Question

Prove the following theorems: $\mathbb{N}_{\mathrm{o} \sigma}=\bigcap_{\mathrm{o}(\mathrm{o} \sigma)}\left[\lambda p_{\mathrm{o} \sigma} \cdot p_{\mathrm{o} \sigma} 0_\sigma \wedge \forall x_\sigma \cdot p_{\mathrm{o} \sigma} x_\sigma \supset p_{\mathrm{o} \sigma} \cdot S_{\sigma \sigma} x_\sigma\right]$

   Prove the following theorems:
$\mathbb{N}_{\mathrm{o} \sigma}=\bigcap_{\mathrm{o}(\mathrm{o} \sigma)}\left[\lambda p_{\mathrm{o} \sigma} \cdot p_{\mathrm{o} \sigma} 0_\sigma \wedge \forall x_\sigma \cdot p_{\mathrm{o} \sigma} x_\sigma \supset p_{\mathrm{o} \sigma} \cdot S_{\sigma \sigma} x_\sigma\right]$
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An Introduction to Mathematical Logic and Type Theory: To Truth Through Proof (Computer Science & Applied Mathematics)
An Introduction to Mathematical Logic and Type Theory: To Truth Through Proof (Computer Science & Applied Mathematics)
Peter B. Andrews 1st Edition
Chapter 6, Problem 8 ↓

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The theorem involves the set $\mathbb{N}_{\mathrm{o} \sigma}$, which we assume to be the set of natural numbers in a specific formal system or context. The notation $\mathrm{o}(\mathrm{o} \sigma)$, $\lambda p_{\mathrm{o} \sigma}$, $p_{\mathrm{o} \sigma} 0_\sigma$,  Show more…

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Prove the following theorems: $\mathbb{N}_{\mathrm{o} \sigma}=\bigcap_{\mathrm{o}(\mathrm{o} \sigma)}\left[\lambda p_{\mathrm{o} \sigma} \cdot p_{\mathrm{o} \sigma} 0_\sigma \wedge \forall x_\sigma \cdot p_{\mathrm{o} \sigma} x_\sigma \supset p_{\mathrm{o} \sigma} \cdot S_{\sigma \sigma} x_\sigma\right]$
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Key Concepts

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Inductive Definitions
An inductive definition specifies a set or type by stating a base element and a rule that, if an element belongs to the set, then so does another element constructed from it. In the context of the natural numbers, this is typically done by declaring a starting element (often 0) and a successor function that generates new elements. This method of definition lays the foundation for proofs by mathematical induction, ensuring that any property proven for the base case and preserved under the successor step holds for all elements in the defined set.
Intersection of Sets
The intersection of a collection of sets is the set of elements that are common to all of them. In defining the natural numbers, the intersection is taken over every set that is inductive (i.e., respects the base case and the successor rule), yielding the smallest or least inductive set. This guarantees that the natural numbers are exactly those elements that must belong to every inductive set and thus have the minimal structure required by their inductive definition.
Least Fixed Point
A least fixed point in this context is the minimal set that remains unchanged when the inductive construction is applied. It represents the smallest solution to the inductive definition, such that it is included in every set that satisfies the given properties. Defining the natural numbers as a least fixed point ensures that no excess elements are included beyond those necessary to satisfy the base case and iteration, capturing the essence of minimality that is important in many areas of logic and computer science.
Base Case and Inductive Step
The base case establishes the starting point of an inductively defined set, asserting that a particular element (commonly 0 in the naturals) is included. The inductive step shows that if an arbitrary element holds the property (or is a member of the set), then its successor (obtained via a specified function) also holds the property. Together, these two components form the backbone of mathematical induction, a proof technique used to establish that a property holds for all elements of an inductively defined set.
Higher-Order Logic
Higher-order logic extends first-order logic by allowing quantification not just over individual variables but also over functions and predicates. This increased expressive power enables the formulation of properties and definitions like the one concerning the natural numbers as the intersection of all inductive sets, where functions and sets themselves are treated as mathematical objects. Such a framework is essential for formalizing complex mathematical theories and reasoning about them in a rigorous manner.

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