Knights to Infinity

A knight is placed at the center of an infinitely large chess board. For large n , n, the number of squares on which the knight can be after exactly n n moves is asymptotically a n b a \cdot n^b for real numbers a a and b . b. Find a + b . a+b.

Note: A chess knight moves in an "L" shape either 1 square vertically and 2 squares horizontally or 2 squares vertically and 1 square horizontally, as indicated by the stars above.


The answer is 9.

This section requires Javascript.
You are seeing this because something didn't load right. We suggest you, (a) try refreshing the page, (b) enabling javascript if it is disabled on your browser and, finally, (c) loading the non-javascript version of this page . We're sorry about the hassle.

5 solutions

Mark Hennings
Jul 20, 2017

According to OEIS , the number of squares a ( n ) a(n) that can be reached by a knight in n n or fewer moves is a ( n ) = 5 6 n + 14 n 2 n 4 a(n) \; = \; 5 - 6n + 14n^2 \hspace{1cm} n \ge 4 There is a slight adjustment to this formula for n = 0 , 1 , 2 , 3 n=0,1,2,3 . Thus the number of squares that can be reached in precisely n n moves is b ( n ) = a ( n ) a ( n 1 ) = 14 ( 2 n 1 ) 6 = 28 n 20 n 5 b(n) \; = \; a(n) - a(n-1) \; = \ 14(2n-1) - 6 \; = \; 28n - 20 \hspace{1cm} n \ge 5 The number of squares that can be reached after n n moves is equal to c ( n ) = j = 0 1 2 n b ( n 2 j ) c(n) \; =\; \sum_{j=0}^{\lfloor \tfrac12n\rfloor} b(n-2j) To see this, any square that takes exactly n 2 j n - 2j moves to reach can be reached after n n moves; take n 2 j n-2j moves to get there, and then jump to a square and back again a total of j j times. Obviously, squares that take exactly n 2 j 1 n - 2j-1 moves to reach cannot be reached in n n moves, since they will be of the wrong colour. Thus c ( n ) j = 0 1 2 n ( 28 n 56 j 20 ) 28 n 1 2 n 28 1 2 n ( 1 2 n + 1 ) 20 1 2 n 7 n 2 n c(n) \; \sim \; \sum_{j=0}^{\lfloor \tfrac12n\rfloor} (28n-56j - 20) \; \sim \; 28n\lfloor \tfrac12n\rfloor - 28\lfloor \tfrac12n\rfloor\big(\lfloor \tfrac12n \rfloor + 1\big) - 20\lfloor \tfrac12n \rfloor \; \sim \; 7n^2 \hspace{2cm} n \to \infty making the answer 7 + 2 = 9 7+2=\boxed{9} .


To save quoting from OEIS, here is a direct proof of the formula for b ( n ) b(n) . After playing around a bit, a clear pattern emerges as to which squares can be covered when.

This is the general pattern. The black squares are those that can be reached in fewer than n n moves, and the red squares are the ones that can be reached in n n moves, but not fewer than n n , (so that b ( n ) b(n) is the number of red squares. This pattern occurs for all n 5 n \ge 5 . The overall pattern is a "fringed octagon", where the outermost fringe describes an octagon with n + 1 n+1 red squares (interspersed with gaps) on each horizontal and vertical side, and n + 1 n+1 red squares on each diagonal side. The above picture is the pattern for n = 15 n=15 .

It is easy to see that any of the white squares within the outer red/white fringe can be reached from one of the red squares in one knight's move. In the move from the pattern for n n to the pattern for n + 1 n+1 , all the red squares in the outer fringe will turn black, and all the white squares in the outer fringe will turn red. In addition, it is clear that knight's moves from the red squares outwards will create an additional red/white fringe in the n + 1 n+1 pattern as required. That this pattern is correct for all n 5 n \ge 5 is therefore shown by induction.

In this pattern, counting the columns from left to right:

  • there are 4 4 columns containing n + 1 , n + 2 , n + 3 , n + 4 n+1,n+2,n+3,n+4 red squares each,
  • then there are n 3 n-3 columns each containing 6 6 red squares,
  • then there are 2 n 1 2n-1 columns each containing 4 4 red squares,
  • then there are n 3 n-3 columns each containing 6 6 red squares,
  • finally there are 4 4 columns containing n + 4 , n + 3 , n + 2 , n + 1 n+4,n+3,n+2,n+1 red squares,

and so we deduce that b ( n ) = 2 [ ( n + 1 ) + ( n + 2 ) + ( n + 3 ) + ( n + 4 ) + 6 ( n 3 ) ] + 4 ( 2 n 1 ) = 28 n 20 n 5 . b(n) \; = \; 2\big[(n+1)+(n+2)+(n+3)+(n+4) + 6(n-3)\big] + 4(2n-1) \; = \; 28n - 20 \hspace{2cm} n \ge 5 \;. Direct calculation shows that b ( 1 ) = 8 b(1) = 8 , b ( 2 ) = 32 b(2) = 32 , b ( 3 ) = 68 b(3) = 68 and b ( 4 ) = 96 b(4) = 96 .

