PeterDonis said:
When I asked for an explicit description I meant a description in words or math, something that everyone here could be expected to understand.
Actually, rather than wait for
@Boing3000 to do this, I'm going to give such a description of a straightforward algorithm using the QM math. Here, schematically, is such a description:
The algorithm assumes a number of "trials", each of which consists of making a polarization measurement on each of a pair of entangled photons. Each pair of photons is assumed to be prepared identically in the "PP" state (i.e., their polarizations are 100% correlated if measured at the same angle, and 100% anti-correlated if measured at angles 90 degrees apart). The photons in each pair are labeled A and B, corresponding to the locations of the polarizers that measure them. (Strictly speaking, each polarizer either passes its photon or not, and a photon detector after the polarizer either detects the photon or doesn't.)
The algorithm provides two functions, ##f_A## and ##f_B##, each of which takes defined inputs (given below) and outputs a measurement result for its corresponding photon for that trial. All of the information about the preparation procedure (identical for each trial) is encoded in these functions. So the only variables for each trial are the measurement settings (polarizer angles) at A and B; everything else is known in advance. Each measurement result is a boolean value: "1" means the photon was detected (i.e., passed the polarizer), "0" means the photon was not detected (did not pass the polarizer).
The inputs provided to the algorithm are the measurement settings (A, B) for each trial. These can be determined by any means desired, but they are external to the algorithm; the algorithm does not compute them, it just takes them as inputs. The input also, implicitly, determines the number of trials (by the number of pairs of settings that are provided).
According to Bell's Theorem, in order to properly reproduce the QM predictions (and the actual experimental results), each function, ##f_A## and ##f_B##, must take as inputs the measurement settings for that trial at
both A and B. It is impossible to have ##f_A## only take as input the settings for A, and ##f_B## only take as input the settings for B, and still reproduce the QM predictions.
I'll hold off on saying what the functions ##f_A## and ##f_B## actually are, for the case under discussion, since the above might already be enough to clarify what, exactly, the algorithm in question needs to compute and what inputs it takes.