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If $M_i$ is a chain of measures on a common measurable space, then the supremum of the $M_i$ is the measure that assigns to each measurable set $X$ the supremum of the $M_i(X)$.
The space of a supremum of a family of topological spaces is the union of the spaces of the family.
If $M$ is a nonempty set of $\sigma$-algebras on $X$, then the $\sigma$-algebra generated by the union of the $\sigma$-algebras in $M$ is equal to the $\sigma$-algebra generated by the $\sigma$-algebra generated by the union of the $\sigma$-algebras in $M$.
If $m$ is a measure on $X$ and $M$ is a set of measures on $X$, then $A \in \mathcal{M}$ if and only if $A \in \mathcal{M}_m$ for all $m \in M$.
If $k(A_i) = k(B_i)$ for all $i$, and $R(c(A_i))$ and $R(c(B_i))$ for all $i$ such that $k(B_i) = \sup_i k(B_i)$, and $R(s(A_i))$ and $R(s(B_i))$ for all $i$, then $R(\sup_i A_i)$ and $R(\sup_i B_i)$.
If two families of measures agree on the sets they measure, then the supremum of the measures in the two families agree on the sets they measure.
If $M$ is a nonempty set of $\sigma$-algebras on the same space $X$, then the $\sigma$-algebra generated by the union of the $\sigma$-algebras in $M$ is contained in the $\sigma$-algebra generated by $X$.
If $f$ is measurable with respect to a measure $m$ and $m$ is a member of a set of measures $M$ such that all measures in $M$ have the same space, then $f$ is measurable with respect to the supremum of $M$.
If $f$ is measurable with respect to each measure space in a nonempty set $M$ of measure spaces, and if all the measure spaces in $M$ have the same underlying set, then $f$ is measurable with respect to the supremum measure space.
If $f$ is measurable with respect to each of the measures $M_i$, then $f$ is measurable with respect to the supremum of the measures $M_i$.
If $M$ is a nonempty set of subsets of $\Omega$, then the $\sigma$-algebra generated by the union of $M$ is the same as the $\sigma$-algebra generated by the union of the $\sigma$-algebras generated by the elements of $M$.
If $M$ is a nonempty set of subsets of $\Omega$, then $\sigma(\bigcup M) = \sigma(\bigcup_{m \in M} m)$.
If $M$ is a nonempty set and $f$ is a function from $M$ to the power set of $\Omega$, then $\sigma(\bigcup_{m \in M} f(m)) = \sigma(\bigcup_{m \in M} \sigma(\Omega, f(m)))$.
If $f$ is a function from $X$ to $Y$ and $M$ is a set of measures on $Y$, then the sets of the measure algebra of the supremum of $M$ under $f$ are the same as the sets of the supremum of the measure algebras of the measures in $M$ under $f$.
The sets of a restricted space are the same as the sets of the vimage algebra of the intersection of the space and the set.
If $A$ is a subset of the power set of $X$, then the $\sigma$-algebra generated by $X$ and $A$ is a subset of the $\sigma$-algebra $N$ if and only if $X$ is in $N$ and $A$ is a subset of $N$.
A function $f$ is measurable if and only if it is a function from the space of $M$ to the space of $N$ and the preimage of every measurable set in $N$ is measurable in $M$.
The set $X$ is in the $\sigma$-algebra generated by the image of $f$.
If $N'$ is a sub-$\sigma$-algebra of $N$ and $M'$ is a super-$\sigma$-algebra of $M$, then any $N$-measurable $M$-measurable set is $N'$-measurable $M'$-measurable.
If $f$ is a function from a measurable space $N$ to a set $A$, then $f$ is measurable with respect to the smallest $\sigma$-algebra on $A$ that makes $f$ measurable.
If $a \subseteq M$ and $\Omega' \in M$, then $\sigma(a) \subseteq M$.
If $X$ is a measurable set in the measure space $(Y, \mathcal{M}_i)$, then $X$ is a measurable set in the measure space $(Y, \mathcal{M})$, where $\mathcal{M}$ is the supremum of the $\sigma$-algebras $\mathcal{M}_i$.
If $f$ is measurable with respect to each $M_i$, then $f$ is measurable with respect to $\sup_{i \in I} M_i$.
If $X$ is a measurable set and $f$ is a measurable function, then the image of $X$ under $f$ is measurable.
If $M$ is a sub-$\sigma$-algebra of $N$, then the image of $M$ under $f$ is a sub-$\sigma$-algebra of the image of $N$ under $f$.
If $M$ is a sub-$\sigma$-algebra of $N$, then the restriction of $M$ to $X$ is a sub-$\sigma$-algebra of the restriction of $N$ to $X$.
The sets of a measure space $M$ are empty if and only if $M$ is the trivial measure space.
The only $\sigma$-algebra on a set $X$ that contains only the empty set is the trivial $\sigma$-algebra.
If $M$ is a finite measure, then the set of points $x$ such that $M(\{x\}) \neq 0$ is countable.
If $x$ is an integer, then $x^n$ is an $n$th power.
If $x = y^n$, then $x$ is an $n$th power.
If $x$ is an $n$th power, then there exists $y$ such that $x = y^n$.
A number $x$ is a zeroth power if and only if $x = 1$.
$1$ is the first power of any number.
The first power of any number is itself.
If $n$ is a positive integer, then $0$ is an $n$th power.
A number is an $n$th power if and only if it is zero and $n > 0$.
$1$ is an $n$th power.
