Gaussian integral

E29365

The Gaussian integral is a fundamental result in mathematics that evaluates the integral of the exponential of a negative quadratic function over the entire real line, yielding a value proportional to the square root of π and underpinning the normal distribution in probability theory.

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Predicate Object
instanceOf definite integral
mathematical concept
appearsIn Brownian motion theory
central limit theorem proofs
heat equation solutions
category closed-form integrals
special integrals
condition a > 0 in ∫_{−∞}^{∞} e^{−a x^2} dx
consequence moments of the normal distribution are finite
convergenceReason rapid decay of e^{−x^2} at infinity
definedAs ∫_{−∞}^{∞} e^{−x^2} dx
dimension one-dimensional case of Gaussian measures
domainOfIntegration (−∞, ∞)
evaluationMethod squaring the integral and using polar coordinates
using the Gamma function Γ(1/2) = √π
field mathematical analysis
probability theory
statistics
generalization ∫_{−∞}^{∞} e^{−a x^2} dx = √(π/a)
historicalAttribution Carl Friedrich Gauss
implies ∫_{0}^{∞} e^{−x^2} dx = √π / 2
integrand e^{−x^2}
notation ∫_{−∞}^{∞} e^{−x^2} dx = √π
property convergent improper integral
relatedTo Gamma function
Laplace method
error function
multidimensional Gaussian integral
normal distribution
saddle-point approximation
standard normal distribution
requires a > 0 for convergence in ∫_{−∞}^{∞} e^{−a x^2} dx
role basis for defining Gaussian measure
normalization constant for Gaussian distributions
symmetryProperty even integrand
type Lebesgue integration
surface form: Lebesgue integral

improper Riemann integral
usedFor approximating sums by integrals in asymptotic analysis
computing partition functions of quadratic Hamiltonians
evaluating Fresnel-type integrals via transformations
usedIn Fourier analysis
derivation of the normal distribution
error function definition
path integrals
probability density normalization
quantum mechanics
statistical mechanics
value √π

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Carl Friedrich Gauss notableWork Gaussian integral