Justifying Log Approximation for Low \tau and High E_o

In summary, the teacher makes the approximation that log(1 + 3e^{-2\frac{E_o}{\tau}}) \approx \log(3e^{-2\frac{E_o}{\tau}}) for \tau << E_o. The logs are assumed to be natural logs. The justification for this is that for many purposes, x \approx x+1 when x is large, but in this case x is not large. The context is calculating the partition function for rotational degrees of freedom for a single molecule and taking only the first two terms in the \tau << E_o limit. There was confusion around the use of log in the second expression, but it was clarified that it was a misreading of
  • #1
eep
227
0
Hi,
In his notes, our teacher makes this approximation:

[tex]
\log(1 + 3e^{-2\frac{E_o}{\tau}}) \approx \log(3e^{-2\frac{E_o}{\tau}})
[/tex]

For [itex]\tau << E_o[/itex]

Also, and I don't think this matters, the logs are assumed to be natural logs.

I was wondering what the justification for this was...
 
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  • #2
For many purposes, [itex]x \approx x+1[/itex] when x is large.
 
  • #3
But x isn't large in this case?
 
  • #4
There doesn't appear to be much. What's the context? Is [tex]3e^{-2\frac{E_o}{\tau}}[/tex] very large?

EDIT: In that case, ask your teacher
 
  • #5
I thought maybe you had forgotten [itex]\tau < 0[/itex]. If the argument to log isn't large, then that's not a good approximation.
 
  • #6
Sorry I hadn't quite finished editing my post when people started replying. We're trying to calculate the partition function for rotational degrees of freedom for a single molecule. So we have an infinite sum which we keep only the first two terms in the [itex]\tau << E_o[/itex] limit (the terms in the log). We then want to calculate the average energy which is where the log comes from, and he then makes that approximation. I guess I'll just have to ask him.
 
  • #7
Are you sure there's a log around that second expression? Because [itex]log(1+x)\approx x [/itex] for x very small.
 
  • #8
Ah, yes. I just misread the notes! Thanks anyways!
 

1. What is the "Justifying Log Approximation" and why is it important?

The "Justifying Log Approximation" is a mathematical technique used to simplify complex equations involving logarithms. It is important because it allows scientists to solve problems more efficiently, especially when dealing with low values of τ (tau) and high values of Eo (energy). This approximation is commonly used in various scientific fields, including physics, chemistry, and engineering.

2. How does the "Justifying Log Approximation" work?

The "Justifying Log Approximation" works by using the properties of logarithms to rewrite an expression in a simpler form. It involves taking the logarithm of both sides of an equation and using logarithm rules to simplify the equation. This process can be repeated multiple times until the equation is in a form that is easier to solve.

3. What are the limitations of the "Justifying Log Approximation"?

While the "Justifying Log Approximation" is a useful technique, it has limitations. It is only accurate for small values of τ and large values of Eo. If these values are too far from the range of validity, the approximation may introduce significant errors in the solution. Additionally, the approximation may not work for complex equations with multiple variables and parameters.

4. Can the "Justifying Log Approximation" be used in all scientific fields?

Yes, the "Justifying Log Approximation" can be used in various scientific fields, including physics, chemistry, and engineering. However, it is important to note the limitations and ensure that the values used in the approximation fall within the range of validity. In some cases, alternative techniques may be more appropriate for solving certain equations.

5. Are there any other similar approximation techniques used in science?

Yes, there are other approximation techniques used in science, such as the Taylor series approximation and the binomial approximation. These techniques are used to simplify complex equations and make them easier to solve. Each technique has its own set of limitations and is suitable for different types of equations and problems.

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