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CompSci 102 Discrete Math for Computer Science March 27, 2012 Prof. Rodger Lecture adapted from Bruce Maggs/Lecture developed at Carnegie Mellon, primarily by Prof. Steven Rudich

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Announcements More on Counting

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X1 X1 X2 X2 + + X3 X3 Counting III

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Power Series Representation (1+X) n = n k XkXk k = 0 n n k XkXk = “Product form” or “Generating form” “Power Series” or “Taylor Series” Expansion For k>n, n k = 0

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By playing these two representations against each other we obtain a new representation of a previous insight: (1+X) n = n k XkXk k = 0 n Let x = 1, n k k = 0 n 2 n = The number of subsets of an n-element set

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Example = 16 Number of subsets of size 0, size 1, size 2, size 3, and size 4

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By varying x, we can discover new identities: (1+X) n = n k XkXk k = 0 n Let x = -1, n k k = 0 n 0 = (-1) k Equivalently, n k k even n n k k odd n =

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The number of subsets with even size is the same as the number of subsets with odd size

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Proofs that work by manipulating algebraic forms are called “algebraic” arguments. Proofs that build a bijection are called “combinatorial” arguments (1+X) n = n k XkXk k = 0 n

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Let O n be the set of binary strings of length n with an odd number of ones. Let E n be the set of binary strings of length n with an even number of ones. We gave an algebraic proof that O n = E n n k k even n n k k odd n =

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A Combinatorial Proof Let O n be the set of binary strings of length n with an odd number of ones Let E n be the set of binary strings of length n with an even number of ones A combinatorial proof must construct a bijection between O n and E n

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An Attempt at a Bijection Let f n be the function that takes an n-bit string and flips all its bits f n is clearly a one-to- one and onto function...but do even n work? In f 6 we have for odd n. E.g. in f 7 we have: Uh oh. Complementing maps evens to evens!

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A Correspondence That Works for all n Let f n be the function that takes an n-bit string and flips only the first bit. For example,

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The binomial coefficients have so many representations that many fundamental mathematical identities emerge… (1+X) n = n k XkXk k = 0 n

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The Binomial Formula (1+X) 0 = (1+X) 1 = (1+X) 2 = (1+X) 3 = (1+X) 4 = X 1 + 2X + 1X X + 3X 2 + 1X X + 6X 2 + 4X 3 + 1X 4 Pascal’s Triangle: k th row are coefficients of (1+X) k Inductive definition of k th entry of n th row: Pascal(n,0) = Pascal (n,n) = 1; Pascal(n,k) = Pascal(n-1,k-1) + Pascal(n-1,k)

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“Pascal’s Triangle” 0 0 = = = 1 Al-Karaji, Baghdad Chu Shin-Chieh 1303 Blaise Pascal = = = 1

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Pascal’s Triangle “It is extraordinary how fertile in properties the triangle is. Everyone can try his hand”

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Summing the Rows n k k = 0 n 2 n = = 1 = 2 = 4 = 8 = 16 = 32 = 64

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= Odds and Evens

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Summing on 1 st Avenue i = 1 n i 1 = n i n+1 2 =

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Summing on k th Avenue i = k n i k n+1 k+1 =

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Fibonacci Numbers = 2 = 3 = 5 = 8 = 13

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Sums of Squares

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Al-Karaji Squares +2 = 1 = 4 = 9 = 16 = 25 = 36

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Pascal Mod 2

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All these properties can be proved inductively and algebraically. We will give combinatorial proofs using the Manhattan block walking representation of binomial coefficients

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How many shortest routes from A to B? B A 10 5

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Manhattan j th streetk th avenue There areshortest routes from (0,0) to (j,k) j+k k

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Manhattan Example j th streetk th avenue j+k k 2cd street, 3 rd ave 5 3 = 6 points on that row, this is the 4 th binomial coefficient of 6 items

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Manhattan Level nk th avenue There areshortest routes from (0,0) to (n-k,k) n k

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Manhattan Level nk th avenue There are shortest routes from (0,0) to n k level n and k th avenue 4 3 Example: Level 4, 3 rd avenue

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Level nk th avenue

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Level nk th avenue n k n-1 k-1 n-1 k = + +

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Level nk th avenue n n n k k = 0 n 2 = Example: Show for n=3

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= =

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Level nk th avenue n+1 k+1 i k i = k n = Show for k=2, n=5

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= = 20

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Vector Programs Let’s define a (parallel) programming language called VECTOR that operates on possibly infinite vectors of numbers. Each variable V ! can be thought of as:

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Vector Programs Let k stand for a scalar constant will stand for the vector = V ! + T ! means to add the vectors position-wise + =

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Vector Programs RIGHT(V ! ) means to shift every number in V ! one position to the right and to place a 0 in position 0 RIGHT( ) =

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Vector Programs Example: V ! := ; V ! := RIGHT(V ! ) + ; V ! = Store: V ! =

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Vector Programs Example: V ! := ; Loop n times V ! := V ! + RIGHT(V ! ); V ! = n th row of Pascal’s triangle Store: V ! =

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X1 X1 X2 X2 + + X3 X3 Vector programs can be implemented by polynomials!

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Programs Polynomials The vector V ! = will be represented by the polynomial: i = 0 aiXiaiXi P V =

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Formal Power Series The vector V ! = will be represented by the formal power series: i = 0 aiXiaiXi P V =

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i = 0 aiXiaiXi P V = V ! = is represented by 0 k V ! + T ! is represented by(P V + P T ) RIGHT(V ! ) is represented by(P V X)

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Vector Programs Example: V ! := ; Loop n times V ! := V ! + RIGHT(V ! ); V ! = n th row of Pascal’s triangle P V := 1; P V := P V + P V X;

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Vector Programs Example: V ! := ; Loop n times V ! := V ! + RIGHT(V ! ); V ! = n th row of Pascal’s triangle P V := 1; P V := P V (1+X);

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Vector Programs Example: V ! := ; Loop n times V ! := V ! + RIGHT(V ! ); V ! = n th row of Pascal’s triangle P V = (1+ X) n

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Polynomials count Binomial formula Combinatorial proofs of binomial identities Vector programs Here’s What You Need to Know…

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