Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Errors in Global Positioning System01:26

Errors in Global Positioning System

Global Positioning System (GPS) technology has revolutionized navigation and positioning, but its accuracy is often compromised by various errors. These errors, stemming from environmental, satellite, and receiver-related factors, require careful mitigation to ensure reliable performance across applications.Atmospheric ErrorsGPS signals travel through the Earth’s ionosphere and troposphere, introducing delays which affect accuracy. The ionosphere is strongly influenced by charged particles,...
Random and Systematic Errors01:20

Random and Systematic Errors

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...
Random and Systematic Errors01:20

Random and Systematic Errors

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...
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.
Random Error01:04

Random Error

Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Altaicalarins A-D, cytotoxic bisabolane sesquiterpenes from Ligularia altaica.

Journal of natural products·2010
Same author

[Isolation and biodiversity of copper-resistant bacteria from rhizosphere soil of Elsholtzia splendens].

Wei sheng wu xue bao = Acta microbiologica Sinica·2010
Same author

Chemotherapy resistance research of lung cancer based on micro-fluidic chip system with flow medium.

Biomedical microdevices·2010
Same author

[Preparation of enteric nanoparticles of Schisandra total lignanoids and preliminary study on its pharmacokinetics].

Yao xue xue bao = Acta pharmaceutica Sinica·2010
Same author

[A survey of health effects on population exposure to a dust event in Beijing City].

Wei sheng yan jiu = Journal of hygiene research·2010
Same author

Effects of beta-ionone on mammary carcinogenesis and antioxidant status in rats treated with DMBA.

Nutrition and cancer·2010
Same journal

Multifunctional reconfigurable terahertz metasurface based on vanadium dioxide phase transition: achieving broadband absorption and efficient polarization conversion.

Applied optics·2026
Same journal

High-Q-factor electromagnetically induced transparency utilizing quasi-bound states in the continuum in an all-dielectric terahertz metasurface.

Applied optics·2026
Same journal

Automated stitching interferometry for high-precision metrology of X-ray mirrors.

Applied optics·2026
Same journal

Experimental demonstration of an approach to designing a metal-dielectric DBR resonant cavity structure.

Applied optics·2026
Same journal

High-precision wavefront reconstruction from a single-shot interferogram using a physics-driven hybrid feature calibration network.

Applied optics·2026
Same journal

Ultra-high-Q Fano resonance based on coupled topological corner states in Kagome photonic crystals.

Applied optics·2026
See all related articles

Related Experiment Video

Updated: Jun 16, 2026

Experimental and Data Analysis Workflow for Soft Matter Nanoindentation
13:04

Experimental and Data Analysis Workflow for Soft Matter Nanoindentation

Published on: January 18, 2022

4.7K

Random errors in interferometry with the least-squares method.

Qi Wang1

  • 1Department of Physics, Huazhong University of Science & Technology, Wuhan, 430074, China.

Applied Optics
|January 26, 2011
PubMed
Summary
This summary is machine-generated.

This study quantifies random errors in interferometric surface profilers caused by intensity and position noise. Derived formulas accurately estimate measurement standard deviations, aiding in precise surface analysis.

More Related Videos

Implementation of a Reference Interferometer for Nanodetection
16:11

Implementation of a Reference Interferometer for Nanodetection

Published on: April 26, 2014

9.7K
The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry
12:14

The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry

Published on: August 12, 2013

22.3K

Related Experiment Videos

Last Updated: Jun 16, 2026

Experimental and Data Analysis Workflow for Soft Matter Nanoindentation
13:04

Experimental and Data Analysis Workflow for Soft Matter Nanoindentation

Published on: January 18, 2022

4.7K
Implementation of a Reference Interferometer for Nanodetection
16:11

Implementation of a Reference Interferometer for Nanodetection

Published on: April 26, 2014

9.7K
The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry
12:14

The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry

Published on: August 12, 2013

22.3K

Area of Science:

  • Optical Metrology
  • Surface Characterization
  • Data Analysis

Background:

  • Interferometric surface profilers are crucial for high-precision measurements.
  • Random noise, including intensity and position noise, can significantly impact measurement accuracy.
  • Understanding and quantifying these errors is essential for reliable surface analysis.

Purpose of the Study:

  • To analyze random errors in interferometric surface profilers.
  • To investigate the impact of intensity and position noise on surface height measurements.
  • To develop and validate methods for estimating measurement standard deviations.

Main Methods:

  • Application of the least-squares method to analyze random errors.
  • Derivation of formulas for estimating standard deviations under specific noise conditions (intensity noise only, position noise only).
  • Validation using simulated noisy interferometric data and comparison with theoretical derivations.

Main Results:

  • Two distinct formulas were derived for estimating standard deviations based on noise type.
  • Simulated measurements showed good agreement with theoretically derived standard deviations.
  • Established relationships between random error and light source wavelength, and between random error and fringe amplitude.

Conclusions:

  • The derived formulas provide accurate estimations of random errors in interferometric measurements.
  • The study successfully quantifies the impact of intensity and position noise on surface profiling.
  • Findings contribute to improved accuracy and reliability in optical surface metrology.