Boolean Algebras
(ブール代数)
Discrete Mathematics I
12th lecture, December 21, 2018
http://www.sw.it.aoyama.ac.jp/2018/Math1/lecture12.html
Martin J. Dürst
© 2005-18 Martin
J. Dürst Aoyama Gakuin
University
Today's Schedule
@@@@ next year, check/add the concept of order (as opposed to size) of a
Boolean algebra (needs more research, "order" doesn't show on Wikipedia,
not even "size" shows, maybe 'dimension' might work)
- Remaining schedule
- Summary and homework for last lecture
- Algebraic structures related to groups
- Boolean algebra
- Examples of boolean algebras
- Bitstrings and Bitwise Operations
- Structure of Boolean algebras
Video
Please use the video recordings!
Email messages will be sent out when the video recordings are available.
Usually, videos become available on the afternoon of the lecture.
Remaining Schedule
About makeup classes: The material in the makeup class is part of the final
exam. If you have another makeup class at the same time, please inform the
teacher as soon as possible.
補講について:
補講の内容は期末試験の対象。補講が別の補講とぶつかる場合には事前に申し出ること。
(注:
一時期、佐久田先生の授業とダブっていたが、解消済み。)
Summary of Last Lecture
- Algebraic structures are defined as sets with operations and
axioms
- Groups are the best known example of an algebraic structure, with a rich
theory
- Groups have one associtive binary operation, an identity
element, and inverse elements
- Examples of groups are (ℤ, +), (ℝ-{0}, ·), (ℝ+, ·),
and symmetric groups (permutations of n elements with
composition)
- Finite groups are represented by Cayley tables, and compared
using the concept of isomorphism (one-to-one mapping conserving
structure)
Sorry, it was removed! :)
Last Week's Homerwork 2:
Non-Isomorphic Groups of Size 4
Sorry, it was removed! :)
More Algebraic Structures
- Ring: Two operations, 'addition' and 'multiplication'; forms an Abelian
group under addition and a semigroup under multiplication, and addition
distributes over multiplication.
Examples: ℝ, ring of polynomials
- Field: Same as ring, but commutative, and 'multiplication' has to have an
inverse for all non-zero elements.
- Lattice: Two operations; both operations are associative and commutative,
and respect absorbtion laws
Boolean Algebra
- A Boolean algebra is an algebraic structure
- A Boolean algebra has one set (B), two special elements
(0, 1), and three operations (⫬, △,
▽)
- B = (B, 0, 1,
⫬, △, ▽) is a Boolean algebra if and only if it meets the
following conditions:
- 0 ∈ B, 1 ∈
B (1 is called unit element,
0 is called zero element)
- ⫬ is an unary operation on B, △ and
▽ are binary operations on B
- △ and ▽are associative and commutative, and
distribute over each other
- ∀a∈B:
a▽0 = a,
a△1 = a
(0 is the neutral element for ▽, 1
is the neutral element for △)
- ∀a∈B:
a▽⫬a = 1,
a△⫬a =
0
- This definition (operations, axioms) can be simplified
- Boolean algebras define a (partial) order, with 1 at the
top and 0 at the bottom
Boolean Algebra Example 1:
Basic Logic
- B is the set {false, true}
- 0 is false (0)
- 1 is true (1)
- ⫬ is negation (logical not, ¬)
- △ is conjunction (logical and, ∧)
- ▽ is disjunction (logical or, ∨)
- The (partial) order relation is false<true
- Hasse diagram: BAbasic_logic.svg
Comments on Boolean Algebra
- Symbols such as 0 and 1 (bold) are
abstract and do not have any concrete meaning
- A Boolean algebra is a (partial) order and a lattice
- Boolean algebra is a general concept covering logical operations, set
operations, and some (partial) orders
- Because a Boolean algebra is a partial order, it can be shown with a
Hasse diagram
Boolean Algebra Example 2:
A Powerset with Set Operations
- B is the powerset of a (finite) set U
- 0 is the empty set
- 1 is U (the universal set)
- ⫬is the complementary set operation
- △ is set intersection (∩)
- ▽ is set union (∪)
- The (partial) order relation is ⊂ (subset)
- Hasse diagram for U={a, b, c}: BApowerset.svg
Bitwise Operations
- Inside a computer, information is represented as strings of bits (e.g.
a=00101011, b=10011100).
