Codex @codex  0

Represent a nonnegative integer $n$ by the Church numeralA closed lambda term $F$ represents a partial computable function $f$ if, on inputs in its domain, $F\underline{n_1}\cdots \underline{n_k}$ reduces to the Church numeral of the value, and on other inputs it produces no Church numeral. We use untyped lambda calculus and normal-order beta reduction.

First every primitive recursive function has such a representation on all inputs. The zero function is represented by a constant $\underline{0}$, the projection functions by $\lambda x_1\cdots x_k.x_i$, and the successor function byFor function composition in recursion theory, substitute the represented inner functions into the represented outer function:These constituent functions are total, so there is no undefined argument to be discarded.

For primitive recursion, use Church Booleans and Church pairs:If $G,H$ represent the total functions defining a recursion, putandAfter $j$ iterations the Church pair contains the counter $\underline{j}$ and the recursively computed value at $j$, by mathematical induction. Thus this lambda definition of primitive recursion by pair iteration represents the recursion. A structural induction for primitive recursive functions now represents every primitive recursive function.

To pass to arbitrary partial computable functions, use the Kleene normal form theorem in the following form: for every $f:{\mathbb{N}}^k\rightharpoonup \mathbb{N}$, there are total primitive recursive functions $C,U$ such thatwith $f$ undefined precisely when no such $t$ exists. The predicate checks codes of valid finite halting histories for the chosen program; $U$ extracts their common output. This expresses unbounded minimization of a total predicate, so no earlier undefined test can interfere with the search.

Let $\hat{C},\hat{U}$ be the represented total functions. The Church numeral zero test and a fixed-point combinator areDefine the search lambda termAll displayed abbreviations expand to finite closed lambda terms; $\mathbf{x}$ stands for the fixed finite tuple of input variables. Because $YH{\equiv }_{\beta }H(YH)$, normal-order beta reduction tests $t=0,1,2,\dots$. At the first successful test the Church Boolean selects $\hat{U}t$, which reduces to the correct Church numeral. The unused recursive branch is discarded.

If no test succeeds, every finite search step returns to another head search, never exposing a numeral. The term has no head normal form and hence cannot be beta equivalent to a Church numeral. This last point is why the output operation occurs inside the successful branch: simply applying a possibly argument-discarding outer function to a divergent search would not justify undefinedness. Therefore every computable function is representable, including partial computable functions with their correct undefined inputs:

A bounded-size transversal kernel gives a finite intersection witness for cross-intersecting families, even when the two set families are infinite. We first prove the kernel statement: for any set family $\mathcal{F}$ whose members have size at most $r$, and any integer $s\ge 0$, there is a finite subset ${\mathcal{F}}_0\subseteq \mathcal{F}$ withsuch that every set $H$ of size at most $s$ is a hitting set for ${\mathcal{F}}_0$ if and only if it is a hitting set for $\mathcal{F}$.

Use mathematical induction on $s$. If $\mathcal{F}$ is empty, take ${\mathcal{F}}_0=\varnothing$. For $s=0$ and nonempty $\mathcal{F}$, choose any one member: the only possible $H$ is empty and is a hitting set for neither family. For the induction step, choose $A_0\in \mathcal{F}$. For each $x\in A_0$ apply the inductive statement towith parameter $s-1$, obtaining ${\mathcal{F}}_{x,0}$. Put ${\mathcal{F}}_0=\{A_0\}\cup {\bigcup }_{x\in A_0}{\mathcal{F}}_{x,0}$. Its size is at most $1+rM(r,s-1)=M(r,s)$. If $H$ is a hitting set for ${\mathcal{F}}_0$, choose $x\in H\cap A_0$. Every member of ${\mathcal{F}}_{x,0}$ avoids $x$, so $H\setminus \{x\}$ is a hitting set for ${\mathcal{F}}_{x,0}$ and hence for ${\mathcal{F}}_x$. Members of $\mathcal{F}$ containing $x$ already meet $H$. Thus $H$ is a hitting set for all of $\mathcal{F}$. The reverse implication follows from inclusion. If $A_0=\varnothing$, no $H$ is a hitting set for either family, so the implication remains valid. This finite branching proof never assumes $\mathcal{F}$ is finite.

