diamondsuit^- is the statement that there exists a \diamondsuit^--sequence.
  • +\diamondsuit^+ implies \diamondsuit; \diamondsuit^- is equivalent to \diamondsuit.

Constructible Hierarchy

Skolem's paradox:

  • 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 A,BA, B, it is possible that in VV there exists a bijection from AA to BB, but an inner model lacks this bijection.
  • Cardinality is not absolute.

Transitive model:

  • (Theorem) By compactness, there exists a model (M,E)(M, E) of ZFC s.t. EE is not well-founded.
    • Such models are not necessarily recursive.
  • (Theorem) By Mostowski collapse, every well-founded model (M,E)(M, E) is isomorphic to some (N,N)(N, \in\restriction N).
  • A model (N,N)(N, \in\restriction N) when NN 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, \models is a well-defined relation only if NN is a set.
  • For any sentence ϕ\phi, let ϕN\phi^N denote the sentence where all quantifiers x\forall x and x\exists x are replaced with xN\forall x\in N and xN\exists x\in N.
    • For any transitive set model, NϕN\models \phi iff ϕN\phi^N is true.
    • When NN is a proper class, we use NϕN\models \phi to abbreviate ϕN\phi^N.

The Lévy hierarchy: Similar to arithmetic hierarchy, every formula in set theory is categorized into Σn\Sigma_n, Πn\Pi_n and Δn\Delta_n.

Absoluteness:

  • If ϕ(v1,,vn)\phi(v_1,\ldots, v_n) is a Δ0\Delta_0 formula and MM is a transitive class. Then for all x1,,xnMx_1,\ldots,x_n\in M, we have ϕ(x1,,xn)\phi(x_1,\ldots, x_n) iff ϕM(x1,,xn)\phi^M(x_1,\ldots, x_n).
  • Suppose NN, MM are transitive classes and NMN\subseteq M.
    • If ϕ\phi is Σ1\Sigma_1, then ϕN\phi^N implies ϕM\phi^M. (upward absoluteness)
    • If ϕ\phi is Π1\Pi_1, then ϕM\phi^M implies ϕN\phi^N. (downward absoluteness)
    • If ϕ\phi is Δ1\Delta_1, then ϕMϕN\phi^M\leftrightarrow\phi^N.

The model VαV_\alpha:

  • If α\alpha is a limit ordinal, then VαV_\alpha is a model of Extensionality, Foundation, Pairing, Union, Nullset, Separation, and Powerset.
  • If α>ω\alpha>\omega, then VαV_\alpha is a model of Infinity.
  • If α\alpha is a strongly inaccessible cardinal, then VαV_\alpha is a model of Collection.

The model HκH_\kappa:

  • If κ\kappa is a cardinal, then HκH_\kappa is the collection of sets whose transitive closure has size less than κ\kappa.
  • For every regular cardinal κ\kappa, HκH_\kappa is a model of ZFC - Powerset.

The reflection theorem

  • Suppose Mα:αORD\langle M_{\alpha}: \alpha\in\text{ORD}\rangle is a cumulative hierarchy:
    • MαM_{\alpha} is transitive.
    • For all α<β\alpha < \beta, MαMβM_{\alpha}\subseteq M_{\beta}.
    • (Continuous) If λ\lambda is a limit, Mλ=α<λMαM_{\lambda} = \bigcup_{\alpha < \lambda} M_{\alpha}.
  • Let M=MαM = \bigcup M_{\alpha}. Then for every formula φ\varphi, there exists a closed and unbounded set of ordinals α\alpha, s.t. for all sets XˉMα\bar{X}\in M_{\alpha}, Mαφ(xˉ)M_{\alpha}\models\varphi(\bar{x}) iff Mφ(xˉ)M\models\varphi(\bar{x}).
  • 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 LL:

  • For a set MM, let Def(M)\mathrm{Def}(M) be the set of definable sets over (M,)(M, \in) with parameters of MM. The function MDef(M)M\mapsto\mathrm{Def}(M) is Δ1\Delta_1.
  • Replace P\mathcal{P} with Def\mathrm{Def} in the definition of VV, and we will get the constructible universe LL.
    • L0=L_0 = \varnothing.
    • Lα+1=Def(Lα)L_{\alpha+1} = \mathrm{Def}(L_{\alpha}), for any α\alpha;
    • Lλ=β<λLβL_{\lambda} = \bigcup_{\beta<\lambda}L_{\beta}, for λ\lambda a limit ordinal;
    • L=αLαL = \bigcup_{\alpha} L_{\alpha}.