The number $1$ is an $n$th power.
If $n$ is a positive integer, then $x$ is an $n$th power if and only if $n$ divides the multiplicity of $p$ in $x$ for every prime $p$.
If $n$ is a positive integer, then $x$ is an $n$th power if and only if $n$ divides the multiplicity of $p$ in $x$ for every prime $p$.
If $a$ and $b$ are $n$th powers, then $a \cdot b$ is an $n$th power.
If $a$ and $b$ are coprime and $a b$ is an $n$th power, then $a$ and $b$ are $n$th powers.
If $a$ and $b$ are coprime, then $a$ is an $n$th power if and only if $b$ is an $n$th power.
If $p$ is a prime number, then $p^k$ is an $n$th power if and only if $n$ divides $k$.
If $n$ divides $n'$, then $m^{n'}$ is an $n$th power.
The function is_nth_power_nat is defined by the following code:
The $n$th root of $0$ is $0$.
If $k > 0$, then the set of all $m \in \mathbb{N}$ such that $m^k \leq n$ is a subset of the set $\{0, 1, \ldots, n\}$.
If $k > 0$, then the set of all $m \in \mathbb{N}$ such that $m^k \leq n$ is finite and non-empty.
If $k > 0$ and $n \geq 1$, then $k$-th root of $n$ is the largest integer $x$ such that $x^k \leq n$.
If $k > 0$ and $x^k > n$, then the $k$th root of $n$ is less than $x$.
If $m^k \leq n < (m+1)^k$, then $n^{1/k} = m$.
The $k$th root of $0$ is $0$.
If $k > 0$, then the $k$th root of $1$ is $1$.
If $k > 0$, then the $k$th root of $1$ is $1$.
The first root of $n$ is $n$.
The first root of a natural number $n$ is $n$.
The $k$th root of $n$ is the largest integer $m$ such that $m^k \leq n$.
If $k^m \leq n$, then $n^{1/m} \leq n$.
If $m > 0$, then $(\text{nth\_root\_nat\_aux}(m, k, k^m, n) + 1)^m > n$.
If $k^m \leq n$ and $m > 0$, then the function $nth\_root\_nat\_aux$ returns the same value as $nth\_root\_nat$.
The naive code equation for the nth root of a natural number.
If $k$ is a positive integer, then the $k$th root of $n^k$ is $n$.
If $k$ is a positive integer that divides $m$, then the $k$th root of $n^m$ is $n^{m/k}$.
If $m \leq n$, then $\sqrt[k]{m} \leq \sqrt[k]{n}$.
The list $0$ followed by the empty list is the empty list.
The list constructor $x \# y$ is the same as the list constructor $x # y$.
The concatenation of a list with a singleton list is the same as the concatenation of the list with the singleton list.
If $x \neq 0$, then $x ## xs = x # xs$.
If $x$ is not $0$, then the result of stripping $x$ from the list $x :: xs$ is $x$ followed by the result of stripping $x$ from $xs$.
The tail of a list with a single element is the empty list.
Two polynomials are equal if and only if they have the same coefficients.
If two polynomials have the same coefficients, then they are equal.
All but finitely many coefficients of a polynomial are zero.
If the degree of a polynomial $p$ is less than $n$, then the coefficient of $x^n$ in $p$ is zero.
If the coefficient of $x^n$ in a polynomial $p$ is nonzero, then $n$ is less than or equal to the degree of $p$.
If the coefficients of a polynomial $p$ are zero for all indices greater than $n$, then the degree of $p$ is at most $n$.
If $n$ is less than the degree of a polynomial $p$, then there exists an index $i > n$ such that the coefficient of $x^i$ in $p$ is nonzero.
The coefficient of $x^n$ in the polynomial $0$ is $0$.
The degree of the zero polynomial is zero.
If a polynomial is nonzero, then its leading coefficient is nonzero.
The leading coefficient of a polynomial is zero if and only if the polynomial is zero.
If the coefficient of the $n$th power of a polynomial $p$ is zero, then either $p$ is the zero polynomial or the degree of $p$ is less than $n$.
If the coefficient of $x^d$ in a polynomial $p$ is zero, and $d$ is at least the degree of $p$, then the degree of $p$ is at most $d-1$.
The coefficient of a polynomial is equal to the coefficient of its representation.
The coefficient of the constant term of a polynomial is the constant term.
The coefficient of $x^n$ in $a + x p$ is the coefficient of $x^{n-1}$ in $p$.
The degree of a polynomial with a leading coefficient is at most one more than the degree of the polynomial without the leading coefficient.
If $p$ is a nonzero polynomial, then the degree of $p$ is one more than the degree of $p$ with a leading coefficient of $a$.
The degree of a polynomial of the form $a + 0x$ is $0$.
The degree of a polynomial with a nonzero constant term is one more than the degree of the polynomial without the constant term.
The polynomial $0x^0$ is equal to $0$.
Two polynomials are equal if and only if their leading coefficients are equal and their tails are equal.
A polynomial is zero if and only if its leading coefficient is zero and its tail is zero.
Every polynomial can be written as $a + bx + cx^2 + \cdots$, where $a, b, c, \ldots$ are coefficients.
If $P(0)$ and $P(p)$ implies $P(a + xp)$ for all $a$ and $p$, then $P(p)$ for all $p$.
If the degree of a polynomial is zero, then it is a constant polynomial.
The polynomial whose coefficients are all zero is the zero polynomial.
A polynomial is zero if and only if all of its coefficients are zero.