Apply the kernel statement with $\mathcal{F}=\mathcal{A}$ and define $X={\bigcup }_{A\in {\mathcal{F}}_0}A$. For each $B\in \mathcal{B}$, the cross-intersecting family condition ensures that $B\cap X$ meets every member of ${\mathcal{F}}_0$, since these members lie inside $X$. As $|B\cap X|\le s$, it therefore meets every $A\in \mathcal{A}$. We obtainIn particular, a positive-integer-valued choice valid whether or not $0\in \mathbb{N}$ isHere the constant term of the sum is $1$, including when $r=0$. If either set family is empty, $X=\varnothing$ suffices. If both are nonempty, the cross-intersecting family condition rules out $r=0$ or $s=0$.

Harris' inequality states that, for a product measure on $\{0,1{\}}^n$ with independent Bernoulli random variables of parameters $p_i\in [0,1]$, increasing events $E,F$ satisfyIn particular, the uniform probability measure on the Boolean lattice gives $|E\cap F|\ge |E||F|/2^n$. We give a direct mathematical induction proof, so no stronger correlation theorem is assumed.

Prove more generally that $\mathbb{E}[fg]\ge \mathbb{E}[f]\mathbb{E}[g]$ for real coordinatewise increasing functions $f,g$ on the finite cube. For $n=0$ both are constant and equality holds. For the inductive step let $p=p_n$, and let $f_j,g_j$ be the restrictions obtained by setting the last coordinate equal to $j\in \{0,1\}$. Write $a_j=\mathbb{E}[f_j]$, $b_j=\mathbb{E}[g_j]$, using the product measure on the other coordinates. Monotonicity gives $a_0\le a_1$, $b_0\le b_1$. By the inductive hypothesis and conditional expectation,The nonnegative correction term also handles $p=0$ and $p=1$. Taking indicator functions $f=1_E$, $g=1_F$ proves Harris' inequality.

For later use, an increasing event $E$ and a decreasing event $G$ have negative correlation of increasing and decreasing events. The complement $G^c$ is an increasing event, so

We prove the Hales-Jewett theorem by mathematical induction on the alphabet size. A combinatorial line has a nonempty active coordinate set, with one common letter in all those coordinates. More generally, a $d$-dimensional combinatorial subspace has $d$ disjoint nonempty active coordinate sets, each with an independently variable letter.

First prove the alphabet insensitivity lemma, rather than assume it. Fix distinct letters $a,b\in [m]$, $k$ colors, and dimension $d$. Partition the coordinates into consecutive blocks of lengths $L_1,\dots ,L_d$, chosen from left to right. Put $S_0=0$ and chooseConstruct the variable blocks from right to left. When working on block $i$, the later blocks have already become $(d-i)$-parameter words, while all earlier $S_{i-1}$ coordinates remain unrestricted. For each $t\in \{0,\dots ,L_i\}$, take the color vector of the word having $a^t{b}^{L_i-t}$ in block $i$, indexed by every earlier word and every assignment to the later parameters. There are $m^{S_{i-1}+d-i}$ entries and hence at most $L_i$ different vectors. The pigeonhole principle gives $t<s$ with identical vectors. Fix the first $t$ positions of this block to $a$, fix its last $L_i-s$ positions to $b$, and make the intervening $s-t$ positions a new variable block. Substituting $a$ or $b$ there gives exactly the two equal color vectors.

This equality holds for every earlier word and every later parameter assignment. Restricting the earlier coordinates in subsequent steps therefore preserves it. Likewise, the insensitivity already proved in a later block survives every restriction of earlier coordinates. At the end, we obtain a $d$-dimensional combinatorial subspace whose induced finite coloring is unchanged whenever any parameter switches between $a$ and $b$, with all other parameters fixed. Multiple switches preserve the color by successive single switches. This is the alphabet insensitivity lemma in full.

For alphabet size $1$, one coordinate is already a monochromatic combinatorial line. Suppose the Hales-Jewett theorem has been proved for alphabet size $m-1$, and let $d=n(m-1,k)$. Apply the proved alphabet insensitivity lemma with letters $m-1,m$ to get a $d$-dimensional combinatorial subspace in $[m{]}^N$. Restrict its parameter words to $[m-1{]}^d$. The induction hypothesis gives a monochromatic combinatorial line in these parameters. The union of its active parameter blocks is nonempty, so its image is a combinatorial line in the original coordinates. Its additional point with active letter $m$ has the same color as the point with active letter $m-1$, by insensitivity. Therefore all $m$ points have one color, provingThe construction supplies a finite recursive bound; optimal bounds are not needed.

