Difficult(?) convergence problem

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In summary, the conversation is about proving the convergence of a series involving a constant, u_n, and cos(n\vartheta +a), where a is an arbitrary constant. The attempts at using Cauchy's root test, Dirichlet's test, and Abel's test were unsuccessful due to not meeting certain conditions. However, it is pointed out that the monotonic series u_n can be used to prove convergence, as it is bounded by a constant and has alternating terms.
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Atropos
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Homework Statement




Show that if [tex]\vartheta[/tex] is any constant not equal to 0 or a multiple of 2[tex]\pi[/tex], and if u[tex]_{0}[/tex], u[tex]_{1}[/tex], u[tex]_{2}[/tex] is a series that converges monotonically to 0, then the series [tex]\sum u_{n} cos(n\vartheta +a)[/tex] is also convergent, where a is an arbitrary constant.



Homework Equations





The Attempt at a Solution



I have attempted to show convergence via Cauchy's root test, Dirichlet's test, and Abel's test. All 3 of these attempts were unsucessful as one or more conditions required for the tests was not met.
 
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  • #2
I have attempted to show convergence via Cauchy's root test, Dirichlet's test, and Abel's test. All 3 of these attempts were unsucessful as one or more conditions required for the tests was not met.

What are the objections to the Dirichlet test?

I'd think that [tex] | \sum_{i=1}^n (cos(n\vartheta)| [/tex] would be bounded since a run of positive terms is followed by a run of negative terms. Likewise for [tex] sin(n\vartheta) [/tex].

What's the longest run of postive terms that can happen? For [itex] \vartheta > 0 [/itex] there is some smallest m so [itex] M \vartheta > 2 \pi [/itex] Intuitively, I'd think [itex]2M [/itex] would be plenty big to bound it.
 
  • #3
Wow, I'm an idiot.

I was so hung up on the cosine part of the sum that I completely forgot about the monotonic series u_n. I was only paying attention to the fact that cosine was sinusoidal ad therefore f_n>f_n+1>0 couldn't apply.

...but it does apply to u_n.

Thank you for pointing that out. :biggrin:
 

Related to Difficult(?) convergence problem

1. What is a "difficult convergence problem" in science?

A difficult convergence problem refers to a situation where a scientific model or theory does not accurately predict or explain a phenomenon. This can occur due to a lack of data, limitations in the model itself, or other underlying factors that are not yet fully understood.

2. How do scientists approach a difficult convergence problem?

Scientists approach a difficult convergence problem by gathering more data, analyzing the existing data more closely, and modifying the model or theory to better fit the observed phenomenon. They may also collaborate with other scientists and utilize different tools and techniques to gain a better understanding of the problem.

3. What are some common examples of difficult convergence problems?

Some common examples of difficult convergence problems include climate change predictions, the behavior of subatomic particles, and the development of new medical treatments. These are complex issues that involve multiple variables and can be difficult to accurately predict or explain.

4. How do scientists determine if a difficult convergence problem has been solved?

Scientists determine if a difficult convergence problem has been solved by comparing the predictions of the modified model or theory to new data and observations. If the new predictions align with the observed phenomenon, then the problem may be considered solved. However, further research and testing may be necessary to confirm the solution.

5. Can a difficult convergence problem ever truly be solved?

It is possible for a difficult convergence problem to be solved, but it is also possible for new data or discoveries to challenge the existing solution. Science is an ongoing process of discovery and refinement, so even if a problem is deemed solved, it may be revisited in the future as new evidence emerges.

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