Method of Differences

Suppose we are given several consecutive integer points at which a polynomial is evaluated. What information does this tell us about the polynomial? To answer this question, we create the following table, known as the Difference Table:

nf(n)D1(n)D2(n)D3(n)123 \begin{array} {l l l l l l l} n & f(n) & D_1(n) & D_2(n) & D_3(n) & \ldots \\ 1 & \\ 2 & \\ 3 & \\ \vdots \\ \end{array}

In the first column, we fill out the points at which the polynomial is evaluated (which I will assume is 1,2,31, 2, 3\ldots.
In the second column, we fill out the corresponding values of the polynomial at those points.
In the third column, we calculate the difference between two entries in the previous column. This is known as the first difference and is given by D1(n)=f(n+1)f(n) D_1 (n) = f(n+1) - f(n) .
In the fourth column, we calculate the difference between two entries in the previous column. This is known as the second difference and is given by D2(n)=D1(n+1)D1(n) D_2 (n) = D_1 (n+1) - D_1 (n) .
We continue building out subsequent columns of the table in this way, with Dk+1(n)=Dk(n+1)Dk(n) D_{k+1} (n) = D_k (n+1) - D_k (n) .

For example, if we are given that f(n) f(n) is a quadratic polynomial satisfying

f(1)=4,f(2)=3,f(3)=4,f(4)=7 and f(5)=12, f(1) = 4, f(2) = 3 , f(3) = 4, f(4) = 7 \mbox{ and } f(5) = 12,

then the difference table is as follows:

nf(n)D1(n)D2(n)D3(n)14120231203432475512 \begin{array} {l l l l l l l} n & f(n) & D_1(n) & D_2(n) & D_3(n) & \ldots \\ 1 & 4 & -1 & 2 & 0 \\ 2 & 3 & 1 & 2 & 0\\ 3 & 4 & 3 & 2\\ 4 & 7 & 5 \\ 5 & 12 & \\ \vdots \\ \end{array}

Note that since we are not given f(6)f(6) , we are unable to calculate D1(5),D2(4),D3(3)D_1(5), D_2(4), D_3(3) or D4(2)D_4(2). Now, there isn't (yet) any reason why this table would ever end; if we are given infinitely many values, we can always calculate the differences of terms. However, here is an interesting fact.

If a polynomial f(x)f(x) has degree kk, then the kkth difference is constant.
Furthermore, the kkth difference is equal to k!k! times the leading coefficient of f(x)f(x) .

In the above example, we see that D2(1)=D2(2)=D2(3)=2 D_2 (1) = D_2(2) = D_2( 3) = 2 . Since f(x)f(x) is a quadratic polynomial, the above fact tells us that D2(n)=2 D_2(n) = 2 for all nn, and this allows us to fill in other entries in the table. We get that D2(4)=2 D_2(4) = 2 so D1(5)=7 D_1 (5) = 7 and hence f(6)=19f(6) = 19 ! These values are previously unknown to us, but the difference table allows us to calculate them without knowing the polynomial f(x)f(x)!

How do we prove this interesting fact? Let's consider a general polynomial of degree kk. We have

f(n)=aknk+ak1nk1++a1n+a0. f(n) = a_k n^k + a_{k-1} n^{k-1} + \ldots + a_1 n + a_0.

What is the value of D1(n) D_1(n) ? By definition, we have

D1(n)=f(n+1)f(n)=i=1kai[(n+1)ini] D_1(n) = f(n+1) - f(n) = \sum_{i=1}^k a_i [(n+1)^i - n^i]

By the binomial theorem, we have

(n+1)ini=(i1)ni1+(i2)ni2++(ii)n1+(ii)n0, (n+1)^{i} - n^i = {i \choose 1} n^{i-1} + {i \choose 2} n^{i-2} + \ldots + {i \choose i} n^1 + {i \choose i } n^0,

implying that there are no terms of degree nkn^k in D1(n)D_1(n) . Furthermore, the coefficient of nk1 n^{k-1} comes solely from the term ak[(n+1)knk]a_k [(n+1)^k - n^k] , and is equal to kak k a_k .

We may likewise continue by induction to consider the second difference, third difference, etc. Each time, we see that the degree of the polynomial decreases by 1. Hence, by the time we get to the kkth difference, it is a polynomial of degree 0. Since the only polynomials of degree 0 are the constants, this implies Dk(n)D_k(n) is a constant polynomial.

