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Related Concept Videos

Correlations02:20

Correlations

35.8K
Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Correlation and Causation01:27

Correlation and Causation

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Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
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Correlation01:09

Correlation

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In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
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Frequency-dependent Selection01:21

Frequency-dependent Selection

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When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
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Correlation and Regression00:53

Correlation and Regression

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In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
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Coefficient of Correlation01:12

Coefficient of Correlation

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The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable x and the dependent variable y.
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...
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Related Experiment Video

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Triplet Fusion Upconversion Nanocapsule Synthesis
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Second-order photon correlation measurement with picosecond resolution using frequency upconversion.

Aymeric Delteil, Chun Tat Ngai, Thomas Fink

    Optics Letters
    |August 2, 2019
    PubMed
    Summary
    This summary is machine-generated.

    We developed a new method to measure the second-order correlation function (g^(2)(τ)) of light with high time resolution. This technique overcomes detector limitations, enabling quantum signature analysis of light sources with picosecond precision.

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    Area of Science:

    • Quantum Optics
    • Quantum Information Science
    • Photonics

    Background:

    • The second-order correlation function (g^(2)(τ)) is crucial for characterizing quantum light sources.
    • Experimental measurement of g^(2)(τ) is often limited by the timing jitter of single-photon detectors.

    Purpose of the Study:

    • To present a versatile technique for measuring g^(2)(τ) with enhanced time resolution.
    • To overcome the limitations imposed by detector jitter in quantum light analysis.

    Main Methods:

    • Utilizing frequency upconversion in a nonlinear waveguide to enhance time resolution.
    • Modeling pulse propagation and frequency conversion processes within the nonlinear waveguide.
    • Measuring g^(2)(τ) from diverse light signals, including quantum emitters.

    Main Results:

    • Achieved time resolution determined by the laser pulse length, surpassing detector jitter limitations.
    • Successfully measured g^(2)(τ) from a confined exciton-polariton structure.
    • Revealed quantum signatures of the emitter at picosecond timescales.

    Conclusions:

    • The developed frequency upconversion technique offers a versatile and high-time-resolution method for g^(2)(τ) measurements.
    • This technique significantly advances the characterization of quantum emitters for quantum information applications.
    • Demonstrated the capability to probe quantum phenomena at unprecedentedly short timescales.