Does the series f_n(x)= x^n/1 + x^n converge on the interval [0,1]?

In summary: So it converges for all x in [0,1).In summary, the series f_n(x)= x^n/1 + x^n converges on the interval [0,1) and diverges for x=-1. It converges to 0 for |x| < 1, 1 for x=1, and 1 for x > 1.
  • #1
Pearce_09
74
0
[tex]f_n(x)= x^n/1 + x^n [/tex]

does this series converge on the interval [0,1]
Say if x = 1 then the series is < some epslon , where epslon is > 0
but if x = 1 then the value for [tex]f_n(x)[/tex] is constant for all n
but does this still mean the series converges.. even tho the series doesn't get smaller for large values of n...
if not then it doesn't converge?
 
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  • #2
read what you posted one more time... your answer is in there somewhere :wink:
 
  • #3
Pearce_09 said:
[tex]f_n(x)= x^n/1 + x^n [/tex]
does this series converge on the interval [0,1]
Say if x = 1 then the series is < some epslon , where epslon is > 0
but if x = 1 then the value for [tex]f_n(x)[/tex] is constant for all n
but does this still mean the series converges.. even tho the series doesn't get smaller for large values of n...
if not then it doesn't converge?
I assume you mean [itex]f_n(x)= \frac{x^n}{1+ x^n}[/itex] since otherwise (i.e. if you mean [itex]f_n(x)= 2x^n[/itex]) I see no reason for the "1". Also It's not clear whether you mean a "sequence" rather than "series" (which is an infinite sum) since you say "even tho the series doesn't get smaller for large values of n". A sequence doesn't have to "get smaller", just get closer to (or be) a number (an infinites series does not converge it the sequence does not go to 0). fn(0)= 0 for all n and the "constant" sequence 0 certainly converges to 0 (and the infinite sum is also 0!). fn(1)= 1 for all n so the sequence "converges" to 1 but that means that the infinite series [itex]\sum f_n(1)[/itex] does not converge. For x any number between 0 and 1, we can divide both numerator and denominator by xn to get [itex]\frac{1}{1+\frac{1}{x^n}}[/itex]. That sequence also converges to 0 so the series may converge. Since these are all positive values, we can apply the integral test: The series [itex]\sum \frac{x^n}{1+ x^n}[/itex] will converge if and only if the infinite integral [itex]\int_1^\infty \frac{x^y}{1+ x^y} dy[/itex] converges (for 0< x< 1). To integrate that, let u= 1+ xy. Then du= ln(x) xy so
[tex]\int_1^\infty \frac{x^y}{1+ x^y} dy= \frac{1}{ln x}\int_{1+x}^1\frac{du}{u}= -\frac{ln(1+x)}{ln(x)}[/tex]
Okay, that exists (and is positive since x< 1), and so the series converges for all x< 1.
The sequence of functions converges to the discontinuous (at 0) function f(x)= 0 for 0<= x< 1, f(1)= 1.
The series converges on [0, 1).
 
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  • #4
It's much easier to apply the ratio or comparison test.
Let [itex] s_n = \sum_{n=0}^\infty f_n(x)[/itex]
Obviously sn diverges for x>=1 since fn converges to 1 for x=1 and diverges for x>1. Thus we are only concerned with abs(x)<1. Note that each term fn in sn is positive for all x>0 and that the terms alternate in sign for x<0.

Ratio test: Each term in sn is positive for all x>0.
sn is a convergent series if [itex]f_{n+1}(x)/f_n(x) < 1[/itex] for all sufficiently large f. The ratio converges to x for x<1, so sn is convergent for [itex]x\in [0,1)[/itex].

Comparison test: The series [itex]\sum_{n=0}^\infty x^n[/itex] converges for all x in (-1,1). For all x>0, each term [itex]f_n(x) = \frac{x^n}{1+x^n}[/itex] is smaller than [itex]f_n(x) = x^n[/itex]. Thus sn is convergent for [itex]x\in [0,1)[/itex].

Alternating series test: The sequence [itex]\frac{\lvert x^n\rvert}{1+x^n}[/itex] is monotonically deceasing for [itex]x\in(-1,0)[/itex] and some sufficiently large n. Thus the alternating series \sum_{n=0}^\infty f_n(x), x\in(-1,0)[/itex] is convergent.
 
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  • #5
Pearce_09 said:
[tex]f_n(x)= x^n/1 + x^n [/tex]
does this series converge on the interval [0,1]
Say if x = 1 then the series is < some epslon , where epslon is > 0
but if x = 1 then the value for [tex]f_n(x)[/tex] is constant for all n
but does this still mean the series converges.. even tho the series doesn't get smaller for large values of n...
if not then it doesn't converge?

It looks easy...

If [tex]|x| < 1[/tex] it obviously converges to 0.

If [tex]x = 1[/tex] it is always [tex]1/2[/tex].

If [tex]x = -1[/tex] it doesn't converge, considering [tex]n[/tex] can take odd values.

If [tex]|x| > 1, [/tex] [tex]f_n(x)=x^n/(1+x^n) = 1/(1/x^n+1)[/tex], so it converges to 1.
 
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1. What is analysis and convergence?

Analysis and convergence refers to the process of studying and understanding a system or data by breaking it down into smaller components and analyzing how these components interact with each other. It also involves determining the stability and behavior of the system as it approaches a certain limit or goal, known as convergence.

2. Why is analysis and convergence important in science?

Analysis and convergence are crucial in science because they allow us to gain a deeper understanding of complex systems and data. By breaking down a system into smaller components and studying their interactions, we can make predictions and draw conclusions about the behavior of the system as a whole. Convergence also helps us determine the accuracy and reliability of our findings.

3. What are some common techniques used in analysis and convergence?

There are many techniques used in analysis and convergence, but some of the most common ones include mathematical modeling, statistical analysis, and computer simulations. These techniques help scientists break down complex systems and data into more manageable parts and analyze them to gain a better understanding of their behavior.

4. How does analysis and convergence contribute to scientific discoveries?

Analysis and convergence play a critical role in scientific discoveries by helping scientists make sense of complex data and systems. By using these techniques, scientists can identify patterns, make predictions, and draw conclusions that can lead to new discoveries and advancements in various fields of science.

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Yes, analysis and convergence can be applied to a wide range of data and systems. These techniques are used in many branches of science, including physics, biology, chemistry, and economics. They can also be applied to both static and dynamic systems, making them versatile tools for scientific research and analysis.

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