Is thermal noise a statistical uncertainty?

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In summary, the conversation discussed a system described by ##y=ax##, where a is the parameter to be extracted and y is the measured quantity. The parameter x is experimentally controlled but has associated uncertainty. It was clarified that x represents the position of a particle in contact with a thermal bath at temperature T, with the particle's energy being ##kx^2/2##. The probability of a given x was stated to follow a Boltzmann distribution. It was questioned whether this uncertainty is of a statistical nature and the concept of "Gaussian and not thermal noise" was brought up. The conversation ended with a discussion on the nature of the thermal probability distribution and the meaning of the "true" value.
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kelly0303
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Hello! I have a system described by ##y=ax##, where a is the parameter I want to extract and y is the stuff I measure (we can assume that I can measure one instance of y without any uncertainty). x is a parameter I can control experimentally but it has an uncertainty associated to it. In a simplified form (but enough for my question), x is the position of a particle (classically) in contact with a thermal bath at temperature T. For example we can assume that the energy of the particle is ##kx^2/2##, where k is a known constant and for each measurement of y, x has a different x, where the probability of an x is given by the probability of having that given energy based on a Boltzman distribution at temperature T. I am not sure if this is a statistical uncertainty or not. I would say it is, because if I measure many y values, I can narrow down the true y value (if I assume I have Gaussian and not thermal noise, that would go down as ##1/\sqrt{N}##, where N is the number of measurements, right?), but I wanted to make sure this makes sense.
 
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What do you mean by "Gaussian and not thermal noise"? The thermal probability distribution in your case is proportional to
$$e^{-\beta E}=e^{-\beta kx^2/2}$$
which is also Gaussian. Besides, by the "true" value, do you mean the average value?
 

1. What is thermal noise?

Thermal noise, also known as Johnson-Nyquist noise, is a type of noise that is present in any electronic system due to the random motion of electrons. It is caused by the thermal energy of the environment and is independent of any external signals or inputs.

2. How does thermal noise affect measurements?

Thermal noise can cause fluctuations in the measured values of signals, making it difficult to accurately determine the true value. This is because the noise adds an element of uncertainty to the measurements, making it harder to distinguish between the signal and the noise.

3. Is thermal noise a significant factor in electronic systems?

Yes, thermal noise is a significant factor in electronic systems, especially at higher temperatures. It is present in all electronic components and can limit the accuracy and sensitivity of measurements.

4. Can thermal noise be reduced or eliminated?

Thermal noise cannot be completely eliminated, but it can be reduced by using techniques such as shielding, filtering, and amplification. These methods can help to minimize the impact of thermal noise on measurements.

5. How is thermal noise related to statistical uncertainty?

Thermal noise is a type of statistical uncertainty because it follows a statistical distribution and cannot be predicted or controlled. It is a random phenomenon that contributes to the overall uncertainty of measurements and must be accounted for in statistical analysis.

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