Revisiting Twistors

In twistor theory, α-planes are the building blocks of classical field theory in complexified compactified Minkowski space-time. The α-planes are totally null two-surfaces S in that, if p is any point on S, and if v and w are any two null tangent vectors at p ∈ S, the complexified Minkowski metric η satisfies the identity η(v,w) = vawa = 0. By definition, their null tangent vectors have the two-component spinor form λAπA, where λA is varying and πA is fixed. Therefore, the induced metric vanishes identically since η(v,w) = λAπA μAπA = 0 = η(v, v) = λAπA λAπA . One thus obtains a conformally invariant characterization of flat space-times. This definition can be generalized to complex or real Riemannian space-times with non-vanishing curvature, provided the Weyl curvature is anti-self-dual. One then finds that the curved metric g is such that g(v,w) = 0 on S, and the spinor field πA is covariantly constant on S. The corresponding holomorphic two-surfaces are called α-surfaces, and they form a three-complex-dimensional family. Twistor space is the space of all α-surfaces, and depends only on the conformal structure of complex space-time.

Projective twistor space PT is isomorphic to complex projective space CP3. The correspondence between flat space-time and twistor space shows that complex α-planes correspond to points in PT, and real null geodesics to points in PN, i.e. the space of null twistors. Moreover, a complex space-time point corresponds to a sphere in PT, and a real space-time point to a sphere in PN. Remarkably, the points x and y are null-separated iff the corresponding spheres in PT intersect. This is the twistor description of the light-cone structure of Minkowski space-time.

A conformally invariant isomorphism exists between the complex vector space of holomorphic solutions of  ◻φ = 0 on the forward tube of flat space-time, and the complex vector space of arbitrary complex-analytic functions of three variables, not subject to any differential equation. Moreover, when curvature is non-vanishing, there is a one-to-one correspondence between complex space-times with anti-self-dual Weyl curvature and scalar curvature R = 24Λ, and sufficiently small deformations of flat projective twistor space PT which preserve a one-form τ homogeneous of degree 2 and a three-form ρ homogeneous of degree 4, with τ ∧ dτ = 2Λρ. Thus, to solve the anti-self-dual Einstein equations, one has to study a geometric problem, i.e. finding the holomorphic curves in deformed projective twistor space.

Stationarity or Homogeneity of Random Fields

Let (Ω, F, P) be a probability space on which all random objects will be defined. A filtration {Ft : t ≥ 0} of σ-algebras, is fixed and defines the information available at each time t.

Random field: A real-valued random field is a family of random variables Z(x) indexed by x ∈ Rd together with a collection of distribution functions of the form Fx1,…,xn which satisfy

Fx1,…,xn(b1,…,bn) = P[Z(x1) ≤ b1,…,Z(xn) ≤ bn], b1,…,bn ∈ R

The mean function of Z is m(x) = E[Z(x)] whereas the covariance function and the correlation function are respectively defined as

R(x, y) = E[Z(x)Z(y)] − m(x)m(y)

c(x, y) = R(x, x)/√(R(x, x)R(y, y))

Notice that the covariance function of a random field Z is a non-negative definite function on Rd × Rd, that is if x1, . . . , xk is any collection of points in Rd, and ξ1, . . . , ξk are arbitrary real constants, then

l=1kj=1k ξlξj R(xl, xj) = ∑l=1kj=1k ξlξj E(Z(xl) Z(xj)) = E (∑j=1k ξj Z(xj))2 ≥ 0

Without loss of generality, we assumed m = 0. The property of non-negative definiteness characterizes covariance functions. Hence, given any function m : Rd → R and a non-negative definite function R : Rd × Rd → R, it is always possible to construct a random field for which m and R are the mean and covariance function, respectively.

Bochner’s Theorem: A continuous function R from Rd to the complex plane is non-negative definite if and only if it is the Fourier-Stieltjes transform of a measure F on Rd, that is the representation

R(x) = ∫Rd eix.λ dF(λ)

holds for x ∈ Rd. Here, x.λ denotes the scalar product ∑k=1d xkλk and F is a bounded,  real-valued function satisfying ∫A dF(λ) ≥ 0 ∀ measurable A ⊂ Rd

The cross covariance function is defined as R12(x, y) = E[Z1(x)Z2(y)] − m1(x)m2(y)

, where m1 and m2 are the respective mean functions. Obviously, R12(x, y) = R21(y, x). A family of processes Zι with ι belonging to some index set I can be considered as a process in the product space (Rd, I).

A central concept in the study of random fields is that of homogeneity or stationarity. A random field is homogeneous or (second-order) stationary if E[Z(x)2] is finite ∀ x and

• m(x) ≡ m is independent of x ∈ Rd

• R(x, y) solely depends on the difference x − y

Thus we may consider R(h) = Cov(Z(x), Z(x+h)) = E[Z(x) Z(x+h)] − m2, h ∈ Rd,

and denote R the covariance function of Z. In this case, the following correspondence exists between the covariance and correlation function, respectively:

c(h) = R(h)/R(o)

i.e. c(h) ∝ R(h). For this reason, the attention is confined to either c or R. Two stationary random fields Z1, Z2 are stationarily correlated if their cross covariance function R12(x, y) depends on the difference x − y only. The two random fields are uncorrelated if R12 vanishes identically.

An interesting special class of homogeneous random fields that often arise in practice is the class of isotropic fields. These are characterized by the property that the covariance function R depends only on the length ∥h∥ of the vector h:

R(h) = R(∥h∥) .

In many applications, random fields are considered as functions of “time” and “space”. In this case, the parameter set is most conveniently written as (t,x) with t ∈ R+ and x ∈ Rd. Such processes are often homogeneous in (t, x) and isotropic in x in the sense that

E[Z(t, x)Z(t + h, x + y)] = R(h, ∥y∥) ,

where R is a function from R2 into R. In such a situation, the covariance function can be written as

R(t, ∥x∥) = ∫Rλ=0 eitu Hd (λ ∥x∥) dG(u, λ),

where

Hd(r) = (2/r)(d – 2)/2 Γ(d/2) J(d – 2)/2 (r)

and Jm is the Bessel function of the first kind of order m and G is a multiple of a distribution function on the half plane {(λ,u)|λ ≥ 0,u ∈ R}.