- Bitwise operations are bitwise logic operations.
- Bitwise not: ¬ is applied to each bit (
~
in C, e.g.
¬a=11010100)
- Bitwise and: ∧ is applied to bits in the same position
(
&
in C*, e.g.
a∧b=00001000)
- Bitwise or: ∨ is applied to bits in the same position
(
|
in C*, e.g.
a∨b=10111111)
- Bitwise xor: XOR (⊕) is applied to bits in the same position
(
^
in C*, e.g.
a⊕b=10110111)
*) and many other programming languages
Boolean Algebra Example 3:
Bitstrings and Bitwise Operations
- B is the set of all the bit strings of length n
(e.g. for n=2, B={00, 01, 10, 11})
- 0 is the bit string of length n with all bits set to 0 (e.g.
00)
- 1 is the bit string of length n with all bits set to 1 (e.g.
11)
- ⫬ is bitwise not
- △ is bitwise and
- ▽ is bitwise or
- The (partial) order relation is the conjunction of the order relation at
each bit position: a≤b ↔
∀i∈{1,...,n}:
ai≤bi,
or a has 0 in all those bit positions where b has 0
(in C:
~(b|~a) ==
0).
- Hasse diagram for bit strings of length 4: BAbitstrings.svg
Boolean Algebra Example 4:
Integers and Divisibility
- B is formed by taking a set of n pairwise
coprime integers* (e.g. 2, 3, 5), and all the multiples
that include or exclude each of the integers (including 1)
- 0 is 1
- 1 is the product of all the
original n integers (e.g. 30)
- ⫬a is 1/a
- △ is the greatest common divisor
(GCD) of the operands
- ▽ is the least common multiple
(LCM) of the operands
- The (partial) order relation is divisibility
- Hasse diagram for {1, 2, 3,
5, 6, 10, 15, 30}: BAdivisibility.svg
*) This restriction can be slightly relaxed.
The Structure of Boolean Algebras
- The size of a finite boolean algebra is always |B| =
2n
- All boolean algebras have the same structure (an n-dimensional
cube)
(animation
of a 4-dimensional cube, even
higher dimensions (code))
- The Hasse diagram is the edges of the n-dimensional cube, when
placing 0 at the bottom and 1 at the
top
- The result of △ is the highest vertex equal or lower than its operands
(infimum, greatest lower bound)
- The result of ▽ is the lowest vertex equal or higher than its operands
(supremum, least upper bound)
- The result of ⫬ is the vertex diagonally oposite of its operand
- All boolean algebras of dimension n are isomorphic
- For all boolean algebras, the same laws apply (they can be proven from
the axioms)
Isomorphisms for Examples
- Basic logic is isomorphic to bitstrings of length 1 (0=false, 1=true)
- The subsets of a set of size n can be expressed as bit strings
of size n:
Each bit indicates presence (1) or absence (0) of the respective element
from the subset
- Set operations can be defined by logical operations
Examples: A ∪ B = {x|
x∈A ∨ x∈B}; A
∩ B = {x| x∈A ∧
x∈B}; Ac = {x|
¬(x∈A)}
- Examples with divisibility are constructed to include/exclude each
factor; this can be mapped to bitstrings or to set operations
Axioms for Boolean Algebras
The axioms for Boolean algebras are the same as the axioms for basic logic
(standard/Huntington/Robbins/Sheffer/Wolfram).
There is a choice between compactness and obviousness.
We obtained the axioms by starting with basic logic and trying to find
axiomatizations.
We obtain Boolean algebras by trying to find all objects that conform to
these axioms.