Properties of LL:

  • (ZF) For all ordinals α\alpha,
    • LαVαL_{\alpha} \subseteq V_{\alpha}
    • LαL_{\alpha} and LL are transitive. LL is a cumulative hierarchy.
    • LαORD=αL_{\alpha}\cap\mathrm{ORD} =\alpha, so LL contains all ordinals.
  • Lα=α\|L_{\alpha}\| = \|\alpha\| for each infinite α\alpha.
  • (ZF) LL is a model of ZF.
  • Define a strict partial order <L<_L on LL as follows: x<Lyx <_L y if the rank of xx in LL is less than that of yy; or they have the same LL-rank but the minimal number of formula defining xx is less than that of yy. Then, <L<_L is a well-ordering on LL.
    • (ZF) LACL\models \mathrm{AC}.
  • Let V=LV=L abbreviate xαORD xLα\forall x\exists \alpha\in\mathrm{ORD}\ x\in L_{\alpha}.
  • (The absoluteness of constructibility) If MM is a transitive class inner model of ZF that contains all ordinals, then LM=LL^M = L. Further, (V=L)L(V=L)^L.
  • Corollary: LL is the smallest transitive inner model that contains all ordinals.

Condensation:

  • There is a finite set SS of axioms of ZF-Powerset s.t. if MSM\models S and MV=LM\models V=L, then M=LλM=L_{\lambda} for some limit ordinal λ\lambda.
  • There is a Σ2\Sigma_2 sentence φ\varphi s.t. for every transitive set MM, MφM\models\varphi iff M=LλM = L_{\lambda} for some limit ordinal λ\lambda.
  • For every limit ordinal λ\lambda, if M(Lλ)M\prec (L_\lambda) is an elementary submodel, then the transitive collaps of MM is LγL_\gamma for some limit ordinal γλ\gamma \leq \lambda.
  • Assume V=LV=L. If κ\kappa is a cardinal and xκx\subseteq\kappa, then xLλx\in L_{\lambda} for some λ<κ+\lambda < \kappa^+.
    • LL models GCH.
    • Con(ZF)Con(ZFC)Con(ZFC+GCH)\text{Con}(\text{ZF})\to\text{Con}(\text{ZFC})\to\text{Con}(\text{ZFC}+\text{GCH}).
  • If κ\kappa is an uncountable regular cardinal, then LκL_{\kappa} models ZF-Powerset.
    • If V=LV=L, then Hκ=LκH_{\kappa} = L_{\kappa} for all cardinals.

Other properties of LL:

  • V=LV=L implies +\diamondsuit^+.
  • If κ\kappa is weakly inaccessible, then LκL_{\kappa} models ZFC.
  • V=LV=L 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 ϕ\phi is consistent of TT,

  • First, start with a model MM in which ϕ\phi is not necessarily true.
  • Punch new elements into MM and get a structure NN, where ϕ\phi is true.
  • Show that NN is still a model of TT.

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 MM, we cannot choose M=VM = V. To have more choices on the missing elements, we want MM as simple as possible. Therefore, we can use a ctm MM. 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:

  • MM has ω\omega, since it's absolute.
  • MM does not have all subsets of ω\omega, because otherwise MM cannot be countable.
  • In VV, there is an injection from ω2M\omega_2^M to P(ω)\mathcal{P}(\omega), but MM cannot see it.

