Noise Power Paradox: Explaining Limitations

In summary, the noise power across a resistor in thermal equilibrium is limited because the formula for the noise V_{RMS} = \sqrt{4RkT\Delta f} is based on the assumption of an ideal resistor with a uniform power spectral density over an infinite range of frequencies. However, in reality, resistors possess a small stray capacitance which modifies the power spectral density and limits the noise power.
  • #1
The Alchemist
18
0

Homework Statement


Explain why the noise power across a resistor in thermal equilibrium is limited in contradiction to the formula for the noise [tex]V_{RMS} = \sqrt{4RkT\Delta f}[/tex]
which states that if we measure with infinite bandwidth we have infinitely large power


Homework Equations


[tex]V_{RMS} = \sqrt{4RkT\Delta f}[/tex]


The Attempt at a Solution


So the formula states that if a system measures the noise power of a resistor with infinite bandwidth is the noise power is infinitely large. But the noise power cannot exceed the internal energy of the resistor, which is not infinitely large. But I don't know where and why the formula can't hold anymore.

Thanks in advance
 
Physics news on Phys.org
  • #2
Hi The Alchamist, welcome to PF!:smile:

The Alchemist said:
So the formula states that if a system measures the noise power of a resistor with infinite bandwidth is the noise power is infinitely large. But the noise power cannot exceed the internal energy of the resistor, which is not infinitely large. But I don't know where and why the formula can't hold anymore.

Thanks in advance

Hmmm... well, how was the formula derived? What assumptions was the derivations based on?
 
  • #3
Thanks,

Well the power spectral density function of thermal noise is [tex] \phi = 4RkT [/tex]
So the power is the integral of the power spectral density function over the bandwidth.
[tex]W = \int\limits_{bandwidth} \phi \mathrm{d}f = \int_{f_{1}}^{f_{2}}4RkT \mathrm{d}f = 4RkT\Delta f [/tex]

With [tex]\Delta f = f_{2}-f_{1} [/tex]
This means that
[tex]V_{RMS} = \sqrt{W} = \sqrt{4RkT \Delta f}[/tex]

So probably there is something wrong with the assumption of the boundary condition of the integral that f2 can't go to infinity. But I have no clue why there is such condition it should be possible to take an infinite bandwidth. So maybe the phi is wrong :?. confusing
 
  • #4
There are certain assumptions that underline the claim that [itex]\phi = 4RkT[/itex]...what are they?
 
  • #5
Well, the PSD is uniform over an infinite range of frequencies but it is proportional to the temperature of the resistor. What you want is a PSD that is cut-off at a certain frequency to limit the power. But I don't know why the PSD should have such a frequency.
 
  • #6
The point I'm hinting towards is that the PSD is valid only for an Ideal resistor, something which is inherently unphysical. Real resistors will always possesses some small stray Capacitance. If you call the effective capacitance of the resistor [itex]C[/itex], the effect of it is to modify the power spectral density to

[tex]\phi=\frac{4RkT}{\left(1+(2\pi fRC)^2\right)}[/tex]

Which you should derive yourself by considering a circuit consisting of an ideal resistor, a capacitor and a noise source...

What happens when you integrate this distribution over all frequencies? Why is [itex]\phi=4RkT[/itex] a good approximation for most frequencies?
 
  • #7
Ok I put a capacitor parallel to the resistor and derive the new impedance which is indeed
[tex]
Z = \frac{R}{\left(1+(2\pi fRC)^2\right)}
[/tex]
So [tex]
\phi= 4ZkT = \frac{4RkT}{\left(1+(2\pi fRC)^2\right)}
[/tex]

Integrating over df gives:
[tex]
\frac{2kT}{ \pi C} \arctan{2 \pi C f R}
[/tex]
filling in f with limits from 0 to infinity gives:
[tex]
\frac{2kT}{ \pi C} \frac{\pi}{2} - 0
= \frac{kT}{C}
[/tex]
which is of course finite with constant temperature.
The idea that phi is a good approximation up to a certain frequency is because the capacitance of the parallel capacitor is very small so the term [tex](2 \pi f R C)^2[/tex] is negligible and phi is the "original" phi for the ideal resistor.

That is what I can think of and seems correct,
Thanks
 
  • #8
Looks good to me!:approve:
 

1. What is the Noise Power Paradox?

The Noise Power Paradox is a phenomenon in which the noise level in a system increases with the number of components, even though each individual component may have a low noise level. This can lead to limitations in the overall performance of the system.

2. What causes the Noise Power Paradox?

The Noise Power Paradox is caused by the interaction between the components in a system. As the number of components increases, so does the number of interactions between them, leading to an overall increase in noise.

3. How does the Noise Power Paradox affect system performance?

The Noise Power Paradox can limit the performance of a system by reducing its signal-to-noise ratio. This means that the desired signal becomes harder to distinguish from the background noise, leading to errors and decreased accuracy.

4. Are there any ways to mitigate the effects of the Noise Power Paradox?

There are several techniques that can be used to reduce the impact of the Noise Power Paradox. These include using noise-cancelling methods, designing components to have lower noise levels, and optimizing the system's layout to minimize interactions between components.

5. Are there any real-world examples of the Noise Power Paradox?

Yes, the Noise Power Paradox has been observed in various systems, such as electronic circuits, communication systems, and even biological systems. It is a fundamental limitation that must be considered in the design and operation of any complex system.

Similar threads

  • Advanced Physics Homework Help
Replies
4
Views
2K
Replies
9
Views
1K
  • Classical Physics
Replies
8
Views
2K
Replies
3
Views
1K
  • Electrical Engineering
Replies
1
Views
1K
  • Introductory Physics Homework Help
Replies
4
Views
2K
Replies
4
Views
6K
  • Advanced Physics Homework Help
Replies
16
Views
2K
  • Engineering and Comp Sci Homework Help
Replies
4
Views
2K
  • Electrical Engineering
Replies
18
Views
7K
Back
Top