Eli Ross Staff
Jul 19, 2017

Note: This is not a solution (more of an asymptotic hack), and I'd encourage people to work out the problem in nicer ways (i.e., via induction ).

When a knight moves "optimally" away from its original square, it moves about 1 2 + 2 2 = 5 \sqrt{1^2+2^2} = \sqrt{5} units per move. When it moves "unoptimally" away (in a ~straight line) from its original square, it moves about 2 2 units per move (i.e., up-right followed by up-left).

The knight can then move around in this "blob" (something like a circle, but really closer to an octagon) that has radius at most 5 n \sqrt 5 n and at least 2 n . 2n. However, it can only move around to half of the squares, due to even/odd parity.

So, the number of square it can move to in n n moves is between 2 π n 2 6.28 n 2 2\pi n^2 \approx 6.28n^2 and 2.5 π n 2 7.85 n 2 . 2.5 \pi n^2 \approx 7.85 n^2. However, you can prove that the number of reachable squares should be quadratic in n n with integer coefficients, so the asymptotic behavior is 7 n 2 . 7n^2.

My proof now contains an inductive demonstration of the formula for b n b_n for n 5 n \ge 5 , so does not rely on OEIS any more!

Mark Hennings - 3 years, 10 months ago
Greg Norgard
Jul 26, 2017

Now fit an exponent to your curve. Low and behold 7*n^2 works pretty well.

You have only checked for n=1,2,...,100. Is this sufficient to conclude that the function is asymptotic to 7n^2?

Pi Han Goh - 3 years, 10 months ago

Log in to reply

If you consider the many options that were considered over the centuries before the Prime Number Theorem was proved, the answer is "no". Many different functions can have similar behaviour for small n n , and yet very different asymptotic behaviour as n n\to\infty . And 100 100 is very small.

Mark Hennings - 3 years, 10 months ago
Prayas Rautray
Jul 26, 2017

Taking n=1, we get that the knight can go to 8 different places.
Taking n=2,we get that the knight can go to 16 different places.
This you can know by drawing the diagrams. .
So, a 1 b = 8 a 1^{b}=8 So, a = 8 a=8 .
Now, taking n=2, a=8, 8 × 2 b = 16 8\times 2^{b}=16 So, b = 1 b=1 Now a+b=8+1=9



But the asymptotic (large n n ) behaviour is 7 n 2 7n^2 , not 8 n 8n . You cannot determine behaviour for large n n by looking at what happens when n = 1 , 2 n=1,2 .

Mark Hennings - 3 years, 10 months ago
Aviel Livay
Jul 30, 2017

You can see in the picture how it looks for n = 10 n=10

the yellow line includes the pattern that we get for n = 8 n=8

summing top to bottom we get: s u m ( 10 ) s u m ( 8 ) = 10 + 11 + 12 + 13 + 6 6 + 17 4 + 6 6 + 13 + 12 + 11 + 10 = 232 sum(10)-sum(8)=10+11+12+13+6*6+17*4+6*6+13+12+11+10=232

or in the more general case

s u m ( n ) s u m ( n 2 ) = 2 [ 4 n + 6 + ( n 4 ) 6 ] + ( 2 n 3 ) 4 = 28 n 48 sum(n)-sum(n-2)=2*[4n+6+(n-4)*6] + (2n-3)*4= 28n - 48

which goes like 28 n 28n as n goes to infinity.

So the difference is a linear function of n.

It implies that s u m ( n ) = a n 2 + b n + c sum(n)=a*n^2+b*n+c As n goes to infinity this sum(n) goes like a n 2 a*n^2

now we know that a n 2 a ( n 2 ) 2 = 28 n a*n^2-a*(n-2)^2=28n

Which means

4 a n 4 a = 28 n 4an-4a=28n

a ( 4 n 4 ) = 28 n a(4n-4)=28n

a = 7 a=7

it means that s u m ( n ) sum(n) goes like 7 n 2 7*n^2 which means a = 7 a=7 and b = 2 b = 2 or in other words 9 \boxed{9}

0 pending reports

×

Problem Loading...

Note Loading...

Set Loading...