Ask how the same oscillator responds at each frequency
For mass and frequency , let denote energy decay rate. A viscous force opposes velocity. At each drive frequency, multiply force by the mechanical susceptibility to obtain displacement. Its units are metres per newton.
Near resonance, repeated pushes accumulate motion. Away from resonance their timing slips relative to the oscillator. Peak position largely reports inertia and elasticity; width reports energy loss.
Source locations: Aspelmeyer
Spectral area gives variance
Subtract the mean displacement. The two-sided spectrum includes positive and negative angular frequencies. Its correlation function asks how similar the motion remains after a time delay. Fourier transformation distributes that correlation over frequency. For quantum displacement, use the symmetrized correlation, averaging the two operator orders.
Many instruments show a one-sided spectrum per hertz: retain positive frequencies and add the equal contribution from negative frequencies. The equations specify our normalization. Integrating over a finite band converts square metres per hertz to square metres.
Use equilibrium to set the area
In the high-temperature white-noise limit, a viscous bath both removes energy and kicks the oscillator. At equilibrium the two effects balance. Multiply the force spectrum by susceptibility magnitude squared, then integrate. It must recover the equipartition variance, providing an independent area check.
Worked example: choose , and . Equipartition gives a displacement standard deviation of . Suppose the converted mechanical peak has area . If mass and temperature are reliable, the displacement-amplitude calibration is too small by two: its variance is too small by four.
Source locations: Aspelmeyer · Callen & Welton
The detector adds its own fluctuations
The instrument sees the whole readout chain. A flat optical background, a mechanical peak and electronic noise may all contribute. Calibrate photocurrent response to displacement independently. Any subtraction of background under the peak needs a stated model. Counting that background as motion overestimates temperature.
A finite observation also broadens spectral lines. Frequencies above half the sample rate can fold into lower frequencies, an effect called aliasing. Longer records improve frequency resolution. Faster sampling and an antialiasing filter address a different limitation.