What happens to the leading coefficient at each step? We see that it gets multiplied by the degree of the (current) polynomial. Since the degree decreases by 1 at each step, we see that it gets multiplied by k×(k1)××2×1=k! k \times (k-1) \times \ldots \times 2 \times 1 = k! . Hence, we have Dk=ak×k! D_k = a_k \times k! , or that ak=Dkk! a_k = \frac{D_k} { k!} .

Worked Examples

1. Construct the difference table for the function fk(n)=(n1)×(n2)××(nk) f_k(n) = (n-1) \times (n-2) \times \ldots \times (n-k) for n=1 n =1 to k+1 k+1 . Note that fk(n)f_k(n) is a polynomial of degree kk.

Solution: This is a specially chosen function. We easily see that:

f(i)={0i=1 to kk!i=k+1. f(i) = \begin{cases} 0 & i = 1 \mbox{ to } k \\ k! & i = k+1 \\ \end{cases} .

This allows us to easily calculate the first difference column as:

D1(i)={0i=1 to k1k!i=k. D_1(i) = \begin{cases} 0 & i = 1 \mbox{ to } k-1 \\ k! & i = k \\ \end{cases} .

Similarly, for the jjth difference column, we have that

Dj(i)={0i=1 to kjk!i=kj+1. D_j (i) = \begin{cases} 0 & i = 1 \mbox{ to } k-j \\ k! & i = k-j+1 \\ \end{cases} .

(*) Show that if f(n)f(n) is a polynomial of degree kk, then f(n)=f(1)+i=1kDi(1)i!×fi(n). f(n) = f(1) + \sum_{i=1}^k \frac{D_i (1)}{i!} \times f_i (n) .

In particular, the quadratic polynomial ff in the write up above satisfying f(1)=4,f(2)=3,f(3)=4,f(4)=7 f(1) = 4, f(2) = 3 , f(3) = 4, f(4) = 7 and f(5)=12f(5) = 12 is given by f(n)=n24n+7f(n) = n^2 - 4n +7.

 

2. Prove that there is no polynomial (of finite degree) which satisfies f(n)=2n f(n) = 2^n for all positive integers.

Solution: Construct the difference table for f(n)=2n f(n) = 2^n . Since D1(n)=f(n+1)f(n)=2n+12n=2n=f(n) D_1(n) = f(n+1) - f(n) = 2^{n+1} - 2^{n} = 2^{n}=f(n) , we see that D1D_1 is exactly equal to ff . This remains true for each kkth difference column, and hence there is no polynomial of degree kk that satisfies f(n)=2nf(n) = 2^n .

#Algebra #MethodOfDifferences #KeyTechniques #Olympiad

Note by Calvin Lin
7 years, 2 months ago

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Comments

@Calvin Lin Is this technique also called 'Synthetic Division'? Or is it different from it?

Satvik Golechha - 7 years ago

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@Satvik Golechha - Nope. Its different I guess. But unfortunately I'm not good at that one too :(

Krishna Ar - 7 years ago

Nope. Synthetic Division is just "Lazy man's long division for linear polynomials". The only thing that you save is writing out all the terms. If you don't understand Synthetic division, then just do long division.

Calvin Lin Staff - 7 years ago

Is there a typo in example 1? Should it be f(n)=f(1)+i=1kDi(1)i!×fi(n)f(n) = f(1) + \sum_{i=1}^k \frac{D_i(1)}{i!}\times f_i(n)

Raymond Tat - 6 years, 5 months ago

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Thanks! I've fixed it :)

Calvin Lin Staff - 6 years, 5 months ago

in the first since this information is provided that the polynomial is quadratic we can assume a general quadratic plug in the given values and solve for three variables.

Rishi Sharma - 6 years, 4 months ago

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Yes, that is certainly one possible approach. But what happens when there are many more equations? See Worked example 2, how would you prove that there is no polynomial which is equal to 2n 2^n on the positive integers?

Calvin Lin Staff - 6 years, 4 months ago

Can you help me? Cos It seems that I don't understand. please

Mark Anthony Seraspe - 6 years, 4 months ago

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What do you not understand? Which problem are you stuck at?

Calvin Lin Staff - 6 years, 4 months ago

@Calvin Lin I tried this method in solving This problem , but something went wrong. Any help please?

Hasan Kassim - 6 years, 10 months ago
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