Please don't take this as a joke, its actually a serious question. If it sounds silly its only because of my (lack of) understanding of probabilities, but my motivation is genuine.
Lets take the following 2 events:
- $A$: Shooting once at a bullseye and hitting at an specific point $P_A$.
- $B$: Shooting twice at a bullseye and hitting both times in the same point $P_B$.
Under classic asumptions (for some sensible definition of classic) both events have $0$ probability. Right?
Now suppose we have backwards time travel (despite physics contradictions). I can watch where the projectile hits the first time, then go back in time, and make a prediction with probability $1$ for $P_A$. However, even with time travel, event $B$ still has $0$ probability.
My questions are:
- Is there some real difference in how these two events are modeled, or interpreted, or is there (more probably) some logical flaw in my reasoning?
- Does this means that time travel is impossible from a logical point of view, without even looking at physics?
This is not a silly question at all. What you are wondering about is the dependence of the probability of an event on the protocol, and about the precise meaning of such claims as "the probability of even $E$ is $p$". A lot has been written about these issues.
Sometimes, probability is meant to reflect a frequency of occurrence. For instance, a typical interpretation of "the probability of rolling a 6 on an honest die is $1/6$" is that if you roll the die a lot of times, then about $1/6$ of the times you will have rolled a 6, and, moreover, the more times you roll, the closer the ratio will actually get to $1/6$ (kinda). This certainly agrees with our intuition acquired after playing with dice.
Other situation are quite different. For instance, "the probability that intelligent life exists outside of our solar system is 0.76" is not quite frequentists, but instead it is reflecting a certain state of knowledge. After all, either there is life out there or there isn't, so clearly the probability is either $0$ or $1$, we just don't know which.
Situation where the probability of an event seems to change drastically when the protocol changes do not require time-travel. A famous example is the Monty Hall Problem.
Mathematically, a common way to model probabilities is through measure theory, an approach initiated by Kolmogorov. However, there are other possibilities. For a very good discussion on the essence and foundations of probability I would recommend Jayness' Probability Theory - The Language of Science (I believe the first few chapters are freely available online.