Is thermal noise a statistical uncertainty?

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SUMMARY

The discussion centers on the relationship between thermal noise and statistical uncertainty in measurements of a system defined by the equation y=ax. The parameter a is to be extracted from measured values of y, while x, the position of a particle in a thermal bath at temperature T, introduces uncertainty. The Boltzmann distribution governs the probability of x based on the particle's energy, which is modeled as kx²/2. The participants conclude that the uncertainty in x leads to a statistical uncertainty in y, and the average value of y can be estimated through multiple measurements, assuming Gaussian noise characteristics.

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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 Boltzmann 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?
 

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