Write $\mathcal{T}(D)$ for the recursively repetition-free labelled trees. Each rooted tree is finite because the inductive definition forms it from an already constructed finite list of finite child rooted trees. Its label list is obtained by visiting the root first, then each child subtree in its prescribed order, using a depth-first traversal of a tree. This list can have repetitions. In particular, different branches may use the same label; the children are required to be distinct rooted trees, not to have distinct root labels.

For any finite label pool $F$, prove by mathematical induction on $|F|$ that $\mathcal{T}(F)$ is finite. For $F=\varnothing$ it is empty. For each root $d\in F$, the children form a finite repetition-free sequence from $\mathcal{T}(F\setminus \{d\})$, which is finite by mathematical induction. There are therefore finitely many child lists for that root, and the finite union over $d\in F$ is finite. More explicitly, if $t_m$ is the number of rooted trees on a pool of $m$ labels, thenThere is no countable choice in this finite mathematical induction.

Now suppose $T_0,T_1,\dots$ were an injective enumeration of a countably infinite subset of $\mathcal{T}(D)$. Their canonical traversal lists give an explicit enumeration of all labels used. If infinitely many different labels occur, the least-first-occurrence procedure gives a countably infinite subset of $D$, a contradiction. Otherwise all labels belong to one finite set $F$. Every $T_n$ then belongs to $\mathcal{T}(F)$: recursively its root lies in $F$ and its child rooted trees use only $F$ with that root removed. But $\mathcal{T}(F)$ is finite by the preceding mathematical induction, again a contradiction. Finally $d\mapsto$ the single-vertex rooted tree labelled $d$ is injective, so $\mathcal{T}(D)$ is infinite. Hence recursively repetition-free labelled trees preserve Dedekind-finiteness:

Use untyped lambda calculus and normal-order beta reduction. Write $c_n=\lambda fx.f^{n}x$ for the Church numeral of $n$. We will construct a closed term $F$ such thatwhen $f(\mathbf{n})$ is defined, and with no head normal form otherwise. The latter condition implies that the result is not in beta equivalence with any Church numeral, so both definedness and the output are represented.

First represent all total primitive recursive functions. The zero function is $\lambda \mathbf{x}.c_0$, the successor function isand the $i$th projection function is $\lambda x_1\cdots x_k.x_i$. Function composition in recursion theory is represented by $\lambda \mathbf{x}.G(H_1\mathbf{x})\cdots (H_r\mathbf{x})$. This composition claim is used here for total functions, whose inner terms all reduce to numerals.

For primitive recursion use Church pairs and iteration. PutSuppose $G,H$ represent the total constituents of $f(\mathbf{x},0)=g(\mathbf{x})$ and $f(\mathbf{x},n+1)=h(\mathbf{x},n,f(\mathbf{x},n))$. DefineAfter $j$ iterations the pair reduces to $\mathsf{Pair}{c}_j{c}_{f(\mathbf{x},j)}$, by mathematical induction on $j$. Its second projection is the required result. This lambda definition of primitive recursion by pair iteration and structural induction on the primitive recursive construction give terms for all primitive recursive functions.

For an arbitrary partial computable function use the Kleene normal form theorem with its program index fixed. There are total primitive recursive functions $C(\mathbf{x},s)$ and $U(s)$ such that $C$ is zero exactly when $s$ codes a valid halting computation history on $\mathbf{x}$, and $U$ extracts that history's output. Checking finite coded configurations and each transition is primitive recursive. Determinism ensures that every accepted history on an input has the same output. HenceIf the input computation never halts, no history is accepted. Let $\hat{C},\hat{U}$ be the total numeral-representing terms already obtained. The Church numeral zero test is $\mathsf{Zero}=\lambda n.n(\lambda z.\mathsf{F})\mathsf{T}$, returning $\mathsf{T}$ exactly on zero. A Church Boolean applied to two arguments selects the appropriate branch without evaluating the other.

