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Related Concept Videos

Probability Distributions01:32

Probability Distributions

The probability of a random variable x  is the likelihood of its occurrence. A probability distribution represents the probabilities of a random variable using a formula, graph, or table. There are two types of probability distribution– discrete probability distribution and continuous probability distribution.
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson probability...
Poisson Probability Distribution01:09

Poisson Probability Distribution

A Poisson probability distribution is a discrete probability distribution. It gives the probability of a number of events occurring in a fixed interval of time or space if these events happen at a known average rate and independently of the time since the last event. For example, a book editor might be interested in the number of words spelled incorrectly in a particular book. It might be that, on average, there are five words spelled incorrectly in 100 pages. The interval is 100 pages.
The...
Sampling Distribution01:12

Sampling Distribution

Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...
Uniform Distribution01:19

Uniform Distribution

The uniform distribution is a continuous probability distribution of events with an equal probability of occurrence. This distribution is rectangular.Two essential properties of this distribution are The area under the rectangular shape equals 1. There is a correspondence between the probability of an event and the area under the curve.Further, the mean and standard deviation of the uniform distribution can be calculated when the lower and upper cut-offs, denoted as a and b,...
Binomial Probability Distribution01:15

Binomial Probability Distribution

A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
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Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this particular...

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Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
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Published on: May 30, 2014

Singular probability distribution of shot-noise driven systems.

Akihisa Ichiki1, Yukihiro Tadokoro, M I Dykman

  • 1Toyota Central R&D Labs., Inc., Nagakute, Aichi 480-1192, Japan.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|February 16, 2013
PubMed
Summary

Shot noise drives systems to exhibit power-law singularities in their coordinate distribution. These singularities form peaks, especially in the underdamped regime, revealing signatures of shot-noise fluctuations.

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Area of Science:

  • Statistical physics
  • Non-equilibrium systems
  • Stochastic processes

Background:

  • Understanding the behavior of systems subjected to random fluctuations is crucial.
  • Shot noise, characterized by discrete random pulses, introduces unique dynamics.
  • Previous studies have explored noise effects, but the specific impact of shot noise on probability distributions requires further investigation.

Purpose of the Study:

  • To investigate the stationary probability distribution of a system driven by shot noise.
  • To analyze the emergence and characteristics of singularities in the coordinate distribution.
  • To explore the influence of shot noise on both overdamped and underdamped regimes.

Main Methods:

  • Analytical derivation of the stationary probability distribution.
  • Identification of power-law singularities in the distribution.
  • Analysis of peak formation and position in both overdamped and underdamped systems.
  • Comparison of analytical findings with numerical simulations.

Main Results:

  • The coordinate distribution exhibits power-law singularities in its central part for both overdamped and underdamped systems.
  • These singularities manifest as distribution peaks at low noise pulse rates.
  • Peak positions in the underdamped regime follow a geometric progression.
  • The energy distribution in the underdamped case also shows multiple peaks with geometric progression positions.
  • Analytical results show excellent agreement with numerical simulations.

Conclusions:

  • Shot noise induces unique structures in the probability distribution of driven systems.
  • The observed power-law singularities and geometric progressions are signatures of shot-noise fluctuations.
  • The findings provide a deeper understanding of non-equilibrium statistical mechanics under shot noise conditions.