Proving convergence of 1/log(n)

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In summary, to prove the convergence of the series Ʃ 1/(n(log(n))^p) where p>1, you can use either the integral test or Cauchy's Condensation test. Additionally, the sum from any fixed number to infinity will also converge if the sum from 1 to infinity converges.
  • #1
hivesaeed4
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Has anybody got any idea as to how to prove that Ʃ 1/(n(log(n))^p) converges? (where p>1)
 
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  • #2
0 < log(n) < n for n>3
 
  • #3
hivesaeed4 said:
Has anybody got any idea as to how to prove that Ʃ 1/(n(log(n))^p) converges? (where p>1)


First way, the integral test: [itex]\int_2^\inf \frac{1}{x\log^px} dx=\frac{\log^{1-p}(x)}{1-p}|_2^\inf \rightarrow \frac{log^{1-p}(2)}{p-1}[/itex] .

Second way, Cauchy's Condensation test: taking [itex]n=2^k[/itex] , the series's general term is [itex]\frac{1}{2^kk^p\log^p(2)}[/itex] , so multiplying this by [itex]2^k[/itex] we get [itex]\frac{1}{k^p\log^p(2)}[/itex] , which is a multiple of the series of [itex]\frac{1}{k^p}[/itex] , which we know converges for [itex]p>1[/itex] .

DonAntonio
 
  • #4
DonAntonio said:
First way, the integral test: [itex]\int_2^\inf \frac{1}{x\log^px} dx=\frac{\log^{1-p}(x)}{1-p}|_2^\inf \rightarrow \frac{log^{1-p}(2)}{p-1}[/itex] .

Second way, Cauchy's Condensation test: taking [itex]n=2^k[/itex] , the series's general term is [itex]\frac{1}{2^kk^p\log^p(2)}[/itex] , so multiplying this by [itex]2^k[/itex] we get [itex]\frac{1}{k^p\log^p(2)}[/itex] , which is a multiple of the series of [itex]\frac{1}{k^p}[/itex] , which we know converges for [itex]p>1[/itex] .

DonAntonio

Thing is I've got to prove determine it's convergence from 1 to infinity.
 
  • #5
Just to clarify, the previous message was supposed to be:
Thing is I've got to determine it's convergence from 1 to infinity.
 
  • #6
If the sum starts at 1, you have a problem because log(1)=0
 
  • #7
The sum from 1 to any fixed number will always converge (unless you divide by zero).
Therefore, if the sum from any fixed number to infinity converges, then the sum from 1 to infinity converges.

You can choose any fixed number you like. I chose 3 because 0<log(n) < n for all n>=3.

You can choose 11 if your log is base 10 rather than natural, or because, you know, usual amps only go up to 10, but yours goes all the way up to 11.

The sum from 3 to infinity of your series is smaller than the sum from 3 to infinity over 1/n^(p+1), which is smaller than 1/n^2 which we know converges.
 

1. What is the definition of convergence in mathematics?

Convergence in mathematics refers to the behavior of a sequence or series as its terms approach a specific limit. In other words, it is the process of approaching a fixed value or point as the number of iterations increases.

2. Why is proving convergence of 1/log(n) important in mathematics?

Proving convergence of 1/log(n) is important in mathematics as it helps in understanding the behavior of the logarithmic function and its relationship to other mathematical concepts. It also allows for the evaluation of the limit of 1/log(n) as n approaches infinity, which can have applications in various areas of mathematics and science.

3. How is convergence of 1/log(n) proven?

To prove convergence of 1/log(n), one can use the Limit Comparison Test or the Integral Test. These tests compare the given series to a known series with a known convergence behavior, allowing for the determination of the convergence or divergence of the series in question.

4. What is the intuition behind the convergence of 1/log(n)?

The intuition behind the convergence of 1/log(n) lies in the fact that the logarithmic function grows very slowly, and as n approaches infinity, the value of 1/log(n) approaches 0. This can also be visualized by plotting the function, where it can be seen that as n increases, the curve approaches the x-axis.

5. Are there any real-world applications of proving convergence of 1/log(n)?

Yes, there are several real-world applications of proving the convergence of 1/log(n), such as in the analysis of algorithms, population growth models, and in the study of computational complexity. It can also be used in various scientific fields, such as physics, to understand the behavior of certain phenomena as they approach a limit.

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