Lucas Theorem – Proof and Applications

forthright48 on November 16, 2018

Problem

Given non-negative integers $N$, $K$ and a prime number $P$, find the value of:

$$\binom{N}{K} \mod P$$

Sounds like a simple problem right? There are several ways to solve the problem, depending on the constraints of $N$, $K$, and $P$.

Direct: If $N$, $K$ are really small, less than $12$, then we can calculate $\binom{N}{K}$ directly using formula $\frac{N!}{K! \times (N-K)!}$ and find the mod $P$ value. Not gonna work when the values are around $1000$.
DP: If they are slightly bigger but still around $1000$, then we can use dynamic programming to find the result, using the recurrence: $\binom{N}{K} = \binom{N-1}{K} + \binom{N-1}{K-1}$. Not going to work if values are around $10^5$.
Modular Inverse: If $P$ is a large prime, say $10^9+7$, then using modular inverse and some precalculation we can still calculate $\frac{N!}{K! \times (N-K)!}$. But still, we will need to run $O(N)$ loop to calculate $N!$. Not going to work if $N$ is too large. Also, if $P$ is small then there won’t be any modular inverse since $P$ will not be coprime with denominator anymore.

So what do we do when $N$ and $K$ are large (let’s say around $10^9$) and prime $P$ is small, let’s say $37$. Is it still possible?

Of course. We use Lucas Theorem.

Stars and Bars Theorem

forthright48 on September 23, 2018

Problem

Given K variables, $a_1, a_2, a_3 \dots a_K$ and a value $N$, how many ways can we write $a_1 + a_2 + a_3 \dots a_K = N$, where $a_1, a_2, a_3 \dots a_K$ are non-negative integers?

For example, if $K = 3$ and $N=2$, there are 6 solutions.

Application of Prufer Code: Random Tree Generation, Cayley’s Formula and Building Tree from Degree Count

forthright48 on February 8, 2018

On the last post (Prufer Code: Linear Representation of a Labeled Tree), we discussed how to convert a labeled tree into Prufer Code and vice versa. On this post, we will look into some of its applications in problem-solving.

Generating Random Tree

This one is the simplest. Though problem-solving may not require generating random trees, problem setting might. In order to generate a random tree with $N$ nodes, all we need to do is generate a Prufer Code of length $N-2$ with each element being in the range of $1$ to $N$. Next, we just convert the Prufer Code into a tree.

The randomness of the tree depends on the randomness of the sequence generated. Using rand() function is not good since it’s not truly random. How we can generate a random sequence requires a blog post of its own. Maybe I will write a post on it in near future.