Maxwell distribution in thermal equilibrium

Then you have to evaluate the other integrals. But by symmetry, they should be the same as the first one, right? So the average value of ##v_x## is zero.In summary, the Maxwell probability distribution describes the distribution of particles in a gas in thermal equilibrium. To find the average velocity, we integrate over the variables vx, vy, and vz using the distribution function and their corresponding coordinates. By symmetry, the average value of vx, vy, and vz is equal to zero.
  • #1
Firben
145
0

Homework Statement



In thermal equilibrium, the particle in a gas are distributed in velocity space according to the Maxwell distribution

f(v) = A*exp(-mv^2/(2KT))

What is the average velocity ? What is the most probable velocity ?

Homework Equations



<v> = ∫∫∫vf(v)d3v = (0 to infinty) ∫∫∫vxf(v)d3vx^ + ∫∫∫vyf(v)d3vy^ + ∫∫∫vzf(v)d3vz^

The Attempt at a Solution



I started with the vy coordinate

[0 to inf] ∫∫∫vyAexp(-mv^2/(2KT))dy = ∫[0 to 2pi]∫[0 to pi][0 to inf]vyA*exp(-mv2/(2KT))*v2y sin(θ)dθdvdφ = 4piA∫vy3exp(-mv^2/(2KT)) dv = Here is the problem, if i evaluate the integral i got a non-zero value. I know the 3 integrals should be zero since they are mult. of odd times even. And the most probable velocity is just the derivative of the f(v) function by resp. coordinate right ?
 
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  • #2
If you are going to use spherical coordinates, then you will need to express vy in terms of v, θ, and φ before you integrate over θ and φ.

Or, you can use Cartesian coordinates and write the volume element as dvxdvydvz. Then you would integrate over the variables vx, vy, and vz.
 
  • #3
Yes, i forgot to include that in my latex code, but i have done that. If i integrate with cartesian coordinates i got:
[0 to inf]∫∫∫Ae-m/(2KT)*(Vx2+vy2+vz2dvxdvydvz =[0 to inf] ∫Ae-m/(2KT)*vx2 +--- = non-zero value which is wrong. What goes wrong ?
 
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  • #4
If you are trying to get the average y-component of velocity, then you need to include a factor of vy in the integrand.

Also, what are the correct limits in the integral for vx, vy, and vz? (Note that the components of velocity can be negative.)
 
  • #5
Did you mean the integral = 4piA∫vy3exp(-mv^2/(2KT)) dv or [0 to inf] ∫Ae-m/(2KT)*vx2 (x component) ?
 
  • #6
If i do the following integral

v- = [inf to -inf]∫vƒm^d3v = and put in spherical coordinates and simplify i got 4π(πvth2)-3/2*vth4 [inf to -inf] ∫y3 e-y2dy = [Part. int.] =...= 2*(2KT/mπ)1/2

It should be zero
 
  • #7
The Maxwell probability distribution is ##Ce^{-m(v_x^2+v_y^2+v_z^2)/(2kT)}## where ##C## is a constant.

This means that the average value of any function ##f(v_x, v_y, v_z)## is given by $$C\int_{-\infty}^{\infty}\int_{-\infty}^{\infty}\int_{-\infty}^{\infty}f(v_x, v_y, v_z)e^{-m(v_x^2+v_y^2+v_z^2)/(2kT)}dv_xdv_ydv_z$$

So, to find the average value of ##v_x##, you would let ##f(v_x, v_y, v_z) = v_x##. Try this and see what you get.

It's important not to confuse the probability distribution for the variables ##v_x, v_y, v_z## (as given above) with the probability distribution for the single variable ##v## (the speed of the particle). The distribution function for ##v## is ##Bv^2e^{-mv^2/(2kT)}##, where ##B## is a constant.
 
  • #8
If i integrate with resp. cartesian coordinates i got it to be equal to C*((2πKT)/m)3/2*(KT/m). Since the Gaussian integral is equal to (2πKT/m)1/2. Is something missing here ?
 
  • #9
Suppose you are trying to find the average value of ##v_x##. What does the integrand look like when you are integrating over all ##v_x##? Is the integrand an even function or an odd function of ##v_x##?
 
  • #10
If i integrate over vx: [-inf to inf]C∫∫[-KTvx/m*exp(-m(vx^2+vy^2+vz^2)/(2KT))](-inf to inf] + KT/m [-inf to inf]∫exp(-m((vx^2+vy^2+vz^2)/(2KT)) dvy dvz. The integral [-inf to inf] Is odd right ?. But i don't know if vx is even or odd
 
  • #11
$$<v_x> = C\int_{-\infty}^{\infty}\int_{-\infty}^{\infty}\int_{-\infty}^{\infty}v_xe^{-m(v_x^2+v_y^2+v_z^2)/(2kT)}dv_xdv_ydv_z$$

$$<v_x> = C\int_{-\infty}^{\infty}v_xe^{-mv_x^2/(2kT)}dv_x\int_{-\infty}^{\infty}e^{-mv_y^2/(2kT)}dv_y\int_{-\infty}^{\infty}e^{-mv_z^2/(2kT)}dv_z$$

What do you get when you evaluate the first integral on the right?
 
