Lattice (order)
- See lattice for other meanings of the term, both within and without mathematics.
In mathematics, a lattice is a partially ordered set in which all nonempty finite subsets have a least upper bound (also called supremum or join) and a greatest lower bound (also called infimum or meet). The term "lattice" comes from the shape of the Hasse diagrams of such orders.
Algebraic definition
A lattice can also be algebraically defined as a set L, together with two binary operations ∧ and ∨ (pronounced meet and join, respectively), such that for any a, b, c in L,
| a ∨ a = a |
a ∧ a = a |
idempotency laws |
| a ∨ b = b ∨ a | a ∧ b = b ∧ a | commutativity laws |
| a ∨ (b ∨ c) = (a ∨ b) ∨ c | a ∧ (b ∧ c) = (a ∧ b) ∧ c | associativity laws |
| a ∨ (a ∧ b) = a | a ∧ (a ∨ b) = a | absorption laws |
(The idempotency laws can be deduced from the absorption laws and therefore don't have to be stated separately.)
If the two operations satisfy these algebraic rules then they define a partial order ≤ on L by the following rule: a ≤ b if and only if a ∨ b = b, or, equivalently, a ∧ b = a.
L, together with the partial order ≤ so defined, will then be a lattice in the above order-theoretic sense.
Conversely, if an order-theoretic lattice (L, ≤) is given, and we write a ∨ b for the least upper bound of {a, b} and a ∧ b for the greatest lower bound of {a, b}, then (L, ∨, ∧) satisfies all the axioms of an algebraically defined lattice.
Homomorphisms
The class of all lattices forms a category if we define a homomorphism between two lattices (L, ∧, ∨) and (N, ∩, ∪) to be a function f : L → N such that
- f(a ∧ b) = f(a) ∩ f(b)
- f(a ∨ b) = f(a) ∪ f(b)
for all a, b in L. If a homomorphism is bijective, then its inverse is also a homomorphism, and it is called an isomorphism of lattices. The two involved lattices are then isomorphic; for all practical purposes, they are identical and differ only in the notation of their elements.
Every homomorphism is a monotone map between the two lattices, but not every monotone map yields a lattice homomorphism: in addition we need the compatibility with finite suprema and infima.
Properties of lattices, examples
A lattice is said to be bounded if it has a greatest element and a least element. The greatest element is often denoted by 1 and the least element by 0. If x is an element of a bounded lattice then any element y of the lattice satisfying x ∧ y = 0 and x ∨ y = 1 is called a complement of x. A bounded lattice in which every element has a (not necessarily unique) complement is called a complemented lattice.
A lattice in which every subset (including infinite ones) has a supremum and an infimum is called a complete lattice. (It is enough to require that every subset have a supremum; the existence of all infima then follows.) Complete lattices are always bounded. Many of the most important lattices are complete. Examples include:
- The subsets of a given set, ordered by inclusion. The supremum is given by the union and the infimum by the intersection of subsets.
- The unit interval [0,1] and the extended real number line, with the familiar total order and the ordinary suprema and infima.
- The non-negative integers, ordered by divisibility. The supremum is given by the least common multiple and the infimum by the greatest common divisor.
- The subgroups of a group, ordered by inclusion. The supremum is given by the subgroup generated by the union of the groups and the infimum is given by the intersection.
- The submodules of a module, ordered by inclusion. The supremum is given by the sum of submodules and the infimum by the intersection.
- The ideals of a ring, ordered by inclusion. The supremum is given by the sum of ideals and the infimum by the intersection.
- The open sets of a topological space, ordered by inclusion. The supremum is given by the union of open sets and the infimum by the interior of the intersection.
- The convex subsets of a real or complex vector space, ordered by inclusion. The infimum is given by the intersection of convex sets and the supremum by the convex hull of the union.
- The topologies on a set, ordered by inclusion. The infimum is given by the intersection of topologies, and the supremum by the topology generated by the union of topologies.
- The lattice of all transitive binary relations on a set.
- The lattice of all sub-multisets of a multiset.
- The lattice of all equivalence relations on a set; the equivalence relation ~ is considered to be smaller (or "finer") than ≈ if x~y always implies x≈y.
The Knaster-Tarski theorem states that the set of fixed points of a monotone function on a complete lattice is again a complete lattice.
The lattice of submodules of a module and the lattice of normal subgroups of a group have the special property that
x ∨ (y ∧ (x ∨ z)) = (x ∨ y) ∧ (x ∨ z)
for all x, y and z in the lattice.
A lattice with this property is called a modular lattice.
The condition of modularity can also be stated as follows: If x ≤ z then for all y we have the identity x ∨ (y ∧ z) = (x ∨ y) ∧ z.
A lattice is called distributive if ∨ distributes over ∧, that is,
x ∨ (y ∧ z) = (x ∨ y) ∧ (x ∨ z).
Equivalently, ∧ distributes over ∨. All distributive lattices are modular.
Two important types of distributive lattices are totally ordered sets and Boolean algebras (like the lattice of all subsets of a given set). The lattice of natural numbers, ordered by divisibility, is also distributive. A lattice is said to be completely distributive if the above distributivity law hold for arbitrary (infinite) meets and joins.
Distributive lattices are used to formulate pointless topology.
Important lattice-theoretic notions
In the following, let L be a lattice. We define some order-theoretic notions that are of particular importance in lattice theory.
An element x of L is called join-irreducible iff
- x = a ∨ b implies x = a or x = b for any a, b in L,
- if L has a 0, x is sometimes required to be different from 0.
When the first condition is generalized to arbitrary joins Vai, x is called completely join-irreducible.
The dual notion is called meet-irreducability. Sometimes one also uses the terms ∨-irreducible and ∧-irreducible, respectively.
An element x of L is called join-prime iff
- x ≤ a ∨ b implies x ≤ a or x ≤ b,
- if L has a 0, x is sometimes required to be different from 0.
Again, this can be generalized to obtain the notion completely join-prime and dualized to yield meet-prime. Any join-prime element is also join-irreducible, and any meet-prime element is also meet-irreducible. If the lattice is distributive the converse is also true.
Other important notions in lattice theory are ideal and its dual notion filter. Both terms describe special subsets of a lattice (or of any partially ordered set in general). Details can be found in the respective articles.
Literature
- B. A. Davey, H. A. Priestley: Introduction to Lattices and Order. Cambridge University Press, 2002. (ISBN 0521784514)
Referenced By
Algebraic structure | List of mathematical topics (J-L) | List of order topics
|