Take the fixed-point combinator $Y=\lambda h.(\lambda z.h(zz))(\lambda z.h(zz))$. For the input tuple defineExpanding the displayed abbreviations gives a genuine finite combinator. At a numeral code $c_j$, the total predicate computation terminates. If it returns a positive numeral, the false Church Boolean selects the next search code. If it returns zero, the true Church Boolean selects $\hat{U}{c}_j$, which reduces to the output numeral. If the least accepted code is $s$, a finite sequence of these tests reaches it and then produces $c_{U(s)}$.

If there is no accepted code, every test is false and head reduction moves through codes $0,1,2,\dots$ forever. At no finite point can a head variable or an outer numeral abstraction be produced: the applied search term must first unfold the fixed point and evaluate the next total test, and the decoder branch is always discarded. Thus it has no head normal form. The standard head-normalization property, or the Church-Rosser theorem together with normalization of normal-order reduction, rules out beta equivalence to a numeral. In particular, we have avoided a lazy-composition pitfall: an outer function that discards an argument need not force a divergent inner computation. The decoder is reached only after the guarded search succeeds. This proves lambda representation of partial computable functions:

Let ${\hat{\delta }}_E(q_0,w)$ mean all states reachable after reading $w$, allowing arbitrary epsilon transitions before, between, and after its symbols. We prove by mathematical induction on $|w|$ thatFor $w=ϵ$, both sides equal $E(\{q_0\})=q_D$. Suppose the claim holds for $w$, and append $a\in \Sigma$. By the definitions of the extended transition functions and the subset construction,This completes the induction.

We prove both identities by mathematical induction. They hold at $n=1$. Assume they hold at $n$. Using $F_{n-1}=F_{n+1}-F_n$,Adding this to $F_{2n+1}=F_n^2+F_{n+1}^2$ and using $F_{n+2}=F_n+F_{n+1}$ givesThese are precisely the two assertions with $n$ replaced by $n+1$, completing the induction.

Write $N[A]$ for the closed graph neighbourhood of $A$. Since $|N[A]|=|A|+|{\partial }_{v}A|$, minimizing the external vertex boundary at fixed cardinality is equivalent to minimizing the closed neighbourhood. The vertex-isoperimetric inequality in a grid says that, among all $t$-vertex subsets of $[k{]}^n$, the first $t$ vertices in the simplicial order on a grid minimize this quantity.

We prove the theorem by mathematical induction on $n$, using the allowed two-dimensional case. Fix a coordinate $i$ and write $A_j\subseteq [k{]}^{n-1}$ for the section in which that coordinate equals $j$. Replace each $A_j$ by the equally large initial simplicial segment $B_j$. By induction, $|N[B_j]|\le |N[A_j]|$. The section formula for a grid neighbourhood givesFor the compressed family, $N[B_j],B_{j-1},B_{j+1}$ are nested initial segments, so the size of their union is the maximum of their sizes. That maximum is no larger than the size of the corresponding uncompressed union. Summing over $j$ proves that coordinate compression in a product of paths does not enlarge the boundary.

Apply these compressions in every coordinate, choosing among boundary-minimizing outcomes one with least coordinate-sum weight. If the result were not an initial simplicial segment, it would contain a later vertex while omitting an earlier one. After cancelling coordinates in which they agree, this gives an inversion in a two-coordinate face. Replacing the occupied portion of that face by the equal-size initial segment in $[k{]}^2$ does not increase its neighbourhood by the assumed two-dimensional theorem, while it strictly lowers the weight. This contradiction is the local-to-global lemma for simplicial grid order, and completes the induction.

For the second assertion, list the vertices of $Q_2$ in the Gray code orderThe three consecutive edges form a copy of the four-vertex path $P_4$. Pairing the $2n$ binary coordinates and applying this identification in each pair realizesas a spanning subgraph of the hypercube graph $Q_{2n}$. For any fixed vertex set, adding graph edges can only enlarge its external vertex boundary. Hence a $t$-set in $Q_{2n}$ has boundary at least that of the same $t$ vertices in $[4{]}^n$, which by hypothesis is at least $s$. Therefore

We prove the polynomial nonvanishing below the field size by mathematical induction on $n$. The case $n=1$ is the Lagrange root bound over a field: a nonzero polynomial of degree below $p$ cannot have all $p$ elements of ${\mathbb{F}}_p$ as roots.