Now, we want to inject this injection into MM. 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 P\mathbb{P} be finite partial functions ω×ω2M2\omega\times\omega_2^M\to 2. 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 1P=1_{\mathbb{P}} = \varnothing.
  • Every element is part of a multimap from ω2\omega_2 to ω\omega, ω×ω2\omega\times\omega_2.
    • Let f(α)={n:p(n,α)=1}f(\alpha) = \{n: p(n, \alpha) = 1\}, then ff will be a partial function ω2P(ω)\omega_2\to\mathcal{P}(\omega).
  • P\mathbb{P} in MM, because both ω\omega and ω2\omega_2 are in MM.
  • If pqp\leq q, then we say pp extends qq or pp refines qq.
  • If there is some rr extends both pp and qq, we say pp and qq are compatible.
    • Intuitively, two compatible elements look like in a sublattice, though there does not exist a real lattice. For example, p={(0,0)1,(0,ω)0}p = \{(0,0)\mapsto 1, (0,\omega)\mapsto 0\} and q={(0,0)1,(1,1)0}q = \{(0,0)\mapsto 1, (1,1)\mapsto 0\}. Then, r=pqr = p\cup q refines both pp and qq.
  • A subset FF of P\mathbb{P} 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 \vee.
    • f=Ff = \bigcup F is a partial function ω×ω2M2\omega\times\omega_2^M\to 2.

Now we want to make sure that

  • The union of FF is a total function ω×ω2M2\omega\times\omega_2^M\to 2.
  • The function ω2P(ω)\omega_2\to\mathcal{P}(\omega) that the union of FF leads to is an injection.
  • By augmenting MM with FF, we can get a ZFC model.

The concept of generics solves these issues:

  • A subset XPX\subseteq\mathbb{P} is dense if it can refine every element of P\mathbb{P}.
  • XX is dense below pp if it can refine every element qpq\leq p.
  • Suppose MM is a transitive model containing P\mathbb{P}. A filter GPG\subseteq\mathbb{P} is MM-generic if it meets every dense set. That is, for all dense DPD\subseteq\mathbb{P} in MM, we have GDG\cap D\neq\varnothing.
  • For each (n,α)ω×ω2(n,\alpha)\in\omega\times\omega_2, the set {pP:(n,α)dom(p)}\{p\in\mathbb{P}: (n,\alpha)\in\mathrm{dom}(p)\} is dense. Thus, g=Gg = \bigcup G is a total function.
  • For all α,β<ω2\alpha, \beta< \omega_2, the set {pP:(n)(n,α)dom(p)(n,β)dom(p)p(n,α)p(n,β)}\{p\in\mathbb{P}: (\exists n)(n,\alpha)\in\mathrm{dom}(p)\wedge (n,\beta)\in\mathrm{dom}(p)\wedge p(n,\alpha)\neq p(n,\beta) \} is also dense. Thus, the function f(α):={n:g(n,α)=1}f(\alpha) := \{n: g(n,\alpha) = 1\} is an injection from ω2\omega_2 to ω\mathcal{\omega}.

Now we go back to augment MM. We want to get a new model M[G]M[G ] s.t. MM[G]M\subseteq M[ G] and GM[G]G\in M[G ]. 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 mMm\in M, we bind a "probability" pPp\in\mathbb{P} to it as (m,p)(m, p). However, we cannot use {(m,p):mMpP}\{(m, p): m\in M\wedge p\in\mathbb{P}\} because it's clearly not a model: Let a=(m1,p1)a = (m_1, p_1) and b=(m2,p2)b = (m_2, p_2), then {a,b}\{a, b\} cannot be represented. Therefore, we need to define a cumulative hierarchy:

  • A set τ\tau is a P\mathbb{P}-name if every element in τ\tau is an ordered pair (σ,p)(\sigma, p), where σ\sigma is a P\mathbb{P}-name and pPp\in\mathbb{P}.
  • Equivalently, we have the following hierarchy:
    • V0P=V^{P}_0 = \varnothing;
    • Vα+1P=P(VαP×P)V^{P}_{\alpha+1} = \mathcal{P}(V^{P}_{\alpha}\times \mathbb{P});
    • VλP=α<λVαPV^{P}_{\lambda} = \bigcup_{\alpha< \lambda} V^{P}_{\alpha};
    • VP=αVαPV^{P} = \bigcup_{\alpha} V^{P}_{\alpha};
    • Since being a P\mathbb{P}-name is absolute, the set of P\mathbb{P}-names in MM equals VPMV^{P}\cap M.

