Ordinal number
Ordinal numbers are a fundamental concept in mathematics, particularly in the fields of set theory and order theory. They are used to describe the position of an element within a well-ordered set, such as first, second, third, and so on. Unlike cardinal numbers, which quantify the number of elements in a set, ordinal numbers focus on the order of elements.
Definition[edit | edit source]
In formal terms, an ordinal number is defined based on the concept of transfinite numbers, introduced by Georg Cantor. An ordinal number represents the order type of a well-ordered set. This means it characterizes the abstract relationships of being "before" or "after" within a set, without reference to the specific nature of the elements of the set.
Notation[edit | edit source]
Ordinal numbers are often denoted using lowercase Greek letters, such as α (alpha), β (beta), and γ (gamma). The first ordinal number is 0, which represents the empty set. The next ordinal is 1, representing a set with one element, and so on for the finite ordinals. After all finite ordinals, comes the first infinite ordinal, denoted ω (omega), which represents the order type of the set of all natural numbers.
Properties[edit | edit source]
Ordinal numbers have several important properties:
- Transitivity: If α is an ordinal and β is a member of α, then β is also an ordinal and every element of β is an element of α.
- Well-ordered: Every non-empty set of ordinals has a least element under the usual "<" (less than) relation.
- Successor and Limit Ordinals: Every ordinal has a successor, which is the smallest ordinal greater than it. Ordinals that are not successors are called limit ordinals, with ω being the first limit ordinal.
Applications[edit | edit source]
Ordinal numbers have wide applications in various branches of mathematics:
- In set theory, they are used to describe the sizes of well-ordered sets.
- In model theory, ordinals are used in the construction of models.
- In proof theory and theoretical computer science, ordinals are used to measure the complexity of proofs and algorithms.
See Also[edit | edit source]
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Contributors: Prab R. Tumpati, MD