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Related Concept Videos

Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.
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Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
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In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
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The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry
12:14

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Published on: August 12, 2013

Performance degradation of a Michelson interferometer due to random sampling errors.

D L Cohen1

  • 1Communications Division, ITT Aerospace, PO Box 3700, 1919 West Cook Road, Fort Wayne, Indiana 46801, USA. dlcohen@itt.com

Applied Optics
|February 29, 2008
PubMed
Summary
This summary is machine-generated.

Disturbances in Michelson interferometers cause sampling errors, degrading performance. Adjusting interferogram background can minimize this spectral noise, improving measurement accuracy.

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Area of Science:

  • Optical physics
  • Spectroscopy
  • Interferometry

Background:

  • Michelson interferometer performance is sensitive to environmental disturbances.
  • Nonconstant sampling intervals corrupt interferogram signals and measured spectra.
  • Understanding spectral noise is crucial for accurate interferometric measurements.

Purpose of the Study:

  • To derive a formula for spectral noise in Michelson interferometers caused by nonconstant sampling.
  • To analyze the interaction between random disturbances and the interferogram signal.
  • To identify methods for minimizing sampling noise amplitude.

Main Methods:

  • Derivation of a formula for spectral noise based on the power spectrum of random disturbances.
  • Analysis of the correlation properties of sampling noise across the measured spectrum.
  • Experimental adjustment of unbalanced background interferogram size.

Main Results:

  • A formula was derived detailing how random disturbances contaminate the measured spectrum.
  • Sampling noise was shown to be correlated over large spectral regions, unlike conventional noise.
  • Minimizing the amplitude of sampling noise was achieved by matching background interferogram sizes.

Conclusions:

  • Nonconstant sampling intervals significantly degrade Michelson interferometer performance.
  • The derived formula quantifies spectral noise contamination, aiding in error analysis.
  • Matching background interferogram sizes offers a practical method to reduce sampling noise.