What we define is like the language LM\mathcal{L}_{M}, 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 GPG\subseteq\mathbb{P} be a MM-generic. For every P\mathbb{P}-name τ\tau, the value of τ\tau under GG is defined by recursion: τ[G]={σ[G]:(σ,p)τpG}\tau[ G] = \{\sigma[ G]: (\sigma, p)\in\tau\wedge p\in G\}.
  • For example, let τ={(,p),({(,1)},g)}\tau = \{(\varnothing, p), (\{(\varnothing, 1)\}, g)\}. Suppose gGg\in G. Then {(,1)}[G]=0\{(\varnothing, 1)\}[ G] = 0 is in τ[G]\tau[ G]. Hence, if pGp\notin G, τ[G]={0}\tau[ G] = \{ 0\}; otherwise, τ[G]=2\tau[ G] = 2.
  • Let M[G]M[ G] be the set of τ[G]\tau[ G] for every P\mathbb{P}-name τ\tau that is in MM.

Intuitively, M[G]M[G ] is like a threshold cut, plus Mostowski collapse.

Now we have:

  • M[G]M[ G] is transitive.
    • By the hierarchical definition of values.
  • MM[G]M\subseteq M[ G].
    • Let xˇ={(yˇ,1P):yx}\check{x} = \{(\check{y}, 1_{\mathbb{P}}): y\in x\} for xMx\in M. Then xˇ[G]=x\check{x}[G ] = x. Because the maximal 11 is always in GG, just like probability 1.
  • GM[G]G\in M[ G].
    • Let τ={(pˇ,p):pP}\tau = \{(\check{p}, p): p\in\mathbb{P} \}. Then, τ[G]=G\tau[ G] = G.
  • ORDM=ORDM[G]\mathrm{ORD}\cap M = \mathrm{ORD}\cap M[ G]

Such GG is not constructibly defined, but always exists, because the following lemma:

  • If MM is a ctm, then for every forcing poset P\mathbb{P} and pPp\in P, there is a MM-generic filter GG containing pp.
  • Note: the existence of generic filters comes from that MM can only see finite subsets of P\mathbb{P}. For example, let P\mathbb{P} be an infinite binary tree. If P(P)M=P(P)V\mathcal{P}(\mathbb{P})^M = \mathcal{P}(\mathbb{P})^V, then there do not exist a generic filter. Because for every filter FF, the complement set PF\mathbb{P}\setminus F is dense.

Now we need to show that M[G]M[ G] 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 GG. Formally, we define the forcing relation \Vdash s.t.

M[G]φ(τ1[G],,τn[G])    (pG) pPφ(τ1,,τn)M[ G]\models\varphi(\tau_1[ G],\ldots, \tau_n[ G]) \iff (\exists p\in G)\ p\Vdash^{\mathbb{P}}\varphi(\tau_1,\ldots, \tau_n)

Note that \Vdash is well-defined in MM, since every P\mathbb{P}-name and pp is in MM. The only thing MM does not know is GG.

We define it as follows:

