232 From Classical Mechanics to Quantum Field Theory. A Tutorial
gets its main contribution from the interval (−c, c). The main properties of the
Gaussian measure are given by the average of its momenta,
•〈 1 〉c=1;
•〈x^2 m+1〉c=0;
•〈x^2 m〉c=(2m−1)!!〈x^2 〉m=(2m−1)!!c^2 m.
The last formula is known as Wick’s theorem.
All characteristics of Gaussian measures can be derived from the average of a
single special function
gc(y)=〈gc(y)〉c=e−
c 2 y 2
.
In particular, all momenta of the measure can be obtained from the derivatives of
gcat the origin
〈xm〉=(−i)m
dm
dym
gc
∣∣
∣
y=0
.
The multidimensional generalization is straightforward. LetCbe a positive,
symmetric matrix, i.e.
(x, Cy)=(Cx,y), (x, Cx)>0).
Positivity implies the non-degenerate character ofC,detC= 0, which guarantees
the existence of the inverse matrixC−^1.
The Gaussian probability measure is defined by
dμC=
e−^12 (x,C
− (^1) x)
√
2 πdetC
dnx.
The momenta of the multidimensional Gaussian measure are obtained in terms of
the covariance matrixC,
•〈 1 〉C=1;
•〈xi^1 xi^2 ...xi^2 m−^1 〉C=0;
•〈xi^1 xi^2 ...xi^2 m〉C=
1
2 mm!
∑
σ∈S 2 m
Cσ(i 1 )σ(i 2 )Cσ(i 3 )σ(i 4 )...Cσ(i 2 m− 1 σ(i 2 m)).
The last formula is the multidimensional Wick’s theorem. The generating function
ofdμCis
gC(y)=〈ei(x,y)〉C=e−^12 (y,Cy).
All the momenta of the Gaussian measure, can be obtained from the derivatives
ofgCat the origin
〈xi^1 xi^2 ...xim〉C=(−i)m ∂
mgC
∂xi 1 ∂xi 2 ...∂xim
∣∣
∣y=0.