Math Problem Statement

Question 3 For n ∈ N 0 n∈N 0 ​ let w ( n ) w(n) denote the number of 1 1s in the binary representation of n n. For example, w ( 9 )

2 w(9)=2, since $9$ is 1001 1001 in binary. Try to find a closed formula for g ( n ) g(n) in terms of n n and w ( n ) w(n). If you succeed, the following question will be very easy.

Let n

10000000000000011 n=10000000000000011 in binary notation. What is g ( n ) g(n)? Write your answer in binary!

0 / 1 point Incorrect 4. Question 4 Let n

1152921504606846987 n=1152921504606846987. If we compute ( n k ) m o d     2 ( k n ​ )mod2 for k

0 … 7 k=0…7, which sequence do we get?

Write your answer as a simple 0/1 string. For example, if your sequence is ( 1 , 0 , 1 , 0 , 1 , 0 , 1 , 0 ) (1,0,1,0,1,0,1,0), answer 10101010 10101010.

Solution

Let's break down and solve the questions one by one.

Question 3: Finding g(n)g(n)

Given:

  • nN0n \in \mathbb{N}_0
  • w(n)w(n) denotes the number of 1s in the binary representation of nn.

We need to find a closed formula for g(n)g(n) in terms of nn and w(n)w(n).

Let's analyze the problem by first understanding g(n)g(n). In many problems involving binary representations, a common pattern is counting specific bit configurations or analyzing parity.

For example, consider the function g(n)=n×2w(n)g(n) = n \times 2^{w(n)}. This function would combine nn with the number of 1s in its binary form. Let's now try to apply this and see what happens when we use a specific nn.

Given n=100000000000000112n = 10000000000000011_2 (in binary):

  1. Convert nn to decimal: n=216+21+20=65536+2+1=65539n = 2^{16} + 2^1 + 2^0 = 65536 + 2 + 1 = 65539

  2. Calculate w(n)w(n), the number of 1s in the binary representation: w(65539)=3w(65539) = 3

  3. Let's assume g(n)=n×2w(n)g(n) = n \times 2^{w(n)} as a possible formula. Substituting the values: g(65539)=65539×23=65539×8=524312g(65539) = 65539 \times 2^3 = 65539 \times 8 = 524312

  4. Convert 524312524312 back to binary: g(65539)=10000000000101010002g(65539) = 1000000000010101000_2

This would be the result, but it does not necessarily match any specific answer format expected. Thus, let's revisit the definition of g(n)g(n).

Understanding g(n)g(n)

Since we are asked to relate g(n)g(n) with w(n)w(n), consider another simpler function like g(n)=n×w(n)g(n) = n \times w(n). This will likely involve a modular reduction or additional operation. Let’s try to simplify:

Question 4: Sequence from Binomial Coefficients Modulo 2

Given n=1152921504606846987n = 1152921504606846987:

We need to calculate (nk)mod2\binom{n}{k} \mod 2 for k=0,1,2,,7k = 0, 1, 2, \ldots, 7.

Steps:

  1. Convert nn to binary: n=1152921504606846987=10000000000000000000000000000000112n = 1152921504606846987 = 1000000000000000000000000000000011_2

  2. For each kk, determine (nk)mod2\binom{n}{k} \mod 2:

    Use Lucas' theorem, which states: (nk)mod2=(niki)mod2\binom{n}{k} \mod 2 = \prod \binom{n_i}{k_i} \mod 2 where nin_i and kik_i are the binary digits of nn and kk, respectively.

  3. The sequence (nk)mod2\binom{n}{k} \mod 2 for k=0k = 0 to 77 corresponds to the binary digits of nn restricted to the first 3 digits (since the binomial coefficient of any bit higher than kk would cancel out):

    • For k=0k = 0, (n0)=1\binom{n}{0} = 1.
    • For k=1k = 1, (n1)=1\binom{n}{1} = 1 (if the least significant bit is 1).
    • Continue for all k=0k = 0 to 77.

The sequence is therefore: Sequence=11000000\text{Sequence} = 11000000

This sequence comes from the fact that nn has 1s in the first and second least significant positions.

Summary:

  • Question 3: The binary result was an attempt based on a function g(n)g(n) with the hypothesis that could be incorrect as it does not yield standard expected results.
  • Question 4: The correct answer sequence is 11000000.

Would you like to go through the steps in more detail or explore further examples?


Relative Questions:

  1. How can Lucas' theorem be generalized for other moduli?
  2. What are the properties of binary representations when considering bit manipulation?
  3. What would g(n)g(n) be if we modified the problem to use different weights?
  4. What happens if w(n)w(n) is a very large number, like in the case of very dense binary numbers?
  5. How does one efficiently compute large binomial coefficients modulo small primes?

Tip: Always try decomposing complex binary or modular problems using smaller, simpler examples to verify your hypotheses.

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Math Problem Analysis

Mathematical Concepts

Number Theory
Binary Representation
Combinatorics

Formulas

w(n): Number of 1s in the binary representation of n
g(n): Hypothetical function involving binary operations

Theorems

Lucas' Theorem

Suitable Grade Level

Grades 11-12