  • Atomic formula τσ\tau\in\sigma:
    • An element is in a set if it equals to some element in the set.
    • τσ=(σ,p)σ(Ipτ=σ)\| \tau\in\sigma \| = \bigvee_{(\sigma', p')\in\sigma}\left( I_{p'}\cap \| \tau = \sigma' \| \right), where IpI_{p'} is the principal ideal {qP:qp}\{q\in \mathbb{P}: q\leq p'\}.
      • Note: in a complete boolean algebra generated by a poset topological space, \wedge is \cap, but \vee is not \cup. Actually, pqp\vee q is (pq)(p\cup q)^{\bot\bot}. Here, \bot means the complement set of its closure. And of course, ¬\neg is \bot. For example, in a poset of finite binary strings, I00I01I_{00}\cup I_{01} does not include the string 00, but I00I01=I0I_{00}\vee I_{01} = I_{0}.
      • Note; To understand why here we use IpI_p, consider that an event with probability pp. It happens when pp is greater than the cut GG, which is equivalent to GpG\leq p.
    • pτσp\Vdash \tau\in\sigma iff (σ,p)σ{qp:qτ=σ}\bigcup_{(\sigma', p')\in\sigma} \{q \leq p': q\Vdash \tau = \sigma' \} is dense below pp.
    • pτσp\Vdash \tau\in\sigma iff {qp:(σ,p)σ[qpqτ=σ]}\{ q\leq p: \exists (\sigma', p')\in\sigma [q\leq p'\wedge q\Vdash \tau = \sigma']\} is dense below pp.
  • Atomic formula τ=σ\tau = \sigma:
    • A set xx is equal to yy if zxzyz\in x \leftrightarrow z\in y.
    • τ=σ=(τ,p)τ(Ipτσ)(σ,p)σ(Ipστ)\| \tau = \sigma \| = \bigcap_{(\tau', p')\in\tau}(I_{p'}\rightarrow \|\tau'\in\sigma\|)\cap \bigcap_{(\sigma', p')\in\sigma}(I_{p'}\rightarrow \|\sigma'\in\tau\|)
      • Here, xyx \rightarrow y means ¬xy\neg x\vee y.
    • pτ=σp\Vdash \tau = \sigma iff for all (π,_)τσ(\pi, \_)\in \tau\cup\sigma and all qpq\leq p, qπτqπσq\Vdash \pi\in\tau \leftrightarrow q\Vdash \pi\in\sigma.
    • pτ=σp\Vdash \tau = \sigma iff for all (τ,p)(\tau', p'), {qP:qpqτσ}\{q\in\mathbb{P}: q\leq p'\to q\Vdash\tau'\in\sigma \} is dense below pp, and for all (σ,p)(\sigma', p'), {qP:qpqστ}\{q\in\mathbb{P}: q\leq p'\to q\Vdash\sigma'\in\tau \} is dense below pp.
  • Formula φψ\varphi\wedge\psi:
    • φψ=φψ\| \varphi\wedge\psi \| = \|\varphi\|\cap \|\psi\|.
    • pφψp\Vdash \varphi\wedge\psi iff pφp\Vdash\varphi and pψp\Vdash\psi.
  • Formula φψ\varphi\vee\psi:
    • φψ=φψ\| \varphi\vee\psi \| = \|\varphi\|\vee \|\psi\|.
    • pφψp\Vdash \varphi\vee\psi iff {qP:qφ}{qP:qψ}\{q\in\mathbb{P}: q\Vdash\varphi\}\cup\{q\in\mathbb{P}: q\Vdash\psi\} is dense below pp.
  • Formula ¬φ\neg\varphi:
    • ¬φ=¬φ\| \neg\varphi \| = \neg \| \varphi \|
    • p¬φp\Vdash \neg\varphi iff there is no qpq\leq p s.t. qφq\Vdash \varphi
  • Formula x φ(x)\exists x\ \varphi(x):
    • x φ(x)=τφ[τ]\| \exists x\ \varphi(x) \| = \bigvee_{\tau} \| \varphi[ \tau] \|.
    • px φ(x)p\Vdash \exists x\ \varphi(x) iff the set of qpq\leq p s.t. there exists a P\mathbb{P}-name τ\tau satisfying qφ[τ]q\Vdash \varphi[ \tau] is dense below pp.
  • Formula x φ(x)\forall x\ \varphi(x):
    • x φ(x)=τφ[τ]\| \forall x\ \varphi(x) \| = \bigcap_{\tau} \| \varphi[ \tau] \|.
    • px φ(x)p\Vdash \forall x\ \varphi(x) iff for all P\mathbb{P}-name τ\tau, pφ[τ]p\Vdash \varphi[ \tau].

The forcing relation has the following properties:

  • Force = Truth lemma. Described above.
  • Definability. \Vdash is a well-defined relation in MM.
  • Coherence.
    • If pφp\Vdash\varphi, then for all qpq\leq p, qφq\Vdash\varphi.
    • If the set qφq\Vdash\varphi is dense below pp, then pφp\Vdash\varphi.

Now we can prove that M[G]M[ G] is a model by showing evidence as P\mathbb{P}-names in MM.

Lemma: If MM is a transitive model and GG is a MM-generic, then M[G]ZFCM[ G]\models\mathrm{ZFC}.

One thing we need to ensure is that in M[G]M[ G], ω2\omega_2 is the ω2\omega_2 in MM. This is given by ccc.

Countable chain condition (ccc):

  • A poset P\mathbb{P} is ccc if every strong antichain is countable.
  • A strong antichain is an antichain whose elements are pairwise incompatible.
  • If MM proves P\mathbb{P} is ccc, then MM and M[G]M[ G] 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 P(ω)=2\|\mathcal{P}(\omega)\| = \aleph_2. Then, by the conpactness theorem, ¬CH\neg\mathrm{CH} 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