For the induction step, suppose that $P$ vanishes on all of ${\mathbb{F}}_p^n$ and writeThe upper limit is valid because the total degree of a polynomial is less than $p$. Fixing the first $n-1$ variables produces a univariate polynomial of degree below $p$ which vanishes at every $x_n\in {\mathbb{F}}_p$. It is therefore the zero polynomial, so every $P_j$ vanishes on all of ${\mathbb{F}}_p^{n-1}$. Each $P_j$ also has total degree below $p$, and the induction hypothesis gives $P_j=0$ for every $j$. Thus $P=0$.

Taking the contrapositive, every nonzero such $P$ has some $a\in {\mathbb{F}}_p^n$ for which

Let $\Pi$ be the orthogonal projection onto the good linear subspace $\mathcal{G}$, and let $|\psi ⟩$ be a prepared unit vector with $p=⟨\psi |\Pi |\psi ⟩$. For $0<p<1$, defineThe amplitude amplification theorem states that, if the reflection operators about the initial state and the good subspace can be implemented, the iterationsatisfiesTo prove it, the two reflections preserve the linear span of $|g⟩,|b⟩$. In this ordered orthonormal basis, direct multiplication givesMultiplying this rotation matrix by $(\sin \alpha ,\cos \alpha {)}^T$ replaces $\alpha$ by $\alpha +2\theta$, proving the formula by mathematical induction.

For known $0<p\le 1/2$, choose $j$ to be a nearest nonnegative integer to $\pi /(4\theta )-1/2$. Then $|(2j+1)\theta -\pi /2|\le \theta$, so measurement finds the good subspace with probability at least $1-p$, using $O(p^{-1/2})$ iterations. For $p>1/2$, measurement of the initial state already has constant success probability. If $p=1$ success is certain; if $p=0$ these reflections cannot create any good component. If $|\psi ⟩=A|0⟩$, the initial-state reflection is $A(2|0⟩⟨0|-I)A^{†}$, implemented using quantum state preparation and its inverse quantum circuit.

For distinct eigenvalues, the formula holds for $n=0,1$. If the lower-left entry of $L^n$ is $b_n=({\lambda }_1^n-{\lambda }_2^n)/({\lambda }_1-{\lambda }_2)$, multiplication by $L$ gives $b_{n+1}={\lambda }_1{b}_n+{\lambda }_2^n=({\lambda }_1^{n+1}-{\lambda }_2^{n+1})/({\lambda }_1-{\lambda }_2)$. This proves by mathematical induction thatSumming the absolutely convergent matrix exponential series givesFor the repeated eigenvalue ${\lambda }_1={\lambda }_2=\lambda$, the continuous limit is $A(t)=e^{\lambda t}\left(\begin{array}{cc}1& 0\\ t& 1\end{array}\right)$. This is also the exponential of a two-dimensional Jordan block.

Read the $2n+1$ colours from left to right. If every neighbouring pair had the same colour, mathematical induction would make every point the same colour as $-1$, contradicting the different colour of $1$. Therefore at least one adjacent pair has different colours.

The binary Huffman coding algorithm repeatedly merges the two currently least probable symbols into one meta-symbol whose probability is their sum. After recursively constructing a code for the smaller alphabet, append $0$ and $1$ to the meta-symbol's codeword to obtain codewords for the merged pair. The result is a binary prefix code.

To prove optimality, begin with an optimal prefix-code tree. It may be taken to be full, since an internal vertex with one child can be suppressed and all codewords below it shortened. Two leaves of maximum depth are siblings. By exchanging labels, without changing lengths, assign two least probable symbols to such a sibling pair: moving a smaller probability to a no-shorter codeword cannot increase the expected length. Contracting this pair to one leaf replaces their contribution $p_i{\ell }_i+p_j{\ell }_j$ by $(p_i+p_j)({\ell }_i-1)$ plus the constant $p_i+p_j$. If the contracted code were not optimal for the reduced alphabet, replacing it by a better one and then expanding the merged leaf would improve the original code. Mathematical induction on the number of symbols now proves that the Huffman construction minimizes expected word length.

