  We classify all subsets $S$ of the projective Hilbert space with the following property: for every point $\pm s_0\in S$, the spherical projection of $S\backslash\{\pm s_0\}$ to the hyperplane orthogonal to $\pm s_0$ is isometric to $S\backslash\{\pm s_0\}$. In probabilistic terms, this means that we characterize all zero-mean Gaussian processes $Z=(Z(t))_{t\in T}$ with the property that for every $s_0\in T$ the conditional distribution of $(Z(t))_{t\in T}$ given that $Z(s_0)=0$ coincides with the distribution of $(\varphi(t; s_0) Z(t))_{t\in T}$ for some function $\varphi(t;s_0)$. A basic example of such process is the stationary zero-mean Gaussian process $(X(t))_{t\in\mathbb R}$ with covariance function $\mathbb E [X(s) X(t)] = 1/\cosh (t-s)$. We show that, in general, the process $Z$ can be decomposed into a union of mutually independent processes of two types: (i) processes of the form $(a(t) X(\psi(t)))_{t\in T}$, with $a: T\to \mathbb R$, $\psi(t): T\to \mathbb R$, and (ii) certain exceptional Gaussian processes defined on four-point index sets. The above problem is reduced to the classification of metric spaces in which in every triangle the largest side equals the sum of the remaining two sides. 
An infinite-dimensional helix invariant under spherical projections