  • #12
This was the integral i just evaluated above which i got to be equal to C*((2πKT)/m)^3/2*(KT/m). One with part. integration(and gaussian) and the last two integrals is the gaussian integral.
 
  • #13
Did you integrate the first integral from -∞ to +∞? The integrand is $$v_xe^{-mv_x^2/(2kT)}$$ If you replace ##v_x## by ##-v_x## what happens to the overall sign of the integrand?
 
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  • #14
Firben said:
If i integrate over vx: [-inf to inf]C∫∫[-KTvx/m*exp(-m(vx^2+vy^2+vz^2)/(2KT))](-inf to inf] + KT/m [-inf to inf]∫exp(-m((vx^2+vy^2+vz^2)/(2KT)) dvy dvz. The integral [-inf to inf] Is odd right ?. But i don't know if vx is even or odd
Since you're having problems evaluating the integral, it would help if you showed what you're doing rather than just saying you got the wrong answer.

I don't know if it's just a typo, but what's up with the red part?

[-inf to inf]C∫∫[-KTvx/m*exp(-m(vx^2+vy^2+vz^2)/(2KT))](-inf to inf] + KT/m [-inf to inf]∫exp(-m((vx^2+vy^2+vz^2)/(2KT)) dvy dvz
 
  • #15
I got the right integral to be equal to C[-inf to inf on all integrals]∫vxe((-m*vx2))/(2KT)dvx∫e((-m*vy2))/(2KT)dvy*((2πKT)/(m)) = C((2πKT)/(m))^(1/2)∫vxe((-m*vx2))/(2KT)dvx*((2πKT)/(m)) = C((2πKT)/(m))^(1/2) ([-/KTvx)/m*e-mvx2/(2KT)]+ KT/m∫e-mvx2/(2KT) dvx = the first is equal to zero and the last is (2πKT/m)^(1/2) =C(2πKT/m)^(3/2)*(KT/m)

If i replace vx with -vx in the integral then i got it to be equal to C[inf to -inf]vxe-(mvx2)/(2KT), when i switch -inf to inf
 
  • #16
The integral over ##v_x## has an odd integrand, so the integral must be zero. There is then no need to evaluate the other integrals over ##v_y## and ##v_z##.
 
  • #17
Firben said:
I got the right integral to be equal to C[-inf to inf on all integrals]∫vxe((-m*vx2))/(2KT)dvx∫e((-m*vy2))/(2KT)dvy*((2πKT)/(m)) = C((2πKT)/(m))^(1/2)∫vxe((-m*vx2))/(2KT)dvx*((2πKT)/(m)) = C((2πKT)/(m))^(1/2) ([-/KTvx)/m*e-mvx2/(2KT)]+ KT/m∫e-mvx2/(2KT) dvx = the first is equal to zero and the last is (2πKT/m)^(1/2) =C(2πKT/m)^(3/2)*(KT/m)

If i replace vx with -vx in the integral then i got it to be equal to C[inf to -inf]vxe-(mvx2)/(2KT), when i switch -inf to inf
The problem is that you're not integrating by parts correctly. In fact, integration by parts doesn't work with this integral; the substitution ##u=v_x^2## would work. The easiest route, of course, is what TSny has said. The integrand is odd, so the integral must vanish.
 

1. What is the Maxwell distribution in thermal equilibrium?

The Maxwell distribution in thermal equilibrium is a probability distribution that describes the speeds of particles in a gas or liquid at a specific temperature. It is based on the principles of kinetic theory, which states that the average kinetic energy of particles in a substance is directly proportional to its temperature. This distribution helps us understand the behavior and properties of particles in a thermal system.

2. How does the Maxwell distribution relate to the kinetic theory of gases?

The Maxwell distribution is based on the principles of kinetic theory, which describes the behavior of gases in terms of the motion of individual particles. It states that the average kinetic energy of particles in a gas is directly proportional to its temperature. The Maxwell distribution shows how this energy is distributed among particles at a specific temperature, providing insights into the behavior of gases and liquids.

3. What factors affect the shape of the Maxwell distribution?

The shape of the Maxwell distribution is affected by the temperature of the substance, the mass of the particles, and the type of gas or liquid. Higher temperatures result in a broader distribution, while heavier particles and gases with stronger intermolecular forces lead to a narrower distribution. Additionally, the presence of external forces, such as gravity or electric fields, can also affect the shape of the distribution.

4. How is the Maxwell distribution used in practical applications?

The Maxwell distribution is used in various fields, including physics, chemistry, and engineering. It is helpful in understanding and predicting the behavior of gases and liquids in thermal systems, such as in the design of engines and refrigeration systems. It is also used in statistical mechanics to calculate thermodynamic properties of substances, such as pressure and heat capacity.

5. What is the relationship between the Maxwell distribution and the Boltzmann distribution?

The Maxwell distribution is a special case of the Boltzmann distribution, which describes the distribution of particles in a system at thermal equilibrium. While the Maxwell distribution only applies to particles in a gas or liquid, the Boltzmann distribution can be applied to any type of particles, including solids and plasmas. The Maxwell distribution is a simplified version of the Boltzmann distribution, taking into account only the speed of particles, while the Boltzmann distribution considers all possible energy states of particles.

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