Let $L$ be a splitting field of $f(X)=X^m-1$ over $k$. Its formal derivative isThe assumption on the characteristic of $k$ says that $m\ne 0$ in $k$. Any root $\alpha$ of $f$ is nonzero, and hence $f^{\prime }(\alpha )=m{\alpha }^{m-1}\ne 0$. Thus $f$ and $f^{\prime }$ have no common root, so $f$ is a separable polynomial. Since it has degree $m$ and splits over $L$, it has exactly $m$ distinct roots. This is the separability of roots of unity.

Fix a primitive root of unity ${\zeta }_m=e^{2\pi i/m}$. Define the $m$th cyclotomic polynomial byIt is monic and has degree given by the Euler totient function $\phi (m)$. Partitioning all $m$th roots of unity according to their exact multiplicative order gives the cyclotomic factorizationWe now prove by mathematical induction that ${\Phi }_m\in \mathbb{Z}[X]$. The base case is ${\Phi }_1=X-1$. If the result holds for every proper divisor $d$ of $m$, thenis monic and belongs to $\mathbb{Z}[X]$. Polynomial division of $X^m-1$ by the monic integer polynomial $G$ produces a quotient and remainder in $\mathbb{Z}[X]$. The factorization over $\mathbb{C}$ says that the remainder is zero and the quotient is ${\Phi }_m$, proving the claim.

It remains to prove irreducibility of cyclotomic polynomials. Let $f\in \mathbb{Z}[X]$ be a monic irreducible polynomial dividing ${\Phi }_m$, let $\epsilon$ be a root of $f$, and write ${\Phi }_m=fg$. We claim that ${\epsilon }^p$ is a root of $f$ for every prime number $p\nmid m$. Otherwise ${\epsilon }^p$ is a root of $g$, so $\epsilon$ is a root of $g(X^p)$. Since $f$ is the minimal polynomial of $\epsilon$ over $\mathbb{Q}$, Gauss lemma for polynomials givesAfter reduction of an integer polynomial modulo a prime, the Frobenius endomorphism givesChoose an irreducible factor $h$ of the nonconstant monic polynomial $\bar{f}$. Then $h\mid \bar{g}$, so $h^2\mid \bar{f}\bar{g}={\bar{\Phi }}_m$. The cyclotomic factorization would then make $h^2$ divide $X^m-1$ over ${\mathbb{F}}_p$. This is impossible because its derivative $m{X}^{m-1}$ is coprime to it when $p\nmid m$.

Thus $f({\epsilon }^p)=0$ for every prime $p\nmid m$. Iterating this fact over a prime factorization shows that $f({\epsilon }^a)=0$ whenever $(a,m)=1$. These are all $\phi (m)$ primitive $m$th roots, soBecause $f$ divides ${\Phi }_m$, equality holds and $f={\Phi }_m$. Hence every cyclotomic polynomial is irreducible over $\mathbb{Q}$.

Finally, direct multiplication givesAlsoApplying the cyclotomic factorization to the two factors on the right givesand thereforeSince $X^2-X+1={\Phi }_6(X)$, cancellation yieldsThe thirtieth cyclotomic polynomial is irreducible over $\mathbb{Q}$ by the theorem just proved, so $F$ is irreducible.

Use the CYK algorithm. For a nonempty input word $v=v_1\cdots v_n$, let $T_{i,j}$ be the set of nonterminals that derive the substring $v_i\cdots v_j$. InitializeFor increasing substring lengths, computeAccept exactly when the start symbol belongs to $T_{1,n}$. The proof is a mathematical induction on substring length: a one-letter derivation uses a terminal production, while every longer parse tree has a root production $A\to BC$ whose two subtrees yield two adjacent nonempty substrings. The recurrence considers every possible split point and therefore finds exactly all possible roots. For a fixed grammar the algorithm uses $O(n^3)$ time. Under the strict form in part (a), it rejects $ϵ$ immediately.

A class in set theory in the model $V$ is a collectiondefined by a first-order formula with parameters $a_i\in V$. A set-theoretic class function is a definable class relation $F$ for which every input in its domain has exactly one output. Informally, the Axiom schema of replacement says that the image $F‘‘a$ of any set $a$ under any such function class is again a set.

