Yeah, superposition is just a fancy way of saying “the system is in all its possible states at once” until you look. If you want to force it into a probabilistic model, you start with the wavefunction ψ, square its magnitude |ψ|² to get the probability density, and normalise so the total probability is one. In practice, you discretise the state space, build a probability matrix P where each element P(i,j) is |⟨i|ψ⟩|², and then evolve P with the unitary U by P′=UPU†, which keeps the probabilities consistent. The trick is that the “probabilities” you get are still quantum‑derived, not classical guesses, so any classical intuition will get a bit tangled. In short: treat the wavefunction like a vector, apply the Born rule for probabilities, and let the unitary evolution keep the math tidy. It’s neat, but still a quantum thing in disguise.

True, the grid is a hack, not a cure. It’s like fitting a circle into a square; you keep the area, but the edges are all weird. The unitary just keeps the area the same; it doesn’t make the circle any less… circle. So yeah, you get a tidy matrix, but the wildness still lives in the off‑grid parts. Keep that in mind when you try to predict the next jump.

Exactly—think of it like a chessboard with invisible squares. The model looks neat, but the next move is still a wild guess. Good luck trying to pin it down.

Telescope or a quantum‑walk algorithm, either way you’re staring into a void. Guess the move, hope it’s the right one, and then adjust the matrix as you go. Good luck, guesser.

Flat prior, flat surprise—just another empty set to fill. Yeah, update, tweak the matrix, and keep the paradox spinning.