The Magic Garden of George B.
(The Magic Garden of George B. And Other Logic Puzzles, Raymond
Smullyan, Polimetrica, 2007)
- A very special garden: Flowers can change colors every day
(set of flowers F, set of days D, color of flower
a on day d: color(a, d))
- Each flower is either blue or
red for a whole day
(∀f∈F: ∀d∈D:
color(f,d)=red∨color(f,d)=blue)
- For any flowers a and b, there is a flower
c that is red on all and
only those days on which a and b are both blue.
(∀a, b∈F: ∃c∈F:
∀d∈D:
color(a,d)=color(b,d)=blue ↔
color(c,d)=red)
- Any two different flowers a and b have different
colors on at least one day.
(∀a, b∈F:
∃d∈D:
a≠b→color(a,d)≠color(b,d))
- We know that the garden has more than 200 but less than 500 flowers.
(200<|F|<500)
- Question 1: How many flowers does the garden have?
- Question 2: What is the minimum of days that the flowers bloom?
- Question 3: Who is George B.?
How to Solve the Magic Garden Puzzle
- Let red stand for 1, blue for 0
- Let a day be a bit position
- Let a flower be a bit combination
- "there is a flower c that is red on all and only those days on which
a and b are both blue" means that bitwise NOR is always
defined
- Because any logical operation can be defined based on bitwise NOR, all
logical operations are defined
- The flowers therefore form a Boolean algebra:
- B is F (set of
flowers)
- 0 is a flower that is
always(*) blue
- 1 is a flower that is
always(*) red (*assuming
|F|=2|D|)
- ⫬a is the flower that
is red on those days where a is
blue and blue on those days where a is red
- △ is the flower that is red only on those days
where both its operands are red, otherwise
blue
- ▽ is the flower that is red whenever one or more of its operands are red, otherwise
blue
- The (partial) order relation is: a flower a is smaller or
equal than a flower b if on all days
where b is blue, a is also blue
- Hasse diagram for 32 flowers: BAgarden.svg
- The size of a finite Boolean algebra is 2n, hence
200<|F|<500 → |F|=256=28;
min(|D|)=8
- Question 1: How many flowers does the garden have? 256
- Question 2: What is the minimum of days that the flowers bloom? 8 days (dimension of this Boolean algebra)
- Question 3: Who is George B.? George Boole, after
which Boolean algebra is named
This Week's Homework
Deadline: January 10, 2017 (Thursday), 19:00.
Format: A4 single page (using both sides is okay; NO cover
page), easily readable handwriting (NO printouts), name (kanji
and kana) and student number at the top right
Where to submit: Box in front of room O-529 (building O, 5th floor)
Draw the Hasse diagram of a Boolean algebra of dimension 4 (16 elements).
There will be a deduction if you use the same elements of the group as another
student.
Additional Homework (no need to submit): Prepare for final exam using past
exams.
Glossary
- coverage
- 試験範囲
- group isomorphism
- 群同形
- isomorphic
- 同形の、同型の
- Abelian group
- アベル群、可換群
- semigroup
- 半群
- ring
- 環 (かん)
- polynomial
- 多項式
- field
- 体 (たい)
- lattice
- 束 (そく)
- Boolean algebra
- ブール代数
- zero element
- 零元
- unary operation
- 単項演算
- binary operation
- 二項演算
- bitwise operation
- ビット毎演算
- bitwise not
- ビット毎否定
- bitwise and
- ビット毎論理積
- bitwise or
- ビット毎論理和
- bitwise xor (exclusive or)
- ビット毎排他的又は
- coprime
- 互いに素
- greatest common divisor
- 最大公約数
- least common multiple
- 最小公倍数
- coprime
- 互いに素
- pairwise coprime
- 対ごとに素、どの二つも互いに素
- n-dimensional
- n 次元 (の)
- cube
- 立方体
- supremum (least upper bound)
- 上限、最小上界
- infimum (greatest lower bound)
- 下限、最大下界