R i r u . A cell of R i r u , at the end of each day, fragments into r daughter cells, where 1 ≤ r ≤ 4 . The probability of r taking a certain numerical value, is directly proportional to that value itself. Al the beginning of day 1 , one cell of R i r u was present in an isolated habitat, with plenty of resources. Find the average R i r u population at the beginning of day 2 1 .
Let me introduce you to the unicellular organism code-named as:
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That was good. I did not know that we could solve it using a generating function(Not sure if that's the term). Thanks for posting a well explained solution. I found it difficult to get my idea across.
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Yes it is also called that :) I too learnt a lot of tricks while attempting to solve this problem and most importantly was surprised when the answer came out so simple
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Yeah, me too. Actually, when I thought it up, i felt that it might be difficult. Understood why they call it an "exponential growth". It remains an exponential increase even if we allow a small enough probability for dying.
I solved something this way, unfortunate enough, I missed the entry of right answer :
Given that the probabilities are proportional to values in the question, I calculated the expectation and raised it to 20 (As 1st day was lonely for Riru)
E x p ( X ) = 1 0 1 × 1 + 1 0 2 × 2 + 1 0 3 × 3 + 1 0 4 × 4 = 3
3 2 0 = 3 4 8 6 7 8 4 4 0 1
Let's see here:
At the beginning of day 1, there is one cell. Let's say the expected(average) value of population on the n t h day is E [ n ] .
At the start of the second day, we have a few daughter cells, which behave EXACTLY the same way as the parent. That is, E [ ] functions for each daughter is same as the E [ ] function of the parent, but shifted by one day.
Hence:
E [ n ] = ∑ r = 1 4 ( 2 4 ) ( 5 ) r 2 E [ n − 1 ] ⇒ E [ n ] = ( 3 9 ) E [ n − 1 ] ⇒ E [ n ] = ( 3 ) n − 1 E [ 1 ] = ( 3 ) n − 1
Putting n = 2 1 yields answer as 3 2 0 = 3 4 8 6 7 8 4 4 0 1
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Beautiful problem, It can simply be done by symmetry telling that in first day , the expected number of cells on the second day is 3,
After that, each cell feels the same driving force and hence tends to divide in 3 parts, successively and hence answer is 3 2 0 , but Raghav has already shown this way
But for the sake of fun, i want to show a more sophisticated method
Now each cell has 4 choices ,
1) Not divide with probability 1/10
2) divide into two parts with probability 2/10
3) Divide into 3 parts with probability 3/10
4) Divide into 4 parts with probability 4/10
Since the possibilities are not equally likely, so let us rather think of this in this manner,
There is 1 way to not divide at all, 2 ways to divide into two cells, and 3 ways to divide into 3 cells and 4 ways to divide into 4 cells
so there are 10 paths for each cell, some paths having identical results,
Let them be represented by the coefficient of x r and thus the choice of each cell can be represented as
( x + 2 x 2 + 3 x 3 + 4 x 4 )
and if in some day, there are n cells,
Then the number of possibilities of getting p cells is the coefficient of x p in
( x + 2 x 2 + 3 x 3 + 4 x 4 ) n
Now what we want is the expectation of next day,
and expectation is defined as as the sum of probabilities with their respective values
or
since minimum number of cells next day is n and max is 4n
So the expectation is
P n n + P n + 1 ( n + 1 ) + . . . . P 4 n ( 4 n )
To find that let ( x + 2 x 2 + 3 x 3 + 4 x 4 ) n = a x + b x 2 + c x 3 . . . . .
since the coefficients simply represent the number of ways of the particular exponent (cell no.)
So let us differentiate it to get
a + 2 b x + 3 c x 2 . . . . = ( n ( x + 2 x 2 + 3 x 3 + 4 x 4 ) n − 1 ) ( 1 + 4 x + 9 x 2 + 1 6 x 3 )
Now putting x=1 we get
E*(total number of possiblities) = n 1 0 n − 1 ( 3 0 )
and each cell has 10 choices, so total number of possibilties is simply 1 0 n
so E = 3n
where n is the number of cells in the previous day, and E is the expected number of cells the next day,
This recurrence is simply a GP
and initially there was just one cell
so after 20 days
E 2 0 = 3 2 0
Which is the answer,
I know the method is really big and unnecessary, but at the same time its fun