Understanding the Spatial Accuracy of Track Detectors

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SUMMARY

The spatial accuracy of track detectors is defined by the formula σ = pitch/sqrt(12), where "pitch" refers to the distance between two wires or fibers. The factor sqrt(12) originates from statistical analysis related to the uniform distribution. Specifically, the variance of a uniform distribution is calculated as (b-a)²/12, which directly influences the spatial accuracy measurement. Understanding this relationship is crucial for those working with track detectors in experimental nuclear physics.

PREREQUISITES
  • Understanding of statistical analysis, particularly uniform distribution
  • Familiarity with the concept of variance in statistics
  • Knowledge of track detectors and their components
  • Basic principles of experimental nuclear physics
NEXT STEPS
  • Research the derivation of variance for uniform distributions
  • Explore advanced statistical methods in experimental physics
  • Study the design and function of track detectors in nuclear experiments
  • Learn about the implications of spatial accuracy in detector performance
USEFUL FOR

Experimental physicists, statisticians, and engineers involved in the design and analysis of track detectors, as well as anyone interested in the statistical foundations of measurement accuracy in scientific instrumentation.

McCuack
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Hi

please forgive me if you find that this is not the correct place, but since my work is of experimental nuclear physics and I didn't find a sub.forum in math neither engineering I decide to post here.

Here is the question:

in any track detector, the spatial accuracy of the detector is σ=pitch/sqrt(12) where the pitch is the separation between two wires/fibers/etc, but where the sqrt(12) comes from?

I know that should come from some statistics analysis but I have an absolute blockout.

Thank you
 
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The uniform distribution !
\mu = \frac{1}{b-a}\int_a^b \text{d}x\,x = \frac{a+b}{2}
\sigma^2 = \frac{1}{b-a}\int_a^b\text{d}x\, (x-\mu)^2 = \frac{(b-a)^2}{12}
 
thank you very much!
 

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