Is the RMS Mean Free Path Equal to the Mean Free Path?

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SUMMARY

The discussion centers on the relationship between the RMS mean free path and the mean free path in the context of statistical mechanics. It establishes that the RMS mean free path, denoted as λ(rms), is equivalent to the mean free path when derived using the survival equation. The participants clarify the definitions and calculations involved, particularly emphasizing the integration of the exponential distribution and the properties of mean values and variances. The final conclusion confirms that the RMS value equals √2 * λ, aligning with established mathematical definitions.

PREREQUISITES
  • Understanding of statistical mechanics concepts, particularly mean free path.
  • Familiarity with RMS (root-mean-square) calculations.
  • Knowledge of exponential distributions and their properties.
  • Basic integration techniques, including integration by parts.
NEXT STEPS
  • Study the derivation of the survival equation in the context of Maxwellian gas.
  • Learn about exponential distributions and their statistical properties.
  • Explore the concept of weighted averages and their applications in statistical analysis.
  • Practice integration techniques, particularly integration by parts, in various mathematical contexts.
USEFUL FOR

Students and professionals in physics, particularly those focusing on statistical mechanics, as well as mathematicians interested in the application of RMS calculations and integration techniques.

warhammer
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Homework Statement
The distribution of free path is given as N = N(o) e^ (-x/lambda) where lambda is the mean free path, and N is the number of molecules that survive collision on travelling a distance x, and N(o)is the no. of molecules at distance x = 0. Show that the root mean square (rms) free path is given by √2*lambda
Relevant Equations
lambda (rms)= v(rms) * t(rms) where t(rms) is the relaxation time.
lambda (rms)= v(rms) * t(rms) -- 1

Now I assume here that t(rms)=1/(√2*n*π*d^2*v(rms))

But this cancels the v(rms) term when used in eq (1) so the mean free path and the RMS free path would actually be the same (even later on when used in the aforementioned Survival Equation)

I would like to state that I have not understood what is meant by v(rms) clearly.. I would be really obliged if someone would explain the concept behind the question as well as provide the guidance to complete the question.

(I even tried to use the original derivation that was used for Survival Eqn in context of Maxwellian gas but that also provided no real insight)
 
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You are over-thinking things. x has an exponential distribution, for which it is a known property that the mean value of x is λ and the variance is λ2 so the mean value of x2 is 2λ2.
 
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mjc123 said:
You are over-thinking things. x has an exponential distribution, for which it is a known property that the mean value of x is λ and the variance is λ2 so the mean value of x2 is 2λ2.
Thank you for your response. However I'm unable to gauge more clearly how it would entail for the succeeding step in this particular case here. Please provide a hint or elaborate on this.
 
warhammer said:
I would like to state that I have not understood what is meant by v(rms) clearly.. I would be really obliged if someone would explain the concept behind the question as well as provide the guidance to complete the question.

A minor typo here. Please read it as Lambda(rms) or alternatively rms value of free path rather than v(rms).
 
If you have a distribution ##N(x)##, the mean value of ##x## over an interval ##a\leq x \leq b## is $$\langle x \rangle = \frac{\int_a^b x N(x)~dx}{\int_a^b N(x)~dx}.$$ The mean-squared is $$\langle x^2 \rangle = \frac{\int_a^b x^2 N(x)~dx}{\int_a^b N(x)~dx}.$$The root-mean-squared is $$x_{\text{rms}}=\sqrt{\langle x^2 \rangle} =\sqrt{ \frac{\int_a^b x^2 N(x)~dx}{\int_a^b N(x)~dx}}.$$Just use the definition.
 
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kuruman said:
If you have a distribution ##N(x)##, the mean value of ##x## over an interval ##a\leq x \leq b## is $$\langle x \rangle = \frac{\int_a^b x N(x)~dx}{\int_a^b N(x)~dx}.$$ The mean-squared is $$\langle x^2 \rangle = \frac{\int_a^b x^2 N(x)~dx}{\int_a^b N(x)~dx}.$$The root-mean-squared is $$x_{\text{rms}}=\sqrt{\langle x^2 \rangle} =\sqrt{ \frac{\int_a^b x^2 N(x)~dx}{\int_a^b N(x)~dx}}.$$Just use the definition.

Sir what you're expressing quantitatively is not coming out and the remaining resultant text is indecipherable.

Request you to express it again..
 
I have expressed it as clearly as I can. Just substitute and do the integral. If it doesn't "come out", please post what does come out and we will take it from there.
 
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kuruman said:
I have expressed it as clearly as I can. Just substitute and do the integral. If it doesn't "come out", please post what does come out and we will take it from there.
First of all I would like to apologise for the silly question from my side. I was viewing the PF Site on my mobile and it was not rendering the relevant mathematics, just the written words. It was only after I opened the same via another device I was able to finally see the mathematics😅😅

Now I inputted everything via the survival equation & integrated the function using the "by parts technique". This resulted in the mean squared value to be 2*(lambda)^2. Using the same in the RMS definition specified by you, I obtained that RMS value=√2*lambda.

The answer has matched now but I would love if you could explain the mathematical definitions qualitatively if possible (the specific integrands in numerator and denominator, and I hope you would excuse this very trivial and silly probing).
 
Apology accepted. Look up weighted average (or weighted mean). There are plenty of links and videos explaining it and it makes no sense to repeat that stuff when it already exists.
 
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kuruman said:
Apology accepted. Look up weighted average (or weighted mean). There are plenty of links and videos explaining it and it makes no sense to repeat that stuff when it already exists.
Thank you tons for your help sir. You've been most kind!
 

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