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Signal-to-Noise Optimization

Signal-to-Noise Optimization. Noise Sources Most Commonly Encountered 1. Detector Noise 2. Shot Noise 3. Flicker Noise. Detector Noise. Associated only with the detector, and therefore constant for a given set of detector conditions. N detector = Constant (S/N) det  S. Shot Noise.

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Signal-to-Noise Optimization

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  1. Signal-to-Noise Optimization Noise Sources Most Commonly Encountered 1. Detector Noise 2. Shot Noise 3. Flicker Noise

  2. Detector Noise Associated only with the detector, and therefore constant for a given set of detector conditions. Ndetector = Constant (S/N)det S

  3. Shot Noise Noise associated with the random transfer of electrons across a p-n junction. Ex: Whether or not a single photon falling on a detector will actually produce a signal.

  4. Nshot √2SeΔf Where: S = measured signal e = charge on electron Δf = frequency bandwidth Shot noise is usually the limiting source of noise near the detection limit

  5. S (S/N)shot = √2SeΔf(S/N)shot = √S/2eΔf Δf  1/tc where tc = time constant So (S/N)shot  √Stc

  6. Flicker Noise Random noise with a 1/f frequency dependence. f = sampling frequency Flicker noise includes slow drifts in signal intensity caused by such parameters as temperature, flow rates, etc.

  7. Nflicker = ξ S where ξ = flicker factor (unit-less) (S/N)fl = S/ξS = 1/ξ ξ 1/f so (S/N)fl f and f = frequency of data collection

  8. How do we determine which type of noise is present? (S/N)fl = 1/ξ (S/N)shot  √Stc (S/N)det S

  9. Prepare a plot of log(S) vs. log(S/N) determine the slope (m) 1. m = 1 → Detector Noise 2. m = ½ → Shot Noise 3. m = 0 → Flicker Noise

  10. S S/N N

  11. Other noise sources such as environmental noise should always be eliminated. When we measure N experimentally, it is often a combination of all of the noises present in the system. The preceding equations are useful to determine which type of noise dominates in a certain situation.

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