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Related Concept Videos

Random Sampling Method01:09

Random Sampling Method

Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
Random Variables01:09

Random Variables

A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
Randomized Experiments01:13

Randomized Experiments

The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
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...
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...

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Updated: Jun 22, 2026

Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA
12:36

Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA

Published on: May 9, 2011

Bias-free true random-number generator.

Wei Wei1, Hong Guo

  • 1CREAM Group, State Key Laboratory of Advanced Optical Communication Systems and Networks and Institute of Quantum Electronics, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China.

Optics Letters
|June 17, 2009
PubMed
Summary
This summary is machine-generated.

We introduce a novel method for generating true random numbers using laser pulses and photon detection. This approach ensures unbiased random bit generation without postprocessing, offering a fast and reliable solution.

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Area of Science:

  • Quantum optics
  • Information science
  • Cryptography

Background:

  • Nondeterministic random number generation is crucial for secure communication and scientific simulations.
  • Existing methods may suffer from biases or require extensive postprocessing.

Purpose of the Study:

  • To develop a new, bias-free method for true random number generation.
  • To achieve fast random bit generation without postprocessing.

Main Methods:

  • Utilizing the uncorrelated nature of laser pulses with Poissonian photon statistics.
  • Employing photon number detections to generate initial random bits.
  • Applying the von Neumann correction method for bias-free extraction of final random bits.

Main Results:

  • Demonstrated a bias-free random number generation method.
  • Achieved fast random bit generation, eliminating the need for postprocessing.
  • Validated the randomness of a prototype true random number generator using three statistical test batteries.

Conclusions:

  • The proposed method offers a novel and efficient approach to nondeterministic random number generation.
  • The technique leverages quantum phenomena for high-quality random bit production.
  • The realized true random number generator shows promising performance and reliability.