There is no regular approximately invariant finitely additive probability measure on all subsets of a cube or ball

For a totally ordered field K, say a hyperreal one, write x≈y (and say that they are approximately equal) provided that x−y is 0 or infinitesimal. A K-valued probability P defined for all subsets of Ω is said to be regular provided that P(A)>0 whenever A is non-empty. It is approximately rigid motion invariant provided that P(A)≈P(gA) for every rigid motion g and set A such that A∪gA⊆Ω. The following can be proved in Zermelo-Fraenkel (ZF) set theory without any Axiom of Choice:

Theorem 1. There is no totally ordered field K and a regular K-valued approximately rigid motion invariant finitely additive probability on all subsets of a ball or cube Ω.

If we delete "approximately", this follows from this.

The result follows from this post. Given such a regular measure we can define a preorder ≤ by letting A≤B if and only if P(A)≤P(B). By the Theorem from that post, it follows in ZF that Banach-Tarski is true. But Banach-Tarski implies that there is no approximately rigid motion invariant finitely additive probability on all subsets of a ball or cube.

(Why ball or cube? This saves me from having to worry about some edge effects given our definition of invariance.)

Another result, proved by similar methods:

Theorem 2. Let Ω be a subset of three-dimensional Euclidean space invariant under rotations about the origin 0. If K is a totally ordered field and P is a regular K-valued finitely additive probability on all subsets of Ω approximately invariant under rotations about the origin, then P({0})≈1.

Suppose now that we have a particle undergoing Brownian motion released at time t₀ at the origin, and then observed at time t₁. The probability of its being in some set at t₁ should be at least approximately invariant under rotations, and of course it is unacceptable to say that the probability that it is at the origin is approximately one—on the contrary, with approximately unit probability it is going to be away from the origin.

Update: Similar things hold for full-conditional probabilities, where approximate invariance is replaced with
invariance conditionally on the whole space (but there is no requirement of invariance conditionally on subsets of the space).