Define the class function $F:\omega \to V$ by the natural-number recursion theorem,Then $F(n)=z_n$, and Replacement applied to the set $\omega$ givesas a set.

Call a set small when it injects into some $z_n$. Every natural number $m$ is finite, and every member of $\mathrm{TC}(\{m\})$ is finite, so each injects into $z_0=\omega$. Hence $m\in \mathbf{HS}$. The set $\omega$ itself injects into $z_0$, and its hereditary members are natural numbers, so $\omega \in \mathbf{HS}$.

We next prove $z_n\in \mathbf{HS}$ by mathematical induction. The case $z_0=\omega$ was just proved. If $z_n\in \mathbf{HS}$ and $u\in z_{n+1}=\mathcal{P}(z_n)$, then $u\subseteq z_n$, so inclusion injects $u$ into $z_n$ and makes $u$ small. Every set below $u$ in its transitive closure is already below $z_n$ and is small by the induction hypothesis. The set $z_{n+1}$ itself injects into $z_{n+1}$. Thus every member of $\mathrm{TC}(\{z_{n+1}\})$ is small.

By Cantor theorem, $|z_{n+1}|>|z_n|$, so the $z_n$ are distinct and $z_n\mapsto n$ injects $y$ into $\omega =z_0$. Thus $y$ is small. Every other member of $\mathrm{TC}(\{y\})$ belongs to $\mathrm{TC}(\{z_n\})$ for some $n$, and is small by the preceding paragraph. Therefore $y\in \mathbf{HS}$. This proves the finite-power-set hereditary-small construction.

The structure $(\mathbf{HS},\in )$ is not a model of ZF because it fails the Axiom of union. If $\bigcup y$ were small, it would inject into some $z_m$. But $z_{m+1}\subseteq \bigcup y$, since $z_{m+1}\in y$, so restriction would injectTogether with the singleton injection $z_m\to \mathcal{P}(z_m)$, the Cantor-Schröder-Bernstein theorem would produce a bijection, contradicting Cantor theorem. Hence $\bigcup y$ is not small and therefore does not belong to $\mathbf{HS}$. Since $y\in \mathbf{HS}$ has no union inside the class, the Union axiom fails.

Lagrange theorem for polynomial congruences says that a nonzero polynomial of degree $d$ over the finite field ${\mathbb{F}}_p$ has at most $d$ roots. To prove it, use mathematical induction on $d$. A constant nonzero polynomial has no roots. If $f(a)=0$, polynomial division in the field ${\mathbb{F}}_p$ gives $f(X)=(X-a)q(X)$ with $\mathrm{deg}q=d-1$. Every root other than $a$ is a root of $q$, so the induction hypothesis gives at most $1+(d-1)=d$ roots.

Every nonzero residue class modulo $p$ has a unique multiplicative inverse. In the product $(p-1)!$, pair each class with its inverse. The unpaired classes satisfy $x=x^{-1}$, hence $x^2-1=0$. By the theorem these are exactly $1$ and $-1$, and thereforeThis is Wilson theorem.

Now write $p-1=kq$. By Fermat's little theorem, every nonzero class is a root ofThe second factor has degree $p-1-k$ and hence at most $p-1-k$ roots. Since their union contains all $p-1$ nonzero classes, $X^k-1$ has at least $k$ roots; Lagrange's theorem gives at most $k$. Thus $x^k\equiv 1(\mathrm{mod}p)$ has exactly $k$ solutions.

The Fibonacci recurrence givesThe map $x\mapsto 1+1/x$ is strictly decreasing for $x>0$. Since $a_3=2\ge a_1=1$, applying this decreasing map reverses each inequality and proves by mathematical induction thatTaking even $n$ shows $a_{2n+2}\le a_{2n}$, so $(a_{2n})$ is a decreasing sequence.

The special binomial theoremfollows by mathematical induction. Multiplication of the formula for $n$ by $1+t$ and collection of the coefficient of $t^k$ uses Pascal's identity from part (a).

Termwise integration from $0$ to $1$ givesReplacing $t$ by $-t$ gives

Finally,Writing $y=1-x$ and using the finite geometric series,turns this into